[Hiring] Machine Learning Engineer @Transcarent

Role Description

As an ML Engineer, you build production-grade multi-agentic systems that guide people through complex, high-stakes conversations. Our systems combine multi-step agent orchestration, retrieval, memory, and rigorous evaluation and safety layers.

We're looking for an ML Engineer to design, build, tune, and evaluate these agentic systems end to end:

• Context engineering and tool design
• Retrieval and memory
• Evaluation and safety guardrails

This is an applied-ML and LLM-systems role focused on agent behavior, model selection, retrieval of quality, and evaluation.

Though understanding of AI/ML is crucial for this role, we kindly request that you refrain from using GenAI while going through the interview process to allow fair evaluation of your skillset.

Qualifications

• Bachelor's or master's degree in data science, Machine Learning Engineering, or a related technical field, or equivalent practical experience.
• 3+ years of professional Data Science/ML engineering experience.
• Strong applied experience building LLM-powered agents in production: shipped, multi-turn agentic systems, not just prompt experiments.
• Hands-on expertise with agent orchestration frameworks: stateful graphs, tool use, and conditional routing.
• Deep understanding of context engineering and tool/function-calling design for reliable agent behavior.
• Practical RAG experience: embeddings, vector search, and retrieval-quality tuning.
• Fluency with LLM model selection and tuning across providers, including reasoning models and their trade-offs.
• Experience designing LLM evaluation: offline eval, graders, test sets, metrics, and quality gates.
• Comfort with agent observability and tracing to diagnose and improve behavior.
• Strong Python skills as applied to ML/agent work.

Requirements

• Experience with agent memory systems.
• Experience with LangChain suite.
• Experience building safety guardrails for high-stakes domains (clinical, financial, legal).
• Experience optimizing LLM latency, cost, and reliability at scale.
• Experience with building and working with MCPs and loop engineering.
• Prompt optimization techniques such as GEPA.

Benefits

• Competitive medical, dental, and vision coverage
• Competitive 401(k) Plan with a generous company match
• Flexible Time Off/Paid Time Off, 13 paid holidays
• Protection Plans including Life Insurance, Disability Insurance, and Supplemental Insurance
• Mental Health and Wellness benefits