Machine Learning Engineer Remote Jobs in North Carolina (US)
This page tracks remote machine learning engineer openings that are location-eligible for North Carolina.
This page tracks remote machine learning engineer openings that are location-eligible for North Carolina.
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We believe in the power of technology to improve lives, from new opportunities and mission-critical functionality to user experience. Our team is proud to partner with passionate companies focused on reducing energy consumption, curing disease, improving education, building smart cities, and more – and with leading Cloud providers, including Amazon Web Services (AWS) and Microsoft Azure.
Role Description We’re looking for a hands-on Senior AI/Machine Learning Engineer to design, build, and deploy AI and machine learning solutions that solve real business problems for our clients. This is a consulting role that blends hands-on engineering, applied AI/ML expertise, and client-facing advisory work. You’ll partner directly with client stakeholders to understand their goals, translate ambiguous problems into well-scoped solutions, and see your work through from prototype to production. Success in this role depends as much on communication, empathy, and professionalism as it does on technical depth. Key Responsibilities: - Own ML solutions end to end — framing the business problem, exploring data, training and evaluating models, and iterating based on rigorous error analysis — through to production deployment and monitoring. - Apply generative AI and LLMs where they fit the problem, selecting appropriate techniques and adapting as the field evolves. - Establish MLOps best practices: CI/CD for models, experiment tracking, model and drift monitoring, and responsible-AI practices. - Translate ambiguous business problems into well-scoped solutions, setting clear expectations on feasibility, timelines, and trade-offs. - Serve as a trusted technical advisor — presenting demos and recommendations, and explaining models, their limitations, and uncertainty clearly to audiences from engineers to executives. - Mentor teammates and collaborate across multi-disciplinary teams of engineers, data scientists, and designers. - Adapt quickly to new industries, tools, and client environments while staying current with the evolving AI landscape. - Operate as a flexible consulting engineer within DevIQ’s delivery model, contributing beyond AI/ML when project needs and team availability require it, including adjacent work such as discovery, data exploration, data engineering, application development, DevOps, solution documentation, technical analysis, internal tooling, or other client-supporting utility tasks. Qualifications - Machine learning depth. - 4+ years building, training, and deploying ML models in production — owning the modeling work, not just integrating model APIs. - Strong modeling fundamentals: framing a problem as a learning task, feature engineering, model selection, and reasoning about bias/variance, regularization, and overfitting. - Rigorous evaluation discipline: sound train/val/test methodology, avoiding data leakage, choosing metrics that fit the business goal, and error analysis to diagnose why a model underperforms. - Deep learning fundamentals — architectures, loss functions, training dynamics — enough to build and debug models in PyTorch or TensorFlow, not just call them. - Solid math/stats foundation (linear algebra, probability, statistics) and the judgment to know when ML is the right tool versus a simpler approach. - Hands-on LLM/generative-AI delivery — RAG, embeddings, fine-tuning, and major model APIs (e.g., Anthropic, OpenAI, Bedrock) — with judgment to choose between prompting, retrieval, and fine-tuning. - Strong Python and the modern ML stack (PyTorch or TensorFlow, scikit-learn), plus solid SQL. - Experience deploying and monitoring ML workloads on at least one major cloud (AWS, Azure, or GCP), including versioning, drift monitoring, and retraining. - Client-facing or consulting experience, able to explain technical trade-offs — including model limitations and uncertainty — to non-technical stakeholders. - Self-directed and comfortable with ambiguity across multiple engagements. - Willingness and ability to work beyond a narrowly defined AI/ML role, contributing to adjacent engineering, data, discovery, DevOps, consulting, and utility activities as needed in a project-based consulting environment. Requirements - Experience with Databricks, lakehouse architectures, or large-scale data engineering workflows. - Experience supporting pre-sales efforts (solution design, scoping, and estimating). - Depth in one or more ML domains — e.g., NLP, computer vision, time-series forecasting, or recommender systems. - Research or open-source signal in ML — publications, patents, notable contributions, or competition results. - Bachelor's or Master's degree in Computer Science, Machine Learning, or equivalent practical experience. Benefits - Competitive financial compensation and utilization bonus plans. - Medical, Dental, Vision Insurance. - 401k, With 4% Matching. - Paid Time Off. - Health Savings Account (HSA)/Flexible Spending Account (FSA). - Short-Term/Long-Term Disability Insurance. - Business funded Life Insurance Plan. - Dynamic yet relaxed work atmosphere. - Wide Variety of Growth Opportunities.
Waymo is an autonomous driving technology company creating a new way forward in mobility.
Role Description Waymo’s simulator is one of the most complex virtual environments ever built. It blends deterministic logic, physical dynamics, and state-of-the-art Generative AI to create a training ground for the Waymo Driver. The Simulator Evaluation team faces the ultimate data challenge: How do you mathematically prove that a virtual world is "real"? We are seeking visionary machine learning engineers and researchers to architect the scalable deep learning systems, novel data workflows, and eval tools that power our research roadmap. In this role, you will pioneer the machine learning and generative vision paradigms required to define and measure the realism of our multimodal world models. Your work will define the state of the art for autonomous simulation, directly steering our research trajectory and the capabilities of the Waymo Driver. You will: - Lead the design, development and deployment of cutting-edge evaluation approaches to assess realism of state-of-the-art multimodel world models and generative systems for simulation use cases at Waymo. - Architect and implement robust and scalable machine learning pipelines for tuning, evaluating, and deploying large-scale discriminator models for the purposes of simulator realism evaluation. - Evaluate open-source and production-ready video generation techniques that measure realism (e.g. temporal stability, multi-modal consistency, geometric discrepancy, condition following, etc.). - Apply vision language models to evaluate semantic understanding and controllability across our world simulation products. - Collaborate with research teams across Waymo and Alphabet to integrate advancements in 4D world modeling and generative AI into production systems. - Mentor engineers on the team and provide technical guidance on architecture and execution. Qualifications - Bachelor's, Master's, or PhD in computer science, machine learning, robotics, or a related field. - Five or more years of experience in machine learning engineering or applied deep learning, supported by a portfolio of shipped products or peer-reviewed publications. - Proficient programming skills in Python and hands-on experience with modern machine learning frameworks such as Jax, Flax, or PyTorch. - Experience designing and implementing evaluation frameworks for complex systems or machine learning models. Requirements - Track record of training large-scale generative models (diffusion models, flow matching, vision language models, etc.). - A PhD and demonstrated success delivering machine learning products focused on 3D generative models, world models, or video generation. - Experience simulating sensor data, including camera, lidar, and radar, or modeling semantic scenes. - Experience developing autonomous systems, robotics software, or autonomous vehicle simulations. - Experience training and optimizing large-scale models on GPU or TPU clusters for efficient production serving. - Professional experience writing C++ for high-performance production systems. Benefits - Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program. - Equity incentive plan. - Generous Company benefits program, subject to eligibility requirements. Salary Range The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. $213,000 — $263,000 USD
Since 1955, we have been leaders in tax preparation, financial services, and small business solutions. With 70,000 associates and 9,000 retail tax locations across North America, Australia, Ireland, and India, we have helped millions of clients and countless communities. If you embrace challenges as opportunities, value winning as a team, and seek to make a meaningful difference, join us on our journey.
Role Description The Machine Learning Operations (MLOps) Engineer is responsible for building and maintaining the infrastructure that supports the development, deployment, and monitoring of machine learning models. - Work closely with data scientists and other MLOps engineers to streamline workflows, automate processes, and ensure the scalability and reliability of ML systems in production environments. - Ensure that the team is able to offer machine learning model predictions at scale. - Deliver reliable, scalable ML systems that enable teams to move models from experimentation to production quickly and safely, while maintaining high standards for performance, security, and operational excellence. Qualifications - Bachelor’s degree in a related field or the equivalent through a combination of education and related work experience. - Ability to collaborate and solve problems effectively with excellent cross-team collaboration and communication skills. - Experience with Git. - Familiarity with cloud platforms such as AWS, Azure, or GCP, including deploying and operating services in cloud environments. - 3 years minimum related work experience. - Proficiency in Python and experience applying software engineering best practices (version control, testing, and code reviews). - Strong problem-solving skills, attention to detail, and ability to troubleshoot production issues. - Working knowledge of model governance concepts, including model versioning, experiment tracking, reproducibility, and rollback strategies. Requirements - Experience with Databricks, Azure Pipelines, and major cloud platforms (AWS, Azure, and GCP). - Experience with Docker, Kubernetes, SQL, and enterprise scale data management practices. - Working knowledge of Generative AI technologies and their operational considerations. Benefits - Competitive compensation and benefits to support your health and well-being. - Qualifying associates can enroll themselves and/or their eligible dependents in medical and prescription drug coverage. - Participation in the H&R Block Retirement Savings Plan (401(k) Plan). - Access to the Employee Assistance Program, (virtual) fitness center programs, and the associate discount program. - Automatic enrollment in Business Travel Accident Insurance. - Receive Associate Tax Prep benefit. Company Description Since 1955, we have been leaders in tax preparation, financial services, and small business solutions. With 70,000 associates and 9,000 retail tax locations across North America, Australia, Ireland, and India, we have helped millions of clients and countless communities. If you embrace challenges as opportunities, value winning as a team, and seek to make a meaningful difference, join us on our journey.
• Own the architecture of Workiva’s AI platform and core AI services • Shape how machine learning, Generative AI, and agentic systems are integrated across products • Lead the move from early adoption to production-grade, enterprise-ready systems • Define standards for model serving, retrieval, evaluation, governance, and platform reliability • Lead the design of enterprise agentic systems, including orchestration, workflow execution, memory, and multi-agent coordination • Design and evolve Retrieval-Augmented Generation capabilities for enterprise content and knowledge workflows • Establish evaluation methods and quality frameworks for Generative AI applications • Assess emerging AI technologies and guide adoption strategy for Workiva’s platform • Influence technical direction across teams, products, and platform domains • Mentor Staff and Senior Engineers and help raise the technical bar across the organization • Partner closely with Product, Security, Infrastructure, and Architecture leaders • Align teams around a shared vision for scalable, secure AI at Workiva • Lead secure AI platform design, including authorization, runtime isolation, governance, auditability, and compliance • Establish best practices for AI safety, model governance, and customer data protection • Ensure AI systems meet enterprise expectations for availability, resiliency, observability, and operational support • Design for fault tolerance and operational excellence in regulated, security-conscious environments
SS8 is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity or expression, sexual orientation, age, disability, protected veteran status, or any other status protected by applicable law. SS8 does not accept unsolicited resumes from staffing agencies, search firms, or third parties. Any resumes submitted without a signed agreement in place will be considered the property of Company, and no fees will be paid if a candidate is hired as a result.
Role Description We’re looking for a highly motivated and visionary Full-Stack Engineer with deep expertise in Artificial Intelligence to join our core engineering team. In this role, you will be instrumental in advancing our flagship platforms like Intellego® XT, Discovery, and LocationWise. You will design, build, and deploy complex end-to-end distributed systems and AI-powered applications that process massive volumes of multi-modal investigative data. Working at the intersection of full-stack engineering and AI, you will build next-generation web interfaces, geospatial intelligence tools, and generative AI pipelines that help law enforcement turn complex data into actionable clarity. What You'll Work On - Developing complex, end-to-end distributed web applications on cloud-native platforms, primarily utilizing AWS. - Integrating and deploying LLM and deep learning-based applications, including voice analytics (such as OpenAI Whisper), document analysis, and image/video intelligence (e.g., artifact detection) using open-source models. - Building interactive, LLM-driven frontends and complex UI applications involving dynamic dashboards and precise mapping/geolocation for our location intelligence products. - Designing scalable, high-throughput backend architectures utilizing Kubernetes, Kafka, Redis and distributed data stores. - Utilizing AI-assisted coding tools (like Claude Code, Codex, or Devin) to dramatically accelerate development, code reviews, and automated testing cycles. - Collaborating with cross-functional teams to engineer data platforms that fuse network intelligence, open-source intelligence, and high-precision location data into a "single pane of glass." Key Responsibilities - Architect, implement, and maintain high-performance full-stack applications using React (and related ecosystems) for the frontend and robust distributed technologies for the backend. - Design, implement and troubleshoot microservices within Kubernetes-based environments, ensuring high availability and fault tolerance. - Develop and optimize scalable data processing pipelines utilizing distributed systems theory, caching (Redis), search engines (OpenSearch), event streaming (Kafka), and diverse database architectures (Graph, Relational, Document, Multimodal). - Drive the operationalization of Deep Learning and Generative AI models into production environments to augment human analysts. - Implement secure, hardened access controls via robust OAuth and Active Directory (AD) integrations to maintain evidentiary integrity and auditability. - Lead by example in modern software engineering practices, leveraging AI coding assistants for enhanced productivity and mentoring peers. Required Experience & Qualifications - 5+ years of professional full-stack development experience building complex, large-scale distributed systems. Familiarity with Java, Python and JavaScript/Typescript based development. - Extensive hands-on experience with cloud-native platforms such as AWS (preferred), GCP, or Azure. - Proficiency in Kubernetes-based orchestration, deployment, and operational troubleshooting. - Solid engineering background in distributed systems and state management (Kafka, Redis, OpenSearch, and various multi-modal databases). - Deep expertise in frontend development using React.js, with a proven track record of delivering complex UIs (e.g., data-heavy dashboards, mapping, and geo-location products). Must Have - Verifiable experience building and deploying Deep Learning and Generative AI solutions (e.g., LLM-based UIs, voice/image/video analytics using open-source models). - Practical experience incorporating AI-assisted coding tools (Claude Code, GitHub Copilot/Codex, Devin) into your daily engineering workflow. - Strong understanding of enterprise security concepts, specifically OAuth and AD integration. Nice to Have - Hands-on DevOps, CI/CD, and infrastructure-as-code deployment experience, specifically within AWS. - Additional background in large-scale big data platform development, data crawling and data engineering/processing. - Previous experience in lawful intercept, telecommunications data (5G, IMSI/IMEI tracking), cybersecurity analytics, or digital forensics. - Proficiency with Golang and Rust. Compensation & Benefits - The expected base salary range for this position is $110,000 - $135,000. Actual compensation will be determined based on the candidate’s skills, experience, and qualifications. - This role is also eligible to participate in SS8’s corporate bonus program, subject to the terms of the applicable plan. - We offer a comprehensive benefits package including medical, dental, vision, 401(k) with company match, and paid time off. Equal Opportunity Employer SS8 is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity or expression, sexual orientation, age, disability, protected veteran status, or any other status protected by applicable law. SS8 does not accept unsolicited resumes from staffing agencies, search firms, or third parties. Any resumes submitted without a signed agreement in place will be considered the property of Company, and no fees will be paid if a candidate is hired as a result.
Enabling the development of electric vehicles of the future. From #materialscience to ultimate #emobility products.
Role Description We’re looking for an AI Software Engineer to help build the next generation of UJET's AI products: Spiral and AXO. This is a high-impact role for someone who thrives in ambiguity, enjoys moving across the stack, and wants to turn cutting-edge model capabilities into real-world product experiences. - Work across backend systems, AI services, product features, APIs, and infrastructure. - Build agent workflows in Python, ship customer-facing features in TypeScript, improve evals and reliability, or design systems that process large-scale conversational data securely and efficiently. This role is ideal for an engineer who is deeply practical about AI: someone who uses AI-assisted development naturally, understands how to build with and around LLMs, and cares about reliability, performance, and user impact as much as model quality. We value curiosity highly. The best people in this role are excited to dig into messy problems, ask good questions, and iterate until the system is measurably better. Qualifications - 3-5 years of professional software engineering experience, with strong hands-on experience building production systems. - Strong experience as a generalist engineer who can move fluidly between backend systems, frontend, AI services, APIs, and product development. - Excellent programming skills in Python and TypeScript. - Experience shipping AI agents, LLM-powered applications, or other production AI systems, including prompt and tool orchestration, evaluation, and cost/reliability tradeoffs. - Strong product instincts and comfort working in ambiguous environments where the right solution is not obvious at the start. - Experience building and operating systems on AWS/GCP in production. - Comfort working with large, messy datasets and building pipelines that turn unstructured inputs into dependable product functionality. - Strong SQL and data systems fundamentals. - A bias toward ownership, speed, and pragmatic execution. - Experience building AI-native products from 0 to 1. - Familiarity with conversational data, support platforms, CRM/CCaaS integrations, or customer experience tooling. - Experience with observability, evaluation frameworks, and production reliability for AI systems. Requirements - Build and own product and platform capabilities across Spiral and AXO, from early prototypes to production systems. - Design and implement AI-powered workflows, agent capabilities, and backend services that are scalable, secure, and reliable. - Develop high-performance APIs, async workers, and application logic in Python and TypeScript. - Ship user-facing product features and internal tools that make advanced AI systems useful and intuitive for customers. - Architect and improve data ingestion, parsing, and analysis pipelines that transform raw customer interaction data into structured, actionable insights. - Partner across engineering, product, and design to translate ambiguous product ideas into robust technical systems. - Own infrastructure and deployment patterns on AWS/GCP, with a focus on reproducibility, observability, security, and cost efficiency. - Improve system quality through evaluation, monitoring, logging, alerting, and operational best practices. - Help define engineering standards, review code, and mentor teammates working on distributed systems and AI applications. Benefits - Medical, dental, vision, 401(k) plan, commuter benefits, and more.
Dynatrace is a global application performance management software firm and a former member of Compuware. As an employer, the company is in support of helping its team achieve a hea
We put AI firstWe're looking for a Principal Generative AI Engineer to build AI systems that connect development workflows with production observability. You'll design and ship agentic tooling that helps engineers understand code, assess the impact of changes before they hit production, and act on real runtime signals. Your role at DynatraceWe are looking for a visionary, technically excellent engineer who is ready to design and ship production-grade agentic AI systems that bridge the gap between code context and runtime signals. You should thrive on a foundation of freedom, feedback, and responsibility, bringing a startup-like drive backed by the reach of a global platform. - Design, build, and ship agentic AI systems and tooling that helps engineers understand code, assess the impact of changes before they hit production, and act on real runtime signals. - Build production LLM systems end to end, managing prompting, tool calling, retrieval, memory management, and the agent loops that tie them together. - Define the evaluation strategies, metrics, and datasets that make agent quality measurable, ensuring we ship on evidence and catch regressions across model and prompt changes. - Connect development workflows with production observability, turning code context and runtime signals into reliable, actionable insight, and collaborate with product, design, and platform teams to identify developer problems. - Set technical strategy and architectural direction for the team's AI systems, mentor engineers across the organization, and take full ownership of systems using Dynatrace to monitor and optimize them. What will help you succeedYou are a seasoned technical leader with a strong software engineering foundation and proven hands-on experience deploying complex LLM applications. You possess the engineering judgment to navigate ambiguous, fast-moving spaces and set clear architectural direction for your team. - Degree in Software Engineering or equivalent practical experience in software development, combined with a track record of technical leadership and the judgment to set direction in an ambiguous, fast-moving space. - Extensive experience shipping production systems that use LLMs, including prompting, tool calling, evaluation, and iteration. - A strong foundation in at least one of: developer tooling (IDEs, compilers, static analysis, code intelligence), AI/ML engineering, or large-scale distributed systems. - Hands-on experience with agentic patterns, specifically planning, tool use, retrieval, and memory management. - The ability to evaluate and critique AI-generated output, understanding why a model is wrong, not just that it is, with familiarity with observability and the Dynatrace platform as a strong advantage. Why you will love being a Dynatracer - Dynatrace is a leader in unified observability and security. - We provide a culture of excellence with competitive compensation packages designed to recognize and reward performance. - Our employees work with the largest cloud providers, including AWS, Microsoft, and Google Cloud, and other leading partners worldwide to create strategic alliances. - You'll get to work at the forefront of innovation with Dynatrace Intelligence—the industry's first agentic operations system. Bringing together deterministic and agentic AI, it helps teams understand what's happening, why it matters, and what to do next— automatically. - Over 50% of the Fortune 100 companies are current customers of Dynatrace. Compensation and RewardsThe base salary range for this role is $146K - $220K. When determining your salary, we consider your experience, skills, education, and work location. Our total compensation package includes unlimited personal time off, an employee stock purchase plan, and a reward system. We also offer medical/dental benefits and a company-matched 401(k) plan for retirement. Equal Employment OpportunityDynatrace provides equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other protected characteristic. We actively foster an inclusive workplace that celebrates differences and promotes accessibility, collaboration, and growth for all.
Who we are Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale. Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term. About the role: We are looking for a Senior Machine Learning Engineer to lead the architectural evolution of our safety systems. You will move our ML stack from siloed, end-to-end models toward a unified Perception Platform Layer. Your mission is to build the robust infrastructure that translates raw sensor data into real-time, high-stakes decisions, ensuring our models perform reliably across both cloud and edge environments. This is a remote position for candidates based in the US. You should apply if: - You want to impact the industries that run our world: The software, firmware, and hardware you build will result in real-world impact—helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely. - You want to build for scale: With over 2.3 million IoT devices deployed to our global customers, you will work on a range of new and mature technologies driving scalable innovation for customers across industries driving the world's physical operations. - You are a life-long learner: We have ambitious goals. Every Samsarian has a growth mindset as we work with a wide range of technologies, challenges, and customers that push us to learn on the go. - You believe customers are more than a number: Samsara engineers enjoy a rare closeness to the end user and you will have the opportunity to participate in customer interviews, collaborate with customer success and product managers, and use metrics to ensure our work is translating into better customer outcomes. - You are a team player: Working on our Samsara Engineering teams requires a mix of independent effort and collaboration. Motivated by our mission, we’re all racing toward our connected operations vision, and we intend to win—together. In this role, you will work on the following: 1. Platform Architecture & Unification - Architect a Unified Perception Layer: Lead the transition from fragmented, task-specific models to a modular perception platform that supports reusable components and downstream safety applications. - System Design: Design and implement real-time ML systems—from sensor ingestion and tracking to risk reasoning and actuation—ensuring clear interfaces and predictable system behavior. - Hybrid Deployment: Orchestrate model integration across edge and cloud environments, managing versioning, rollouts, and mission-critical fallback mechanisms. 2. Performance & Reliability Engineering - Latency Ownership: Own end-to-end latency and reliability for safety-critical pipelines. You will profile, schedule, and optimize messaging and backpressure across the entire stack. - Observability & Feedback Loops: Build sophisticated monitoring for deployed models to detect drift, false positives/negatives, and latency regressions. You will "close the loop" to ensure production data informs the next iteration of training. 3. Rigorous Evaluation & Safety - Safety Cases: Develop evaluation frameworks specifically for rare "long-tail" safety events. You will define metrics and build targeted test sets that form the basis for principled ship/no-ship decisions. - Explainability: Partner with Applied Scientists to ensure research outputs are translated into production code that is not only performant but also debuggable and explainable. 4. Technical Leadership - Strategic Influence: Shape the system abstractions early in the platform transition to minimize technical debt and maximize future scalability. - Mentorship: Set the engineering standard for correctness and performance. You will mentor junior and mid-level engineers, fostering a culture of rigorous ML engineering. Minimum requirements for the role: - Experience: 6+ years of experience in ML Engineering, with a proven track record of shipping models in production (ideally in safety-critical domains like robotics, automotive, or industrial AI). - Systems Mastery: Deep understanding of distributed systems, performance profiling, and computer vision. - Infrastructure Fluency: Experience with Cloud ML workflows (AWS/GCP/Azure) and containerization, paired with an understanding of the constraints of edge hardware. - Architectural Mindset: You don't just write code; you design systems. You understand the trade-offs between model complexity and operational reliability. An ideal candidate also has: - Ph.D. in Computer Science or quantitative discipline (e.g., Applied Math, Physics, Statistics) - Experience with containerization technologies (e.g., Docker, Kubernetes), continuous integration/continuous deployment (CI/CD) pipelines, and infrastructure-as-code (IaC) frameworks - Familiar with deploying and managing ML applications in cloud environments, as well as leveraging cloud-based services for data storage, processing, and inference - Experience building end-to-end ML applications from scratch The range of annual base salary for full-time employees for this position is below. Please note that base pay offered may vary depending on factors including your city of residence, job-related knowledge, skills, and experience. This role is also eligible for an initial RSU grant with no vesting cliff, and ongoing refresh opportunities tied to performance, subject to plan terms and conditions. Learn more about our total rewards and benefits below. Annual Base Salary $243,100—$286,000 USD Total Rewards At Samsara, we build for the people who keep the global economy moving. We want owners, not passengers, which is why our rewards are designed to fuel high-impact builders. Our compensation program delivers above-market total compensation through a combination of base salary, performance-based bonus/variable pay, and equity (for eligible roles) in a high-growth public company. We meaningfully differentiate pay for our top performers, who have the opportunity to earn above-market compensation that can outpace the broader market over time. Beyond compensation, we provide the foundations that enable long-term success: a flexible, employee-led remote model, a professional development stipend, comprehensive health and parental leave plans, and more. If you’re ready to build for the long term and own the outcome, your journey starts here. Flexible Working At Samsara, we embrace a flexible working model that caters to the diverse needs of our teams. Our offices are open for those who prefer to work in-person and we also support remote work where it aligns with our operational requirements. For certain positions, being close to one of our offices or within a specific geographic area is important to facilitate collaboration, access to resources, or alignment with our service regions. In these cases, the job description will clearly indicate any working location requirements. Our goal is to ensure that all members of our team can contribute effectively, whether they are working on-site, in a hybrid model, or fully remotely. All offers of employment are contingent upon an individual’s ability to secure and maintain the legal right to work at the company and in the specified work location, if applicable. Belonging at Samsara At Samsara, we welcome everyone regardless of their background. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender, gender identity, sexual orientation, protected veteran status, disability, age, and other characteristics protected by law. We depend on the unique approaches of our team members to help us solve complex problems and want to ensure that Samsara is a place where people from all backgrounds can make an impact. Accommodations Samsara is an inclusive work environment, and we are committed to ensuring equal opportunity in employment for qualified persons with disabilities. Please email accessibleinterviewing@samsara.com or click here if you require any reasonable accommodations throughout the recruiting process. Our Commitment to Authenticity We use Tofu, a fraud detection tool, to validate the authenticity of applications and protect against identity fraud. This ensures we are connecting with real people and allows us to prioritize genuine candidates. Please see Samsara’s Candidate Privacy Notice for more information. Fraudulent Employment Offers Samsara is aware of scams involving fake job interviews and offers. Please know we do not charge fees to applicants at any stage of the hiring process. Official communication about your application will only come from emails ending in @samsara.com, @us-greenhouse-mail.io or @mail3.guide.co. For more information regarding fraudulent employment offers, please visit our blog post here.
Using CaaS (Codeless-as-a-Service) to accelerate time-to-market & eliminate legacy code for the enterprise 🚀
• Report directly to our VP of Agentic AI • Shape the core intelligence and behavior of the agent — how it interprets intent, plans, assists, and recovers from failure — so that it reliably helps users build working Unqork applications. • Help scale the backend that powers the agent in production, contributing to a service that stays fast, observable, and resilient as usage grows. • Drive how we measure and raise agent quality over time, turning real-world usage into a feedback loop that makes the product steadily more capable and trustworthy.
• Help build next-generation AI-powered product experiences. • Build AI-driven product features that integrate LLMs (like GPT, Claude, or Gemini) via APIs. • Prototype quickly and iterate fast, turning rough concepts into working interfaces and tools. • Develop front-end experiences in React that make complex AI outputs intuitive and delightful. • Collaborate with backend engineers to design APIs and data pipelines that support AI interactions. • Work across the stack when needed — from front-end interfaces to backend service integration in Python. • Experiment with new LLM capabilities, libraries, and prompt engineering approaches. • Contribute to internal tools for data cleaning, model evaluation, and content generation workflows.
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Python, Java, TypeScript, Cloud, Distributed Systems, Scala