Machine Learning Engineer Remote Jobs in Nebraska (US)

This page tracks remote machine learning engineer openings that are location-eligible for Nebraska.

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$32 - $180,000

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2575 Jobs

1400 Companies

Machine Learning Engineer IV

Avalara

Headquartered in Seattle, Washington, Avalara has been disrupting the world of sales tax management since its inception in 2004. Since the company was founded, its dedicated team h

Machine Learning Engineer5 hours ago

Full Time Remote Mid Level

Role Description Join Avalara's AI and Machine Learning team and help build intelligent systems that improve how businesses manage tax compliance and automation. You will design and deliver production-grade AI and ML solutions that power document intelligence, classification, retrieval, and GenAI-driven workflows across Avalara's products and platforms. You will work with engineers, product managers, infrastructure teams, and domain experts to turn complex challenges into scalable, reliable solutions that create measurable customer and growth. As a senior individual contributor, you will help raise the engineering bar through technical leadership, operational excellence, and mentorship. You will report to Sr Manager, ML Engineering with a #LI-Remote work arrangement. Responsibilities - Design, build, and improve production-grade machine learning systems for classification, document understanding, retrieval, and AI-powered automation. - Fine-tune, evaluate, and deploy transformer-based models, small language models, and other machine learning approaches to solve business problems. - Build and optimise real-time inference services, batch processing pipelines, APIs, and model-serving workflows. - Develop evaluation frameworks that measure model quality, reliability, latency, cost efficiency, and operational performance. - Contribute to GenAI platform capabilities including retrieval-augmented generation, embeddings, prompt orchestration, document ingestion, and agent-based workflows. - Deliver secure, scalable, and observable ML and AI services with operational ownership. - Partner with product, engineering, infrastructure, and business stakeholders to define and implement practical AI solutions. - Improve engineering quality through testing, monitoring, documentation, and continuous improvement practices. - Mentor engineers and share knowledge, frameworks, and reusable patterns that strengthen AI capabilities across the organisation. - Drive technical decisions by balancing accuracy, latency, scalability, maintainability, security, and cost. Qualifications - Bachelor's degree in Computer Science, Engineering, or a related technical field, with 5+ years of experience building and operating production machine learning or AI systems. - Strong software engineering experience in Python, including building backend services, APIs, or distributed systems. - Hands-on experience developing, evaluating, deploying, and maintaining machine learning models in production environments. - Experience with modern AI techniques such as transformers, embeddings, retrieval-augmented generation, large language models, small language models, classification systems, and document intelligence solutions. - Use data, experimentation, and production insights to improve measurable outcomes such as automation quality, reliability, latency, cost efficiency, and developer productivity. Benefits - Total Rewards: In addition to a great compensation package, paid time off, and paid parental leave, many Avalara employees are eligible for bonuses. - Health & Wellness: Benefits vary by location but generally include private medical, life, and disability insurance. - Inclusive culture and diversity: Avalara strongly supports diversity, equity, and inclusion, and is committed to integrating them into our business practices and our organizational culture. Company Description We’re defining the relationship between tax and tech. We’ve already built an industry-leading cloud compliance platform, processing over 54 billion customer API calls and over 6.6 million tax returns a year. Our growth is real - we're a billion dollar business - and we’re not slowing down until we’ve achieved our mission - to be part of every transaction in the world. We’re bright, innovative, and disruptive, like the orange we love to wear. It captures our quirky spirit and optimistic mindset. It shows off the culture we’ve designed, that empowers our people to win. We’ve been different from day one. Join us, and your career will be too. We’re An Equal Opportunity Employer: Supporting diversity and inclusion is a cornerstone of our company — we don’t want people to fit into our culture, but to enrich it. All qualified candidates will receive consideration for employment without regard to race, color, creed, religion, age, gender, national orientation, disability, sexual orientation, US Veteran status, or any other factor protected by law. If you require any reasonable adjustments during the recruitment process, please let us know.

View details: Machine Learning Engineer IV

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Senior Machine Learning Engineer, Recommendation

Sekai

If you are excited about building at the frontier of AI, consumer social, and interactive entertainment, we would love to hear from you. At Sekai, you will work with an AI-native team, move fast, own meaningful problems, and have the flexibility to explore new ideas from an early stage.

Machine Learning Engineer13 hours ago

Full Time Remote Senior

Role Description We are looking for a Senior Machine Learning Engineer to own search and recommendation systems for Sekai’s consumer product. This role sits at the center of content discovery, user engagement, and content distribution. You will build the models and systems that decide what users see, what they search for, what they continue playing, and how high-quality content reaches the right audience. This is a senior IC role for someone who has built real recommendation, search, ranking, or discovery systems in production for consumer apps, especially in entertainment-driven products. What You Will Own - Build and improve recommendation and search systems across feed, discovery, search, and content continuation surfaces. - Own retrieval and ranking systems, including candidate generation, embedding-based retrieval, two-tower models, ranking features, and online serving quality. - Design, launch, and analyze recommendation/search experiments end-to-end, then use the data to iterate quickly. - Improve recommendation quality for new users, new content, and fast-changing content pools. - Build user, content, creator, and session-level representations from behavioral signals. - Partner with product, data, and engineering teams to define metrics, run experiments, and ship measurable improvements to retention, engagement, and content distribution. - Build practical ML systems that can move from prototype to production quickly, with clear monitoring and evaluation. - Help shape the long-term ML architecture for AI-native content discovery. Qualifications - 5+ years of industry experience building production ML systems, with senior-level ownership of recommendation, search, ranking, ads ranking, feed ranking, or content discovery systems. - Hands-on experience building recommendation or search systems for consumer apps. - Experience working on entertainment, social, gaming, short-form content, creator, or other engagement-driven consumer products. - Strong practical experience with two-tower models, embedding retrieval, candidate generation, ranking, and online/offline evaluation. - Strong product intuition around relevance, retention, engagement, satisfaction, cold start, and content distribution. - Ability to translate messy user behavior into useful modeling signals and practical product improvements. - Strong engineering fundamentals across modeling, data pipelines, backend integration, experimentation, and production ML systems. - High ownership, fast execution, and clear communication in ambiguous product environments. Requirements - Experience with AI recommendation, LLM-powered ranking, semantic search, personalized generation, or AI-native content understanding. - Experience with UGC content ecosystems, creator marketplaces, or rapidly changing content catalogs. - Experience with multimodal content understanding across text, image, video, interaction traces, or generated content. - Experience with explore/exploit, contextual bandits, reinforcement learning, or long-term value optimization. - Startup experience or experience building 0-to-1 ML systems with limited infrastructure. Benefits - Top compensation package, including competitive salary and meaningful equity. - Remote-first team. - Comprehensive health insurance and benefits.

View details: Senior Machine Learning Engineer, Recommendation

Worldwide

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AI Architect

Guidewire Software

Engage, Innovate, Grow Efficiently

AI Engineer1 day ago

Full Time Remote LeadTeam 1,001-5,000Since 2001H1B Sponsor

Company Site LinkedIn

• Define and own Guidewire's enterprise AI architecture vision • Architect and lead delivery of production AI systems • Own the full-stack AI architecture • Help define enterprise AI security and governance standards • Lead complex, multi-team AI programs end to end • Help drive technology evaluation and build-vs-buy decisions • Partner with Data Governance, Security, Legal, and Compliance teams • Mentor senior engineers and foster a culture of technical excellence

AWS Guidewire

View details: AI Architect

United States

$132K - $198K / year

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Senior AI Engineer

NetCraftsmen, now BlueAlly

AI Engineer1 day ago

Full Time Remote SeniorTeam 51-200H1B No Sponsor

Company Site LinkedIn

• Design, build, and operate enterprise AI systems across our client portfolio. • Work end-to-end across the AI stack — from inference engines and platform infrastructure up through application-level engineering. • Lead end-to-end design, build, and operation of AI systems on AI Factory platforms across multiple client engagements. • Engineer and tune LLM inference serving stacks — primary depth in vLLM with breadth across the inference ecosystem — for client latency, throughput, and cost targets. • Tune inference performance through KV cache management, paged attention, batching strategies, and Dynamo-based disaggregated serving. • Architect and operate MLOps pipelines covering model lifecycle, registries, deployment, rollback, and observability. • Design and engineer RAG applications on top of vector databases. • Build and tune prompt-engineering patterns at production scale. • Engineer high-performance storage and networking for AI workloads. • Operate Kubernetes clusters underpinning AI workloads. • Build and maintain container images, registries, and CI/CD pipelines for AI/ML services. • Implement monitoring, alerting, logging, and capacity planning across the AI stack. • Harden environments to meet client security and compliance requirements. • Lead troubleshooting across various environments and technologies. • Engage directly with client stakeholders — technical and executive — to communicate status, root cause, options, and recommendations. • Mentor and code-review work from less senior engineers; raise the technical bar of every engagement you join. • Author runbooks, reference architectures, and knowledge base content; lead client knowledge transfer and enablement sessions. • Participate in on-call rotation and incident response for production AI workloads. • Contribute reusable patterns, tooling, and reference designs back to the practice.

DNS Docker Kubernetes Linux Python TCP/IP

View details: Senior AI Engineer

United States

$180K - $200K / year

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AI Engineer

Clera

Your talent agent for your entire career. Connecting you to startups backed by a16z, Index, YC & more.

AI Engineer1 day ago

Full Time Remote Mid LevelTeam 1-10Since 2025H1B No Sponsor

Company Site LinkedIn

Role Description This is a mid-level AI Engineer role on the core product team, focused on building agentic systems that automate complex, multi-step workflows across regulated and enterprise domains. You'll work across the full stack to ship production LLM-based services, ensure reliability and safety, and collaborate with leadership, product, and design to deliver measurable user impact. What You'll Do - Design, build, and maintain agentic systems that automate complex, multi-step workflows across healthcare, legal, fintech, logistics, and compliance domains. - Own production retrieval-augmented generation (RAG) pipelines and retrieval infrastructure including vector databases, embeddings, and indexing for domain-specific search at scale. - Implement multi-agent orchestration, tool-calling, memory, and reasoning components to deliver robust AI-driven user experiences. - Develop evaluation and safety infrastructure to measure model performance, surface regressions, and enforce enterprise-level trust and reliability. - Ship full-stack AI products from MVP to enterprise-grade by designing APIs and data models, implementing frontend and backend code, and operating production systems with CI/CD, monitoring, and testing. - Collaborate with leadership, product, and design to prioritize work, define success metrics, and iterate based on user feedback and telemetry. Qualifications - 2–8 years of software engineering experience with demonstrated delivery of shipped user-facing or backend products. - Practical experience deploying LLMs or LLM-based services in production, including prompt design, orchestration, and tool integration. - Proficiency across the stack: Python plus TypeScript/React (or equivalent), and experience with cloud platforms (AWS or GCP) and relational or NoSQL databases. - Working knowledge of RAG patterns, vector databases, embeddings, and retrieval pipelines, with sound judgment to choose appropriate approaches. - Experience building automated tests, evaluations, and monitoring for AI systems to ensure reliability beyond demos. - Experience with agent or workflow frameworks and orchestration tools. - Familiarity with fine-tuning, parameter-efficient tuning, or multi-modal model integration. - Background building multi-tenant or enterprise-ready systems, or experience in regulated industries such as healthcare, fintech, or legal. - Experience designing API-driven, high-throughput systems and real-time product features. - Proven ownership delivering end-to-end features from data model to deploy and monitoring, with a user-centric and pragmatic engineering mindset. Location - Remote or San Francisco, CA, United States.

View details: AI Engineer

United States

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Senior Engineer, AI-First Builder

Cruit Group

This is the ideal home for a builder who loves shipping real software fast, thrives in autonomy, and wants to work on massive enterprise modernization without the burden of maintaining archaic legacy code. You will have a direct hand in shaping how AI-driven engineering is executed at scale.

AI Engineer1 day ago

Full Time Remote Senior

Role Description The landscape of software development is undergoing a fundamental shift, and so is the way we build technology. We are pioneering the "Builder" role—a hybrid evolution designed for elite engineers who recognize that AI-first workflows can radically compress traditional development timelines. We are not looking for engineers who merely build AI solutions (like standard RAG apps or basic agent fine-tuning). We are seeking seasoned, masterful software engineers who were highly successful before the introduction of Large Language Models (LLMs), and who have now actively evolved their personal development workflows using AI to massively accelerate delivery. You will join a high-impact engineering delivery team initially aligned to a major digital transformation for a massive enterprise client, or leading a greenfield, AI-first operations platform build designed to completely replace a legacy system. What You'll Do - Accelerate the Lifecycle: Take complex business requirements and utilize advanced AI-assisted development tools (such as Claude, GitHub Copilot, etc.) to rapidly spin up MVPs and functional prototypes in hours rather than weeks. - Full-Lifecycle Engineering: Own the architectural planning, documentation, implementation planning, code generation, and product requirement/user story refinement process. - Client-Facing Impact: This role requires high emotional intelligence and exceptional communication. You will regularly interact with enterprise stakeholders, translating technical vision into clear business value. - Build From Scratch: Engage in true greenfield development, focusing on execution, speed, and practical, production-ready solutions over unnecessary over-engineering. Qualifications - Deep Engineering Roots: A strong, foundational background in core engineering principles. You must have a proven track record as a heavy-hitting engineer prior to the mainstream adoption of AI coding tools. - Advanced AI Workflows: You can articulately demonstrate exactly how AI has transformed your development process. We want to hear how you use AI for architectural planning, reviewing diverse technical approaches, research, and writing implementation plans—not just as a basic autocomplete tool. - Tech Stack Agnostic (With Strong Anchors): The core ecosystem for these initial enterprise initiatives leverages Azure, .NET/C#, and React. While an exact match is ideal, we value strong grounding in any robust backend technology, paired with a willingness to adapt. - Sharp, Independent Thinkers: You must be able to hold your own in deep technical conversations, think critically on your feet, and communicate crystal-clear concepts without relying on external aids or scripts. Benefits - 100% Remote (US-Based) - Mid-$150k – $170k base (Bonus Eligible) - Enterprise hardware provided Company Description This is the ideal home for a builder who loves shipping real software fast, thrives in autonomy, and wants to work on massive enterprise modernization without the burden of maintaining archaic legacy code. You will have a direct hand in shaping how AI-driven engineering is executed at scale.

View details: Senior Engineer, AI-First Builder

United States

$150K - $170K / year

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Intern – Generative AI Developer

Cotiviti

Founded in 1979, Cotiviti provides analytics-driven payment and network solutions for the healthcare and retail industries, offering services that help payers, risk-bearing healthc

AI Engineer1 day ago

Internship Remote Entry Level

• The Generative AI Developer Intern focuses on researching and developing advanced healthcare informatics, particularly in the realm of Generative AI and emerging Artificial General Intelligence. • The intern will assist and take a primary role in developing, researching, creating analytical materials, and collaborating with various teams to drive AI-related projects. • Gain hands-on experience in generative AI model development, architecture design, and database management. • Communicates technology-related updates and requirements to other departments and contributes to presentations for senior management. • Collaborates with research and development teams, product management, and strategic analysts to support ongoing projects. • Partners with Business Units to provide reliable intelligence, validated technology options, and insights on enterprise and industry trends. • Supports technology project teams by coordinating specific tasks, assisting with day-to-day operations, and contributing to the successful delivery of solutions. • Completes all responsibilities and goals outlined in the internship program. • Completes all special projects and other duties as assigned.

AWS Azure Cloud Realm

View details: Intern – Generative AI Developer

United States

$32 - $40 / hour

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Senior Director, AI Engineering

nexus IT group

AI Engineer2 days ago

Full Time Remote Lead

Role Description - Define and execute the organization's enterprise AI vision, strategy, and operating model. - Develop a multi-year roadmap for AI adoption, platform investments, business enablement, and technology modernization. - Establish governance, funding, prioritization, and success metrics for AI initiatives. - Build and manage a balanced portfolio of AI programs that drive business value while maintaining appropriate operational, security, and risk controls. - Evaluate emerging technologies and identify opportunities to improve business performance, customer experiences, operational efficiency, and employee productivity. - Serve as a trusted advisor to executive leadership on AI strategy, opportunities, risks, and industry trends. - Lead the development of enterprise AI platform capabilities that support scalable, secure, and reusable AI solutions. - Define architectural standards for intelligent applications, automation platforms, digital assistants, enterprise knowledge solutions, and AI-enabled workflows. - Establish foundational capabilities supporting: - Model access and orchestration - Knowledge retrieval and search - Enterprise data integration - Monitoring and observability - Security and governance controls - Drive adoption of AI-assisted software development practices across the software delivery lifecycle. - Partner with architecture, engineering, infrastructure, operations, security, and data teams to modernize technology delivery through AI-enabled capabilities. - Collaborate with business leaders to identify and prioritize high-value AI use cases. - Lead initiatives focused on: - Intelligent automation - Decision support systems - Document and knowledge management - Workflow optimization - Productivity enhancement - Customer and employee experience improvements - Develop frameworks for evaluating, prioritizing, and scaling AI opportunities across the organization. - Establish adoption strategies, change management programs, and success measurements for enterprise AI initiatives. - Build organizational AI literacy through education, enablement programs, and communities of practice. - Partner with risk, security, legal, compliance, and data governance stakeholders to ensure responsible AI adoption. - Embed security, privacy, transparency, human oversight, and operational controls into AI platforms and business solutions. - Support the development and operationalization of enterprise AI governance frameworks. - Balance innovation and experimentation with appropriate governance and risk management practices. - Promote ethical and responsible use of AI technologies across the organization. - Lead delivery of enterprise AI initiatives from strategy through implementation and adoption. - Establish delivery frameworks, operating models, and performance measures that ensure successful execution. - Manage technology investments, budgets, vendor relationships, and strategic partnerships. - Drive accountability for scope, timelines, quality, adoption, and business outcomes. - Ensure AI initiatives are scalable, supportable, and aligned with enterprise architecture and operational standards. - Build and lead a high-performing team of AI, engineering, architecture, automation, and technology professionals. - Foster a culture of innovation, experimentation, accountability, and continuous learning. - Mentor leaders and technical teams while establishing clear goals, priorities, and performance expectations. - Serve as a catalyst for organizational change and technology transformation. - Promote collaboration across business and technology functions to accelerate enterprise adoption. Qualifications - 15+ years of progressive leadership experience in technology, digital transformation, software engineering, architecture, data, automation, or emerging technologies. - Significant experience leading enterprise-scale AI, automation, analytics, or digital transformation initiatives. - Demonstrated success building and executing technology strategies that deliver measurable business outcomes. - Experience operating within highly regulated or complex enterprise environments preferred. - Strong understanding of modern AI and Generative AI technologies, including: - Large language models and foundation models - AI orchestration and workflow automation - Retrieval and knowledge-based architectures - Prompt engineering and evaluation methodologies - AI application development patterns - Experience with intelligent automation, AI-enabled software development, and enterprise AI platforms. - Familiarity with responsible AI principles, governance frameworks, model lifecycle management, and operational monitoring. - Strong technical foundation across cloud platforms, APIs, distributed systems, data architecture, cybersecurity, identity, and modern engineering practices. - Proven ability to align technology investments with strategic business objectives. - Strong executive communication and stakeholder management skills. - Experience influencing senior leadership and driving enterprise-wide change initiatives. - Demonstrated success managing teams, vendors, consulting partners, and complex delivery portfolios. - Strong financial acumen, including budgeting, investment planning, vendor management, and value realization. Education - Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related discipline required. - Advanced degree preferred. Leadership Characteristics - Strategic thinker with a passion for innovation and emerging technologies. - Hands-on leader who balances vision with execution. - Strong business acumen combined with deep technical credibility. - Collaborative influencer who builds alignment across diverse stakeholder groups. - Results-oriented operator focused on measurable outcomes and sustainable transformation. - Coach and mentor committed to developing talent and building high-performing teams.

View details: Senior Director, AI Engineering

United States

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AI/ML Engineer

VXForward

Machine Learning Engineer2 days ago

Full Time Remote SeniorTeam 1-10H1B No Sponsor

Company Site LinkedIn

• Design, develop, and deploy AI/ML solutions to modernize core pharmacy platforms, with a focus on scalability, reliability, performance, and security • Leverage Generative AI, LLMs, and agentic AI frameworks to automate and enhance pharmacy workflows and decision-making processes • Collaborate with business and technical stakeholders to understand pharmacy domain requirements and translate them into robust AI/ML-driven technical solutions • Contribute to architecture and technical design of AI/ML pipelines, including model selection, data integration, and deployment patterns • Establish and maintain AI/ML engineering standards, best practices, and quality assurance processes • Conduct code reviews, provide constructive feedback, and mentor engineers on modern AI/ML engineering practices • Partner with cross-functional teams including data scientists, product managers, platform engineers, and pharmacy domain experts • Translate legacy system modernization needs into scalable AI applications that enhance products, workflows, and operational efficiency • Monitor and optimize AI/ML model performance, resource utilization, and platform reliability • Collaborate with DevOps and infrastructure teams to ensure secure, scalable deployment and operations of AI/ML solutions • Stay current with advancements in AI/ML frameworks, Generative AI, LLMs, and pharmacy technology modernization

AWS Azure Cloud Distributed Systems Java JavaScript Python Go

View details: AI/ML Engineer

North America

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Senior AI-Machine Learning Engineer

Natera

Founded in 2004 and led by CEO Steve Chapman, Natera is a company in the biotechnology market that offers genetic testing and diagnostics on a global scale. Operating from its head

Machine Learning Engineer2 days ago

Full Time Remote Senior

Senior AI-Machine Learning Engineer US Remote Role Overview The Senior AI/ML Engineer is responsible for designing, building, and deploying Natera’s Generative AI and Machine Learning platforms. The role needs excellent hands-on engineering excellence to build robust, compliant, and efficient Generative AI and ML platform components. This role requires deep expertise in Generative AI and machine learning engineering at scale, with a passion for building robust, compliant, and high-performance systems that directly impact patient outcomes and clinical innovation. You will design, build, and scale enterprise-grade AI/ML systems that power internal workflows (R&D, Lab Ops, Clinical Trials, Billing, Patient/Provider engagement) and external-facing AI/ML platforms. You will design and build cutting-edge AI solutions leveraging agentic architecture, retrieval-augmented generation (RAG), vector search, feature stores, LLMOps, experimentation, observability, and compliance-first AI pipelines. You will be responsible for development of a production-ready Generative AI and MLOps platform with reusable components used to deploy multiple AI solutions across Natera’s business units. You will also develop clear standards and best practices established for AI/ML development across the organization. Key Responsibilities Platform Development - Design and implement foundational GenAI services: vector search, prompt tuning, agent orchestration, document extraction, context/memory services, model/endpoint registry, feature/embedding stores, guardrails, and evaluation pipelines - Build the underlying infrastructure for autonomous and semi-autonomous AI agents including support for agent collaboration, reasoning, and memory persistence, enabling continuous context-aware execution - Build standardized APIs/SDKs that make it easy for product teams to compose, deploy, and monitor Generative AI workloads. - Ensure platform components meet enterprise-grade requirements for scalability, latency, multi-region resilience, and cost efficiency Generative AI Enablement - Stand up LLM runtimes with token/rate governance, caching, and safe tool-use - Implement RAG at scale: ingestion pipelines, chunking/embedding policies, hybrid search, relevance/risk scoring, and feedback loops - Build agent orchestration (single & multi-agent) with planning, tool routing, shared/persistent memory, and inter-agent communication - Integrate tooling and APIs that allow agents to interact with internal systems, retrieve data securely, and take action under strict controls - Collaborate with research teams to prototype and productionize multi-agent architectures for workflow automation, report generation, and data synthesis. Infrastructure & Automation - Implement cloud-native infrastructure for large-scale model training and serving using Kubernetes, MLflow, Terraform, and AWS-native services - Automate data and model pipelines for RAG, LLM fine-tuning, and agent orchestration - Integrate observability tools (Datadog or equivalent) for real-time performance, drift detection and safety monitoring of AI outputs - Optimize compute and storage architecture to ensure cost-effective scaling of large models and multi-agent workloads - Partner with security, data governance, SRE, and application teams to productize platform capabilities Safety, Security & Compliance Integration - Embed compliance-by-design (HIPAA/CLIA/CAP/FDA/GDPR): PHI/PII handling, encryption, access controls, audit trails - Implement guardrails: input/output filters, prompt hardening, allow/deny policies for tool execution, policy-as-code in CI/CD - Bias/explainability hooks and automated evaluations for RAG/LLM/agents; drift and regression detection Technical Leadership & Mentorship - Establish golden paths (templates, examples, docs) and lead platform architecture reviews, code reviews, and design discussions - Partner with data scientists, AI researchers, and product engineers to deliver reliable and maintainable AI services - Mentor junior engineers in platform development, distributed systems, and agentic AI infrastructure concepts - Influence cross-functional roadmaps by partnering with Product and Engineering leadership to align delivery with business needs Qualifications Required: - 8+ years in software/ML engineering, with 5+ years in ML engineering at scale - Expertise in building production-grade ML/LLM systems on AWS tech stack (Python, TensorFlow/PyTorch, Spark, MLflow/Kubeflow, vector DBs) - Proven track record with GenAI/LLMs: fine-tuning, RAG, prompt orchestration, agentic systems, safety guardrails, monitoring, and cost optimization - Hands-on with RAG systems (embeddings, vector DBs, retrieval policies) and LLM runtime operations (caching, quotas, multi-model routing) - Experience building agentic AI platforms (LangChain, LlamaIndex, CrewAI, Semantic Kernel, or custom) - Deep knowledge of data-intensive systems, distributed architectures, and cloud-native development - Strong grounding in compliance-first engineering in healthcare, biotech, or diagnostics preferred - Track record building secure, compliant data/AI systems and automating policy checks. - Excellent ability to influence across teams, mentor engineers, and set technical standards Preferred: - Masters degree in Computer Science, AI/ML, engineering or related field - Experience in healthcare, pharma, diagnostics, or other regulated industries - Familiarity with AI governance frameworks, bias detection, explainability, and compliance (e.g., HIPAA, CLIA, FDA) The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations. Remote USA $125,000 - $156,300 USD OUR OPPORTUNITY Natera™ is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health. Our aim is to make personalized genetic testing and diagnostics part of the standard of care to protect health and enable earlier and more targeted interventions that lead to longer, healthier lives. The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions, who care deeply for our work and each other. When you join Natera, you’ll work hard and grow quickly. Working alongside the elite of the industry, you’ll be stretched and challenged, and take pride in being part of a company that is changing the landscape of genetic disease management. WHAT WE OFFER Competitive Benefits - Employee benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents. Additionally, Natera employees and their immediate families receive free testing in addition to fertility care benefits. Other benefits include pregnancy and baby bonding leave, 401k benefits, commuter benefits and much more. We also offer a generous employee referral program! For more information, visit www.natera.com. Natera is proud to be an Equal Opportunity Employer. We are committed to ensuring a diverse and inclusive workplace environment, and welcome people of different backgrounds, experiences, abilities and perspectives. Inclusive collaboration benefits our employees, our community and our patients, and is critical to our mission of changing the management of disease worldwide. All qualified applicants are encouraged to apply, and will be considered without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, age, veteran status, disability or any other legally protected status. We also consider qualified applicants regardless of criminal histories, consistent with applicable laws. If you are based in California, we encourage you to read this important information for California residents. Link: https://www.natera.com/notice-of-data-collection-california-residents/ Please be advised that Natera will reach out to candidates with a @natera.com email domain ONLY. Email communications from all other domain names are not from Natera or its employees and are fraudulent. Natera does not request interviews via text messages and does not ask for personal information until a candidate has engaged with the company and has spoken to a recruiter and the hiring team. Natera takes cyber crimes seriously, and will collaborate with law enforcement authorities to prosecute any related cyber crimes.

View details: Senior AI-Machine Learning Engineer

Worldwide

$125K - $156.3K / year

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