Architect and build agentic AI systems with capabilities such as planning, memory, tool-use, and multi-agent collaboration.
Define best practices for LLMOps, including prompt versioning, embedding store management, synthetic data generation, fine-tuning strategies, and continuous evaluation for safety, accuracy, and bias.
Drive applied research in large language models (LLMs) and multi-modal AI.
Translate ambiguous, high-impact business problems into scalable AI/ML solutions with measurable outcomes.
Build and guide end-to-end ML systems covering data sourcing, feature engineering, model training, deployment, monitoring, and iteration.
Champion advanced MLOps practices: automated pipelines, CI/CD for ML, model versioning, drift detection, and telemetry-based monitoring.
Ensure models meet standards of fairness, explainability, and responsible AI compliance.
Serve as a technical leader and mentor, guiding senior engineers and applied scientists to build depth and expertise.

Requirements

Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field.
Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field.
Option 3: 7 years' experience in an analytics or related field.
Deep expertise in Generative AI, LLMs, and/or Agentic AI systems (e.g., LLMOps, fine-tuning, RAG, multi-agent orchestration).
Strong applied science background with the ability to design, experiment, and deploy cutting-edge ML models in production.
Proven experience architecting large-scale ML/AI platforms with attention to performance, scalability, and maintainability.
Strong programming and ML tooling skills (Python; PyTorch/TensorFlow).
Familiarity with Agentic development platforms (Google ADK, LangGraph, CrewAI, AutoGen).
Track record of technical leadership, mentoring, and influencing architectural decisions across teams.

Benefits

Health benefits include medical, vision and dental coverage.
Financial benefits include 401(k), stock purchase and company-paid life insurance.
Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting.
Other benefits include short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement.
Live Better U education benefit program for full-time and part-time associates, covering tuition, books, and fees.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Generative AIlarge language modelsLLMOpsfine-tuningmulti-agent orchestrationmachine learningdata sourcingfeature engineeringmodel trainingmodel deployment

Soft Skills

technical leadershipmentoringinfluencing architectural decisionsproblem-solvingcommunication