Senior Machine Learning Engineer

Syndesus, Inc.; Austin (TX); On-site; USD 100,000 - 140,000; Full time

Benefits offered by this job

100% employer-paid health, vision, and dental insurance

Retirement plans (401(k))

Disability insurance

Employee assistance programs

Job summary

Syndesus, Inc. is seeking a hands-on ML/LLM Engineer to revolutionize healthcare through AI applications. The ideal candidate will own and optimize ML and LLM pipelines, collaborating with product and engineering teams to build impactful applications in healthcare.

Qualifications include 3–6 years of applied machine learning experience, strong Python skills, and familiarity with ML frameworks. The position offers competitive compensation, full health benefits, and strong growth potential.

Qualifications

• 3–6 years of experience in applied machine learning, with at least 1–2 years working with large language models.
• Strong Python skills and familiarity with ML/LLM frameworks.

Responsibilities

• Own and optimize ML and LLM-based pipelines.
• Collaborate with teams to build AI applications in healthcare.
• Monitor and improve model quality and latency.

Skills

Python

Machine Learning frameworks

Prompt tuning

Experimentation

Responsible AI practices

Healthcare data familiarity

Tools

PyTorch

Transformers

LangChain

LlamaIndex

Job description

Our client is revolutionizing healthcare by streamlining knowledge workflows with AI. They reduce administrative burdens and elevate outcomes, empowering professionals to focus on what truly matters - improving lives. They’re growing fast and looking for bold, driven teammates to join them.

About the Role

Our client is seeking a hands‑on ML/LLM Engineer who’s excited to ship real‑world applications - not just benchmarks. You’ll help build and optimize AI‑native systems that blend structured and unstructured data to power decisions in high‑stakes domains. This is a mid‑to‑senior level role for someone ready to go deep on applied ML problems - from retrieval to routing to generation - and ship solutions that deliver measurable impact.

Responsibilities

• Own and optimize pipelines that combine classical machine learning and LLM‑based systems (RAG, scoring, summarization, etc.).
• Fine‑tune and evaluate LLMs using both open‑source and proprietary data.
• Collaborate with product and engineering teams to build real‑world applications in healthcare and biopharma.
• Implement retrieval strategies, prompt chaining, and inference orchestration for production use cases.
• Monitor and improve model quality, latency, explainability, and safety.
• Stay ahead of the curve in LLM evaluation, tuning, and agent‑based architecture.

Qualifications

• 3–6 years of experience in applied machine learning, with at least 1–2 years working with large language models.

Requirements

• Strong Python skills and familiarity with ML/LLM frameworks such as PyTorch, Transformers, LangChain, LlamaIndex, etc.
• Experience with embeddings, vector search, retrieval pipelines, and prompt tuning for large language models.
• Bias for experimentation, clarity, and rapid deployment of solutions into production.
• Understanding of responsible AI practices, model evaluation, and observability.
• Experience with healthcare data or other compliance‑sensitive, regulated environments.

Compensation and Benefits

• Opportunity to make a real impact on the future of healthcare.
• Autonomy, ownership, and growth potential.
• Competitive compensation package and benefits.
• 100% employer‑paid health, vision, and dental insurance.
• Retirement plans (401(k)), disability insurance, and employee assistance programs.

This position is open only to individuals who are legally authorized to work in the United States on a permanent basis. At this time, the company is unable to sponsor or take over sponsorship of employment visas (including H-1B, OPT, CPT, or other non‑immigrant statuses).