Founding Forecasting & Ml Engineer

Air Apps; Almada; Presencial; EUR 60 000 - 85 000; Tempo integral

Resumo da oferta

Sword Health is hiring an ML Engineer to own end-to-end ML projects in a healthcare AI platform. You will design multi-step workflows with tooling and orchestration, build robust eval pipelines, and push models from research to production in clinical settings.

You will work across data prep, model adaptation, serving and monitoring, partnering with Product, Clinical, and Engineering to translate medical needs into technical decisions. Strong communication with clinical stakeholders is essential.

Qualificações

• Experience shipping ML systems to production
• Hands-on LLM work in production: prompting, retrieval, tool calling
• Rigorous approach to evaluation with eval datasets/frameworks
• Strong ML fundamentals and tradeoff reasoning
• Comfort with ambiguity turning problems into production
• Production-quality code and distributed systems
• Clear communication with technical and clinical stakeholders

Responsabilidades

• Own ML projects end-to-end from exploration to production deployment
• Design multi-step workflows with tool use and orchestration for clinical settings
• Build eval sets, offline/online harnesses, and regression tests
• Improve model quality with prompts, retrieval, distillation or fine-tuning
• Work across data prep, model adaptation, serving and monitoring
• Translate clinical requirements into technical decisions and surface tradeoffs
• Mentor engineers and share learnings across the team

Conhecimentos

ML systems in production

LLM workflows

Evaluation frameworks

ML fundamentals

Ambiguity tolerance

Distributed systems

Clear technical communication

Descrição da oferta de emprego

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.

Since 2020, Sword has expanded across physical therapy, women's health, cardiometabolic, and mental health, and is now moving beyond the session to a fully AI-native, 24/7 care program that brings physical activity, therapeutic exercise, psychotherapy, nutrition, and behavior change into one connected experience. More than 700,000 members across three continents have completed over 10 million AI sessions, helping 1,000+ enterprise clients avoid more than $1 billion in unnecessary healthcare costs.

Backed by 42 clinical studies, 44+ patents, and more than $500 million raised from leading investors including Khosla Ventures, General Catalyst, and Founders Fund, Sword is defining a new standard for healthcare.

AI Proficiency at Sword

AI fluency is a core expectation at Sword. Every candidate is assessed against three-level framework — be ready to share real examples of how AI is already part of how you work. Explorer (Level

• Uses AI daily to boost personal productivity Builder (Level
• Creates workflows and tools that elevate the whole team Integrator (Level
• Embeds AI into products and processes at scale Every hire must demonstrate at least Level 1. The expected level will vary depending on the seniority of the role.

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 LLMsystems: 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 AIstack: 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 getbetter: 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 workin 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 engineeringskills: 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, orotherhigh‑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. Job titles may span more than one career level, so actual pay depends on skills, qualifications, experience, location, and market demand, among other factors. The range reflects base salary plus any variable, bonus, or sales incentives, and our estimate of the value of private company stock options where applicable. It's subject to change, and future stock value isn't guaranteed. Sword also offers additional benefits beyond total compensation.

Total Compensation Range

€60.000—€85.000 EUR Country-specific benefits may vary and will be detailed separately. Sword Health complies with applicable Federal and State civil rights laws and does not discriminate on the basis of Age, Ancestry, Color, Citizenship, Gender, Gender expression, Gender identity, Gender information, Marital status, Medical condition, National origin, Physical or mental disability, Pregnancy, Race, Religion, Caste, Sexual orientation, and Veteran status.

Founding Forecasting & Ml Engineer Caparica, Portuguese Republic, PT