Machine Learning Engineer Remote Jobs in Utah (US)
This page tracks remote machine learning engineer openings that are location-eligible for Utah.
This page tracks remote machine learning engineer openings that are location-eligible for Utah.
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• Design, build, and operate core AI platform components used to train, deploy, and serve machine learning models in production environments. • Own model serving and inference workflows end-to-end, driving improvements in reliability, scalability, performance, and operational excellence. • Lead efforts to optimize inference systems for throughput, latency, and cost efficiency across CPU and GPU workloads. • Design and manage GPU-based inference and training workloads, including performance tuning, capacity planning, and resource utilization optimization. • Own and improve critical parts of the model lifecycle, including packaging, versioning, testing strategies, validation, and deployment automation. • Implement and evolve observability practices (metrics, logging, tracing, alerting) to improve visibility and operational resilience of ML services and pipelines. • Partner closely with product, infrastructure, security, and data teams to design scalable platform capabilities that enable AI-powered features. • Contribute to technical design discussions, propose architectural improvements, and mentor junior engineers through code reviews and knowledge sharing. • Participate in and help improve operational processes, including incident response, on-call rotations, and post-incident reviews.
Figma was founded in 2012 to build a collaborative, professional-grade interface design tool for the digital age. Created specifically for interface design and built entirely in th
Role Description Figma is evolving the Product Support experience, powered by AI, automation, and integrated systems. The AI Infrastructure & Tooling team helps make that possible by building intelligent, resilient, and integrated solutions that automate workflows, connect systems, and streamline support operations. As a Support AI Engineer on this team, you'll be the technical execution layer that brings our support tools, customer and account context, internal systems, and AI workflows together. This role is ideal for someone who can move from ambiguous support problems to working technical solutions: - Understanding the workflow - Identifying the systems involved - Building the integration or automation - Validating the data flow - Measuring the impact on customer outcomes and Specialist efficiency This is a full-time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: - Build and operationalize AI-powered workflows that improve Product Support experiences for customers and internal support teams. - Design and maintain integrations across Decagon, Zendesk, Figma admin tooling, internal data sources, and adjacent Product Support platforms. - Bring relevant customer, account, product, billing, file, or admin metadata into support conversations so chatbots and Specialists have the context they need to resolve issues more effectively. - Use LLMs and AI patterns for classification, summarization, routing, recommendations, context enrichment, and workflow automation. - Partner with Engineering, Analytics, Security, Programs, Support, and vendor teams to align on requirements, implementation, governance, and rollout. - Build quality checks, monitoring, fallback paths, and operational guardrails so AI-powered workflows can be trusted in production. - Define success metrics for each workflow, track adoption and impact, and iterate based on customer outcomes, Specialist efficiency, and adoption. Qualifications - 3+ years of experience shipping integrations, automations, or internal tools across customer-facing operational systems. - Strong coding or scripting ability, including experience with APIs, webhooks, data flows, and system and workflow data integrations. - Hands-on experience with LLM-powered workflows, AI automations, or AI-enabled customer/support experiences, including working with operational data to debug issues, improve workflows, and measure impact. - Strong product and stakeholder instincts: you can translate ambiguous support problems into practical, adopted, and measurable technical solutions. - Proven track record of designing AI workflows with clear guardrails, fallback paths, and responsible deployment practices. Requirements - Experience with support platforms like Zendesk, Decagon, Sprinklr, Gainsight, Maestro QA/Rippit, Assembled, Salesforce, or similar systems. - Familiarity with agent assist tooling, AI support chatbots, copilot tooling, RAG, AI observability, or monitoring AI workflows in production. - Experience building internal Slack tooling, workflow automations, or embedded support experiences. - Background in Support Engineering, Internal Tools Engineering, Solutions Engineering, Support Operations, CX Systems, or Business Systems. - Familiarity with customer support metrics such as containment, deflection, CSAT, first contact resolution, routing accuracy. Benefits - Equity to employees - Competitive package of additional benefits, including health, dental & vision - Retirement with company contribution - Parental leave & reproductive or family planning support - Mental health & wellness benefits - Generous PTO - Company recharge days - Learning & development stipend - Work from home stipend - Cell phone reimbursement - Sales incentive pay for most sales roles - Annual bonus plan for eligible non-sales roles
Innovation Team is an IT consulting company that provides specialized professional solutions and services to businesses.
Role Description As a Junior Computer Vision Engineer at InnovationTeam, you will be responsible for designing, developing, and deploying vision-based AI systems for real-world, production environments. You will work closely with cross-functional teams to build scalable image and video analytics solutions. - Develop and train Computer Vision models for image and video analysis. - Implement solutions for object detection, image classification, segmentation, and tracking. - Prepare and manage datasets, including data cleaning, labelling, and augmentation. - Optimize models for GPU performance, inference speed, and scalability. - Deploy AI models into production using APIs and containerized services. - Integrate Computer Vision models with broader AI and analytics platforms. - Collaborate with software engineers, data scientists, and product teams. - Maintain documentation and ensure code quality and reproducibility. Qualifications - Minimum 5 years of hands-on experience in AI / Machine Learning/Deep learning with a focus on Computer Vision. - Master’s degree in computer science, software Engineering, Artificial Intelligence, Engineering, or a related field. - Strong knowledge of Computer Vision concepts and algorithms. - Practical experience with CNN-based models and modern CV architectures. - Proficiency in Python and common ML/CV libraries (PyTorch or TensorFlow, OpenCV). - Experience with object detection and segmentation frameworks (e.g., YOLO, Detectron2). - Understanding of model evaluation, metrics, and performance optimization. - Experience deploying models in cloud or on-prem environments. - Familiarity with Docker and basic MLOps practices. - Excellent English communication skills (written and spoken). Requirements - Experience with video analytics or real-time inference. - Exposure to Vision Transformers or multimodal AI. - Experience with GPU-based training and inference. - Knowledge of cloud platforms (OCI, AWS, Azure, or GCP). - Background in domains such as healthcare, smart cities, or industrial AI. - Work on practical, production-grade Computer Vision solutions. - Access to GPU infrastructure and modern AI tooling. - Collaborative, engineering-focused work environment. - Opportunities for growth and advanced AI exposure. - Competitive compensation package.
Building the right solution for you!
• Model Implementation: Design, train, and fine-tune state-of-the-art ML models (Deep Learning, Transformers, Gradient Boosting, etc.) specifically optimized for our internal datasets. • End-to-End Pipeline Development: Build and maintain robust data pipelines and training workflows to ensure reproducible and scalable model development. • Optimization & Performance: Profile and optimize model latency and throughput for production environments. • Data Centricity: Perform deep exploratory data analysis (EDA) to identify biases, signal-to-noise ratios, and feature engineering opportunities within our unique data silos. • Collaboration: Work closely with Data Engineers to streamline data ingestion and Backend Engineers to integrate model APIs into our user-facing products.
Building Advance AI & Cloud Native Software Using The "Virtual Silicon Valley" Model. Let’s Talk AI, Cloud and Outcomes.
• Design and build AI agent pipelines and maintain RAG systems • Integrate and optimize Large Language Models and structured output workflows • Design, develop, and deploy product features and scalable backends • Collaborate with clients and stakeholders to translate business requirements into software solutions • Own observability and quality metrics for AI systems
We deliver the most advanced and flexible learning experience for certification, credentialing, test prep, continuing education, and training. Our cloud-based learning platform helps training organizations, associations, and the extended enterprise deliver a highly engaging and effective learning experience for individuals looking to advance their careers. We incorporate the latest in learner-centered technology, including personalization, gamification, data science, usability, and omni-channel delivery. We’re committed to helping people learn better, and that starts with our own people. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Role Description As a Senior Product Designer, you will collaborate closely with the patient matching team to deliver remarkable patient experiences for finding the right therapist, setting the experience north star. This is an opportunity to have an impact on Headway’s mission that makes mental health more accessible and affordable. - Use your interaction design, prototyping, and visual design skills to collaborate with a talented and mission-driven cross-functional team to evolve our product vision and build design solutions. - Contribute and evolve Headway design system (Helix) as we scale the provider experiences. - Contribute to the team culture, process, foundation and help grow a world-class startup design team. Qualifications - 5-8 years experience as a Product Designer. - Experience in delivering beautiful, innovative consumer-facing experiences; bonus if you’ve worked on mobile web. - Strong portfolio showcasing a diverse range of projects. - Motivated by our mission to solve the biggest problems in mental health care today (access and affordability). Requirements - Excited to jam in Figma with product and engineering partners daily. - Work with a user researcher to test your concepts weekly with potential patients. - Inspired by complex customer problems, early-stage product development, setting vision, and helping teams hold a high bar for craft. Benefits - Starting salary for Senior Product Designer, Patient Matching is $200,000. - Equity Compensation - Medical, Dental, and Vision coverage - HSA / FSA - 401K - Work-from-Home Stipend - Therapy Reimbursement - 16-week parental leave for eligible employees - Carrot Fertility annual reimbursement and membership - 13 paid holidays each year as well as a Holiday Break during the week between December 25th and December 31st - Flexible PTO - Employee Assistance Program (EAP) - Training and professional development
UPSTARS – продуктова IT-компанія, з якою злітають і люди, і бренди. Наш основний фокус – технологічні рішення та B2B-послуги для міжнародних клієнтів.
Role Description The AI Engineer is part of a highly collaborative team that develops cutting-edge machine learning (ML) and artificial intelligence (AI) models to solve complex business challenges and improve member health outcomes. In this role, you will work on high-impact projects involving advanced ML techniques, including large language models (LLMs) and generative AI. You’ll have the opportunity to experiment with state-of-the-art algorithms, push the boundaries of AI capabilities, and contribute to innovative solutions that drive real-world value. Qualifications - Bachelor's degree required; in lieu of a degree, six (6) years of relevant experience required. - Prior professional, co-op, or internship experience developing AI/ML solutions, or relevant coursework. - Basic understanding of fundamental ML concepts, algorithms, and statistical techniques. - Basic experience working with databases, SQL, and data manipulation. - Strong problem-solving skills and a willingness to learn. - Hands-on professional experience developing ML models for real-world applications. - Intermediate proficiency with cloud-based ML platforms (e.g., Databricks, AWS SageMaker, or Azure ML). - Intermediate knowledge of model performance monitoring and optimization techniques. - Experience working with large-scale data pipelines and distributed computing frameworks (e.g., Spark). - Familiarity with CI/CD and ML Ops/LLM Ops principles to collaborate effectively with deployment teams. - Experience working with large language models (LLMs) and generative AI technologies. - Ability to present clear and concise technical concepts to both technical and non-technical stakeholders. - Significant professional experience and knowledge in AI/ML engineering with a track record of developing models at scale. - Advanced proficiency in AI/ML model architecture, optimization, and explainability techniques. - Advanced experience integrating AI solutions with business applications and APIs. - Extensive experience working with large language models (LLMs) and generative AI in production environments. - Advanced understanding of AI model lifecycle management, governance, and operationalization. - Leadership experience in mentoring and guiding AI engineering best practices. - Strong ability to engage with executives and business leaders to drive AI strategy. Requirements - Develops Artificial Intelligence and Machine Learning solutions to solve business problems and improve member health outcomes, incorporating (but not limited to): - Large language models (LLMs) and generative AI applications - Machine learning models - Natural language processing (NLP) - Optimization and mathematical programming - Recommendation systems - Builds and refines data pipelines for feature engineering and ML model input, ensuring efficient and scalable data handling. - Collaborates with data engineering teams to acquire, clean, and prepare data for model training. - Supports model evaluation, testing, and performance monitoring in pre-production environments. - Works within cloud-based ML platforms (e.g., Databricks) to develop and optimize AI models. - Understands ML Operations principles and collaborates with CI/CD and ML Operations engineers for model deployment and monitoring. - Participates in peer code reviews and follows best practices for software development in AI. - Stays up to date with industry trends and new developments in AI/ML. - Develops and refines prompt engineering techniques for optimizing interactions with LLMs and generative AI applications. - Consistently demonstrates high standards of integrity by supporting the Lifetime Healthcare Companies’ mission and values, adhering to the Corporate Code of Conduct, and leading to the Lifetime Way values and beliefs. - Maintains high regard for member privacy in accordance with the corporate privacy policies and procedures. - Regular and reliable attendance is expected and required. - Performs other functions as assigned by management. - Contributes to the AI/ML model lifecycle, ensuring reproducibility, scalability, and maintainability of solutions. - Works with stakeholders to translate business objectives into AI/ML formulations and measurable success criteria. - Optimizes and fine-tunes ML models for performance, explainability, and efficiency. - Develops solutions using large language models (LLMs) and generative AI frameworks. - Supports the integration of AI models with enterprise applications, APIs, or data pipelines. - Engages in continuous learning and shares knowledge on new ML techniques and best practices. - Enhances team efficiency through the adoption of automation tools for model training, evaluation, and monitoring. - Leads the discovery and solutioning process, working with company stakeholders to identify high-impact AI opportunities. - Designs and implements scalable AI architectures that integrate with enterprise systems and support business operations. - Leads initiatives related to large language models (LLMs) and generative AI, ensuring alignment with business needs. - Mentors junior team members and fosters a culture of engineering excellence. - Collaborates with Operations and CI/CD teams to improve AI model deployment pipelines and monitoring strategies. - Recommends and influences best practices for AI model governance, versioning, and compliance. - Engages with leadership and cross-functional teams to align AI strategies with business goals. Benefits - Participation in group health and/or dental insurance - Retirement plan - Wellness program - Paid time away from work - Paid holidays Compensation Range(s) - Level I Min - 65,346 Max - 117,622 - Level II Min - 79,068 Max - 142,322
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or disability.
Role Description The Machine Learning Researcher is responsible for the development, evaluation, and optimization of machine learning and deep learning algorithms that support innovative digital dentistry solutions. This role focuses on advancing artificial intelligence capabilities through research, model development, and collaboration with cross-functional teams to translate cutting-edge technologies into high-impact product features. Working closely with software engineers, data engineers, product teams, and clinical experts, the Machine Learning Researcher contributes to the full machine learning lifecycle, including: - Data preparation - Model training - Validation - Deployment support - Intellectual property development Qualifications - Bachelor’s or master’s degree in computer science, Data Science, Mathematics, Statistics, Engineering, or a related STEM discipline. - Strong understanding of machine learning, deep learning, statistics, and applied mathematics. - Minimum of 3 years of experience developing machine learning solutions, preferably within a regulated medical device, healthcare, or life sciences environment. - Proficiency in Python and machine learning development workflows. - Hands-on experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras. - Experience with software development and best practices, including source control systems (e.g., Git). - Strong analytical and problem-solving skills with the ability to independently investigate complex technical challenges. - Demonstrated ability to learn new technologies quickly and contribute effectively within cross-functional teams. - Excellent written and verbal communication skills. Requirements - Define machine learning and data science requirements for new product features and capabilities. - Design, train, validate, and optimize machine learning models, with a focus on deep neural networks and computer vision applications. - Develop algorithms utilizing dental imaging data, including 2D and 3D radiographic images, CBCT scans, and intraoral optical scans. - Evaluate and improve existing machine learning models using state-of-the-art methodologies and published research. - Establish appropriate performance metrics, validation strategies, and error analysis approaches to ensure robust model performance. - Design and implement efficient algorithms and data structures for model training and inference. - Collaborate with software engineers and data engineers to improve data pipelines, data management processes, and model deployment workflows. - Define data requirements for training, validation, and performance evaluation. - Develop data preprocessing and postprocessing pipelines aligned with product and feature requirements. - Support the integration of machine learning solutions into commercial software products. - Monitor advancements in machine learning, deep learning, computer vision, and related research domains. - Assess emerging technologies and recommend opportunities for application within product development. - Contribute to intellectual property generation, including invention disclosures, patent applications, and technical documentation. - Collaborate with legal and intellectual property teams to support patent prosecution and maintenance activities. - Ensure development activities align with applicable quality management systems and medical device regulations. - Support documentation and validation activities required for regulated software products. Benefits - Primarily remote position with occasional travel as required. - Collaboration with global cross-functional teams across multiple time zones. - Participation in research, product development, and innovation initiatives supporting digital dentistry solutions. Company Description All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or disability. Employment Type: Full Time Alternative Locations: United States : Andover (MA) Travel Percentage: 0 - 10% Requisition ID: 21283
Peraton Corporation, a national security company headquartered in Herndon, Virginia, supplies solutions for mission-critical programs and systems. Founded in 2017, Peraton's missio
Role Description Peraton is seeking an experienced Generative AI Specialist to support high-impact Internal Research and Development (IRAD) initiatives focused on AI/ML-driven platforms for Operations in the Information Environment (OIE). This role is central to delivering advanced generative AI capabilities supporting COCOM information operations across CENTCOM, NORTHCOM, INDOPACOM, AFRICOM, and EUCOM. You will drive innovation in LLMs, agentic AI workflows, and generative AI application development—directly influencing Peraton’s competitive position in the defense AI landscape. - Design and optimize generative AI solutions using GPT 4, Claude, Gemini, and Azure OpenAI, including prompt engineering, fine-tuning, and retrieval augmented generation (RAG). - Implement agentic LLM architectures with structured output (JSON/GeoJSON), chain-of-thought/chain-of-debate methods, and multi-agent orchestration. - Build and maintain prompt libraries, evaluation frameworks, and QA pipelines for defense-grade AI content. - Integrate generative AI into existing platforms via well-documented APIs, ensuring interoperability with DoD systems including Maven, C2IE, and IRIS. - Research emerging generative AI techniques including multimodal models, synthetic data generation, and AI-assisted analysis for information operations. - Translate COCOM operational requirements into deployable AI solutions; support TTX events and platform demonstrations. - Implement responsible AI practices including bias detection, validation, hallucination mitigation, and HITL workflows. - Support MVP-aligned milestone delivery, contributing to TRL progression and ROI measurement. - Document novel prompting techniques, model configurations, and workflows that may constitute IP or trade secrets. Qualifications - Bachelor’s degree in a related technical field + 5 years relevant experience. - An additional 4 years will be considered in lieu of the bachelor's degree requirement. - 3+ years in software development or data science, including 2+ years focused on generative AI, LLMs, or NLP. - Hands-on experience with foundation models (GPT 4, Claude, Gemini, Llama, Mistral) including prompt engineering, few-shot learning, fine-tuning, and API integration. - Strong Python skills; experience with LangChain, LlamaIndex, Hugging Face, OpenAI/Anthropic APIs. - Experience building RAG systems using vector databases (Pinecone, Weaviate, ChromaDB, pgvector). - Cloud experience (AWS, Azure) and deploying AI/ML models in production environments. - Understanding of AI safety, hallucination mitigation, bias reduction, and prompt-injection protection. - Experience with Git, CI/CD, and DevSecOps practices. - U.S. citizenship required. - Ability to obtain Secret and final TS/SCI security clearances. - Current, valid U.S. passport for potential OCONUS travel. Requirements - Master’s degree. - Experience with agentic AI architectures, multi-agent workflows, and LLM tool-use. - Hands-on experience with fine-tuning, RLHF, DPO, LoRA/QLoRA. - Familiarity with multimodal models and defense/intelligence applications. - Experience with IRIS, OMEGA, or similar operational platforms. - Background supporting IO, PSYOP, influence analysis, or COCOM operations. - Knowledge of MLOps, A/B testing, and LLM evaluation frameworks (RAGAS, DeepEval). - Experience with synthetic data generation, simulation, or Monte Carlo methods. - Understanding of geospatial data formats (GeoJSON, KML) and visualization tools (Plotly, D3.js). - Strong communication skills for technical-to-nontechnical translation and customer demos. - Relevant cloud/AI certifications (AWS, Azure, Google, DeepLearning.AI). Benefits - Target Salary Range: $135,000 - $216,000. - This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual’s experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. - Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay. Company Description Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world’s leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees do the can’t be done by solving the most daunting challenges facing our customers.
UPSTARS – продуктова IT-компанія, з якою злітають і люди, і бренди. Наш основний фокус – технологічні рішення та B2B-послуги для міжнародних клієнтів.
Role Description The AI Engineer is part of a highly collaborative team that develops cutting-edge machine learning (ML) and artificial intelligence (AI) models to solve complex business challenges and improve member health outcomes. In this role, you will work on high-impact projects involving advanced ML techniques, including large language models (LLMs) and generative AI. You’ll have the opportunity to experiment with state-of-the-art algorithms, push the boundaries of AI capabilities, and contribute to innovative solutions that drive real-world value. Qualifications - Bachelor's degree required; in lieu of a degree, six (6) years of relevant experience required. - Prior professional, co-op, or internship experience developing AI/ML solutions, or relevant coursework. - Basic understanding of fundamental ML concepts, algorithms, and statistical techniques. - Basic experience working with databases, SQL, and data manipulation. - Strong problem-solving skills and a willingness to learn. - Hands-on professional experience developing ML models for real-world applications. - Intermediate proficiency with cloud-based ML platforms (e.g., Databricks, AWS SageMaker, or Azure ML). - Intermediate knowledge of model performance monitoring and optimization techniques. - Experience working with large-scale data pipelines and distributed computing frameworks (e.g., Spark). - Familiarity with CI/CD and ML Ops/LLM Ops principles to collaborate effectively with deployment teams. - Experience working with large language models (LLMs) and generative AI technologies. - Ability to present clear and concise technical concepts to both technical and non-technical stakeholders. - Significant professional experience and knowledge in AI/ML engineering with a track record of developing models at scale. - Advanced proficiency in AI/ML model architecture, optimization, and explainability techniques. - Advanced experience integrating AI solutions with business applications and APIs. - Extensive experience working with large language models (LLMs) and generative AI in production environments. - Advanced understanding of AI model lifecycle management, governance, and operationalization. - Leadership experience in mentoring and guiding AI engineering best practices. - Strong ability to engage with executives and business leaders to drive AI strategy. Requirements - Develops Artificial Intelligence and Machine Learning solutions to solve business problems and improve member health outcomes, incorporating (but not limited to): - Large language models (LLMs) and generative AI applications - Machine learning models - Natural language processing (NLP) - Optimization and mathematical programming - Recommendation systems - Builds and refines data pipelines for feature engineering and ML model input, ensuring efficient and scalable data handling. - Collaborates with data engineering teams to acquire, clean, and prepare data for model training. - Supports model evaluation, testing, and performance monitoring in pre-production environments. - Works within cloud-based ML platforms (e.g., Databricks) to develop and optimize AI models. - Understands ML Operations principles and collaborates with CI/CD and ML Operations engineers for model deployment and monitoring. - Participates in peer code reviews and follows best practices for software development in AI. - Stays up to date with industry trends and new developments in AI/ML. - Develops and refines prompt engineering techniques for optimizing interactions with LLMs and generative AI applications. - Consistently demonstrates high standards of integrity by supporting the Lifetime Healthcare Companies’ mission and values, adhering to the Corporate Code of Conduct, and leading to the Lifetime Way values and beliefs. - Maintains high regard for member privacy in accordance with the corporate privacy policies and procedures. - Regular and reliable attendance is expected and required. - Performs other functions as assigned by management. - Contributes to the AI/ML model lifecycle, ensuring reproducibility, scalability, and maintainability of solutions. - Works with stakeholders to translate business objectives into AI/ML formulations and measurable success criteria. - Optimizes and fine-tunes ML models for performance, explainability, and efficiency. - Develops solutions using large language models (LLMs) and generative AI frameworks. - Supports the integration of AI models with enterprise applications, APIs, or data pipelines. - Engages in continuous learning and shares knowledge on new ML techniques and best practices. - Enhances team efficiency through the adoption of automation tools for model training, evaluation, and monitoring. - Leads the discovery and solutioning process, working with company stakeholders to identify high-impact AI opportunities. - Designs and implements scalable AI architectures that integrate with enterprise systems and support business operations. - Leads initiatives related to large language models (LLMs) and generative AI, ensuring alignment with business needs. - Mentors junior team members and fosters a culture of engineering excellence. - Collaborates with Operations and CI/CD teams to improve AI model deployment pipelines and monitoring strategies. - Recommends and influences best practices for AI model governance, versioning, and compliance. - Engages with leadership and cross-functional teams to align AI strategies with business goals. Benefits - Participation in group health and/or dental insurance - Retirement plan - Wellness program - Paid time away from work - Paid holidays Compensation Range(s) - Level I Min - 65,346 Max - 117,622 - Level II Min - 79,068 Max - 142,322
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Python, PyTorch, Cloud, Distributed Systems, Spark, SQL