Hire and mentor a blended team to machine learning, data and prompt engineers
Partner with KM on domain taxonomies, embeddings strategies, and feedback loops to continuously improve models.
Work with general counsel and privacy operations on confidentiality, data retention, vendor due diligence and AI policy – aligning to Goodwin Model Risk Management and Responsible AI standards.
Lead end to end lifecycle including problem framing, data pipelines, model selection, fine tuning, evals, deployment, monitoring and iteration
Architect RAG over privilege content with strict access controls.
Implement safety layers including prompt hardening and output filtering
Build evaluation and assurance reference sets from attorney labeled data, offline/online A/B and human in the loop review.
Own change management and adoption including training plans, playbooks and success metrics with named practice leaders.
Publish internal guidance on model cards, decision logs, user guidelines.
Requirements
10+ years building ML/AI products; 4+ years leading applied ML/LLM teams
Hands-on with modern LLM stacks, vector search, orchestration frameworks
Strong data engineering foundations (Python, PyTorch, Spark, SQL); MLOps (Docker, feature store, model registry)
Demonstrated experience with high sensitivity data and regulated deployments (privacy, privilege and auditability)
Great stakeholder management skills with attorneys / partners and business leaders.
Proven record translating ambiguity into shipped systems.
Benefits
Flexible work arrangements and hybrid work schedule
Health, dental, and vision insurance
Life and disability insurance
Retirement & Savings Plan
Emergency back-up child and adult care
Paid vacation, sick time off, and holidays
Professional development and career advancement opportunities
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