Senior AI Engineer – Data, MLOps

This is a fully remote position, open to applicants in Massachusetts.

📋 Description

• Design, construct, and operationalize machine learning and AI solutions for Teradyne’s IT department.

• Convert business challenges into predictive and classification models, GenAI assistants, RAG workflows, and intelligent process automation.

• Create, develop, train, assess, and deploy comprehensive ML and generative AI solutions.

• Develop and integrate AI agents with enterprise data sources, APIs, and MCP servers.

• Employ experimentation, model selection, and evaluation techniques to provide accurate and high-performance solutions.

• Manage the transition of internally developed AI solutions from development to production.

• Determine and certify release readiness in line with AI Platform Operations Team standards.

• Execute model lifecycle management, which includes versioning, model registry, retraining, promotion, and deprecation.

• Establish criteria for drift, degradation, and retraining, and oversee tuning and remediation efforts.

• Offer technical insights for runbooks, on-call processes, and handoff standards.

• Engineer reusable, multi-environment MLOps/LLMOps pipelines.

• Develop CI/CD, testing frameworks, and infrastructure/configuration-as-code for models, prompts, and agents.

• Set up automated offline and online evaluations and regression testing.

• Define technical standards, reference architectures, reusable frameworks, processes, and playbooks.

• Mentor and enhance the skills of engineers in ML/AI, MLOps/LLMOps, and agentic AI.

• Apply responsible AI practices, security measures, observability, logging, and audit trails.

• Monitor the performance, quality, reliability, and cost of solutions and drive ongoing improvement.

• Report to the Enterprise AI/Data Product Manager within Enterprise Architecture and Data.

⛳️ Requirements

• 8–10 years of experience in ML/AI or software engineering.

• Minimum of 3 years in building and managing production ML/AI systems.

• Recent practical experience with generative and agentic AI.

• Bachelor’s or advanced degree in Computer Science, Data Science, Engineering, or a related field.

• Strong expertise in Python and SQL.

• Experience with scikit-learn, PyTorch, or TensorFlow.

• Practical experience with Azure AI Foundry, Microsoft Copilot Studio, Anthropic Claude, Cursor, Google Vertex AI, or Snowflake Cortex AI.

• Proven MLOps/LLMOps experience, including multi-environment pipelines, CI/CD, Azure DevOps or GitHub Actions, Azure Machine Learning, MLflow, and model lifecycle management.

• Familiarity with agentic AI orchestration frameworks, RAG, vector databases and embeddings, prompt engineering, MCP servers, and APIs.

• Experience in transitioning AI solutions from development to production ownership, which includes monitoring, drift detection, retraining, and support.

• Strong understanding of model evaluation and testing, AI observability, responsible AI, AI security, and governance frameworks.

• Multicloud experience with Microsoft Azure as the primary cloud provider and Google Cloud as secondary.

• Experience integrating with enterprise data on Snowflake and Microsoft Fabric.

• Demonstrated ability to mentor and upskill teams.

• Excellent collaboration and communication skills with both technical and business teams.

• Analytical mindset focused on achieving measurable business outcomes.

🏝️ Benefits

• Discretionary bonus(es) based on financial performance.

• Medical insurance.

• Dental insurance.

• Vision insurance.

• Flexible Spending Accounts.

• Retirement savings plans.

• Life insurance.

• Disability insurance.

• Paid vacation and holidays.

• Tuition assistance programs.