Senior ML Engineer
Own ML projects end-to-end and build reliable LLM systems in a fully remote role at Sword Health.
Posted by employer 1 month ago
First seen on Joblaze 1 month ago
Last verified on the company career page 5 days ago
Skills & Technologies
What you'll build
- Own ML projects end-to-end
- Build agentic LLM systems
- Treat evaluation as core engineering work
- Improve model quality
- Work across the full AI stack
Must have
- Experience shipping ML systems to production
- Hands-on LLM work in production
- A rigorous approach to evaluation
- Strong ML fundamentals
- Solid engineering skills
- Clear communication with stakeholders
Nice to have
- Experience with fine-tuning or preference optimization
- Healthcare AI experience
- Built agent frameworks or evaluation tooling
- Open source contributions
- Technical writing
AI in the day-to-day
AI fluency is a core expectation; candidates must demonstrate how AI is part of their work.
Not disclosed in this posting: years of experience, visa sponsorship.
Joblaze summary
In this role, the Senior ML Engineer at Sword Health is responsible for managing machine learning projects from initial exploration to production deployment, ensuring systems are reliable for clinical use. The position requires expertise in building large language model systems, evaluation frameworks, and a strong grasp of machine learning fundamentals. This role is suited for experienced engineers who have a proven track record in deploying ML systems and can navigate ambiguity in problem-solving. Sword Health emphasizes collaboration across product, clinical, and engineering teams to translate healthcare needs into technical solutions.
Joblaze insights
- Listed about a month ago — first seen on Joblaze September 11, 2026. Last confirmed on Sword Health's careers page October 23, 2026.
- Starts above 2% of 416 comparable senior ai/ml roles we track (median $182,000 across 113 companies).
Quick facts
- Is the Senior ML Engineer role remote?
- Yes — Sword Health lists this as a fully remote position.
- What's the salary range?
- Sword Health lists €60,000–€85,000 for this role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AI/ML, Evaluation Frameworks, LLM, Machine Learning, distributed systems.
- What seniority level is this role?
- Sword Health targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this Senior ML Engineer role at Sword Health.
From the original posting
At Sword, we’re building AI to heal billions and unlock humanity’s full potential. In doing so, we’re pioneering AI Care, a fundamentally new approach to healthcare built for medical reasoning, safety, and real-time treatment, not generic technology applied after the fact. As both a clinical-centric frontier AI lab and an applied AI platform, Sword is reimagining how care is delivered at scale, removing traditional barriers like appointments, waiting rooms, and stigma so more people can access the care they need—and ultimately get back to lives lived in full.
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Explorer (Level 1) — Uses AI daily to boost personal productivity
What you’ll be doing
- Own ML projects end-to-end: take problems from exploration through production deployment and keep iterating once real users are on them;
- Build agentic LLM systems: design multi-step workflows with tool use, retrieval, and orchestration, and make them reliable enough for clinical settings;
- Treat evaluation as core engineering work: build eval sets, offline and online harnesses, LLM-as-judge pipelines with human review, and regression tests that catch quality drops before they reach users;
- Improve model quality with whatever fits the problem: prompting, retrieval, distillation, or fine-tuning, chosen on evidence rather than habit;
- Work across the full AI stack: data prep, model adaptation, serving, monitoring, and the feedback loops that keep systems improving in production;
- Partner with Product, Clinical, and Engineering: translate clinical requirements into technical decisions and surface tradeoffs early;
- Help the team get better: review code, share what you learn, and mentor engineers earlier in their careers.
What you need to have
- Experience shipping ML systems to production that people actually depend on;
- Hands-on LLM work in production: prompting, retrieval, tool calling, and agent-style workflows;
- A rigorous approach to evaluation: you've built eval datasets and frameworks, and you can tell a real improvement from noise;
- Strong ML fundamentals: you know which approach fits which problem and can reason clearly about tradeoffs;
- Comfort with ambiguity: you've taken loosely defined problems and turned them into something running in production;
- Solid engineering skills: production-quality code, familiarity with distributed systems, and the patience to debug messy ML pipelines;
- Clear communication with both technical and clinical stakeholders.
Bonus points
- Experience with fine-tuning or preference optimization (RLHF, DPO, or similar);
- Healthcare AI, or other high-stakes domains where errors carry real cost;
- Built agent frameworks or evaluation tooling from scratch;
- Open source contributions, technical writing, or other knowledge sharing.
*The range below reflects base, variable, and equity for this role.
Standard company text repeated across Sword Health's postings is omitted here.