Senior Consultant, AI​/ML Engineer

Hollstadt Consulting is a management and technology consulting firm dedicated to placing professionals at engagements where they will excel. When you work with us, you'll work with a refreshingly real company led and staffed by seasoned experts who are also down-to-earth, good people. We're committed to treating you with respect and helping you achieve your career aspirations.

Since 1990, Hollstadt has been a trusted partner to more than 150 domestic and global companies and has successfully completed over 3,000 projects. Our continued growth has created challenging and rewarding opportunities for accomplished IT and Business Consultants. Hollstadt Consulting is an equal opportunity employer including disability/veteran.

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Role:
Senior Consultant, AI/ML Engineer

Location:

Remote

Duration: 9/1/2026-2/1/2027

Rate: $79-$88/hour W2

The AI CoE builds AI products and the shared platform that powers them. We're looking for a Senior ML / AI Engineer who is equally comfortable building models and building the platform around them: someone

who can train and evaluate an ML model, ship a production LLM/GenAI application, and extend shared AI infrastructure and tooling that the wider team depends on.

This is a senior builder role at the intersection of applied data science, GenAI application engineering, and AI platform engineering. Our work spans predictive modeling, LLM-based systems, and the platform underneath them; you'll take problems from data and prototype through to governed, monitored production services, and set the technical patterns other engineers build on. Projects vary over time — we value engineers who can move across the stack rather than stay in one lane

• Build ML models — frame problems, engineer features, train and evaluate models (ranking, scoring, survival/time-to-event, classification, forecasting), and reason rigorously about metrics (AUC, C-index, calibration), validation strategy, subgroup performance, and failure modes.
• Integrate models into decision systems — combine model output with business/domain rules and LLM reasoning to produce explainable, trustworthy recommendations.
• Ship GenAI applications — design and deploy LLM-powered features: RAG pipelines, agents, structured extraction, summarization, decision-reasoning trails, and evaluation harnesses using Claude/Bedrock and other models.
• Engineer the AI platform — extend the shared AI gateway (unified multi-model access, API keys, per-team budgets, failover, observability) and reusable libraries/SDKs that other teams build on.
• Own the RAG/data layer — embeddings, vector stores, retrieval quality, chunking, and grounding strategies; measure and improve retrieval and answer quality.
• Build evaluation & quality tooling — offline/online eval, LLM-as-judge, regression suites, statistical validation, and guardrails so model and prompt changes ship safely.
• Productionize — wrap models and pipelines as tested, observable services (Python, containers, AWS Lambda/Sage Maker/EKS), with monitoring for quality, cost, latency, and drift.
• Lead technically — set patterns and standards, review designs and code, mentor engineers, and partner with data scientists, MLOps, clinical/domain experts, and product owners to move prototypes to production.

• 5+ years building and shipping ML / AI systems in production (not just…