Senior AI Engineer – Data, MLOps
Employment Information
Report this job
Job expired or something wrong with this job?
Job Description
Senior AI Engineer building production ML, GenAI, and MLOps solutions for Teradyne’s test automation business. Operationalizing enterprise AI across Azure, Google Cloud, Snowflake, and Microsoft Fabric.
Responsibilities:
- Design, build, and operationalize machine learning and AI solutions for Teradyne’s IT organization
- Translate business problems into predictive and classification models, GenAI assistants, RAG workflows, and intelligent process automation
- Design, develop, train, evaluate, and deploy end-to-end ML and generative AI solutions
- Build and integrate AI agents with enterprise data sources, APIs, and MCP servers
- Apply experimentation, model selection, and evaluation to deliver accurate and performant solutions
- Own the transition of internally developed AI solutions from build to production
- Define and certify release readiness according to AI Platform Operations Team standards
- Implement model lifecycle management, including versioning, model registry, retraining, promotion, and deprecation
- Define drift, degradation, and retraining criteria and drive tuning and remediation
- Provide technical input for runbooks, on-call processes, and handoff standards
- Engineer reusable, multi-environment MLOps/LLMOps pipelines
- Build CI/CD, testing, and infrastructure/configuration-as-code for models, prompts, and agents
- Establish automated offline and online evaluation and regression testing
- Define technical standards, reference patterns, reusable frameworks, processes, and playbooks
- Mentor and upskill engineers on ML/AI, MLOps/LLMOps, and agentic AI
- Implement responsible AI practices, security controls, observability, logging, and audit trails
- Monitor solution performance, quality, reliability, and cost and drive continuous 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
- At least 3 years building and operating production ML/AI systems
- Recent hands-on experience with generative and agentic AI
- Bachelor’s or advanced degree in Computer Science, Data Science, Engineering, or a related field
- Strong proficiency in Python and SQL
- Experience with scikit-learn, PyTorch, or TensorFlow
- Hands-on 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
- Experience with agentic AI orchestration frameworks, RAG, vector databases and embeddings, prompt engineering, MCP servers, and APIs
- Experience transitioning AI solutions from development into production ownership, including monitoring, drift detection, retraining, and support
- Strong knowledge of model evaluation and testing, AI observability, responsible AI, AI security, and governance frameworks
- Multicloud experience with Microsoft Azure as primary and Google Cloud as secondary
- Experience integrating with enterprise data on Snowflake and Microsoft Fabric
- Proven ability to mentor and upskill teams
- Strong collaboration and communication skills across technical and business teams
- Analytical mindset focused on 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
Similar Jobs
Senior Data Engineer
Engenheiro de Dados Sênior construindo pipelines medalhão no Databricks e Azure para cliente automotivo global. Garantindo governança, qualidade e CI/CD para habilitar BI e Data Science.
Senior Data Engineer
Senior Data Engineer building data contracts and Delta Sharing for JLL’s enterprise real estate data platform. Enabling governed, self-service access for analytics, reporting, and product teams.
Principal Cloud Data Engineer
Cloud data engineer building governed, AI-ready data pipelines for Teradyne’s global test and automation solutions. Enabling enterprise AI, analytics, and operational insights across multicloud platforms.
Data Architect, Informatica
Senior Data Architect designing Informatica, data governance, and hybrid-cloud solutions. Delivering enterprise architectures for Talan’s international technology consulting clients.
Data Architect, Informatica
Senior Data & Informatica Architect designing secure hybrid enterprise data architectures for Talan, an international technology consulting group. Leading Informatica, cloud, integration, governance, and data security initiatives.
Data Architect, Informatica
Senior Data & Informatica Architect designing secure hybrid enterprise architectures for Talan’s technology consulting clients. Leading data integration, governance, cloud, and Informatica architecture initiatives.
Data Platform Engineer
Data Platform Engineer building data pipelines, APIs, and risk knowledge graphs for Worth AI’s AI-powered decision-making products. Supporting real-time onboarding and trusted data services.
Data Engineer
Data Engineer maintaining ETL pipelines and data quality for Cotiviti’s healthcare data operations. Supporting scalable ingestion, warehousing, governance, and production data delivery.
Principal Data Architect
Principal Data Architect designing scalable GCP Data Lakehouse platforms for Egen’s data and insights consultancy. Leading client architecture, pipelines, governance, and technical delivery.
Lead Data Engineer
Senior Data Engineer building GCP data pipelines for Egen’s healthcare data innovation. Driving machine learning initiatives and data solutions that improve patient outcomes.
Vice President, Data Engineering
Vice President leading data strategy, architecture, and engineering for PICTON Investments, a Canadian alternative investment manager. Building financial data platforms supporting portfolios, analytics, risk, and AI.
Director of Data Engineering
Director of Data Engineering leading scalable, governed data platforms for OnTrac’s same-day and next-day U.S. delivery services. Overseeing pipelines, AI-ready data products, budgets, and engineering teams.
Engagement Lead – Enterprise Data Warehouse
Engagement Lead owning CIO-level client relationships and prioritizing enterprise data warehouse delivery. Shaping Snowflake remediation and Power BI dashboards for Bounteous, a global AI services firm.
Senior Data Engineer, Databricks
Engenheiro de Dados Sênior atuando em migração e engenharia de dados no Azure Databricks. Automatizando pipelines e assegurando governança, desempenho e integridade em ambientes críticos.
DBA, Bulk Data Management Engineer
DBA engineering Webbing’s global telecoms connectivity and IoT data platform. Managing PostgreSQL, telecom network databases, bulk data pipelines, governance, and disaster recovery.
DBA, Bulk Data Management Engineer
DBA engineering Webbing's global telecom connectivity and IoT platform across PostgreSQL, BSS, and network databases. Building resilient data operations, integrations, governance, and disaster recovery.
DBA, Bulk Data Management Engineer
DBA managing PostgreSQL, bulk data, and governance for Webbing’s global telecom connectivity and IoT platform. Building resilient databases, mediation pipelines, monitoring, and disaster recovery.
DBA, Bulk Data Management Engineer
DBA engineering PostgreSQL databases and bulk-data pipelines for Webbing’s global connectivity and IoT platform. Managing telecom network integrations, governance, high availability, and disaster recovery.
Data Engineer
Data Engineer diseñando pipelines, arquitecturas y plataformas de datos escalables para iCodde. Integrando, transformando y asegurando datos para análisis y decisiones operativas.
Collibra Engineer – Data Governance
Collibra Engineer improving data catalogs, metadata, and workflows for AMDEX.ai’s federal data modernization services. Supporting a DHS client with governance, quality, and interoperability.