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The Applied AI Team develops AI and ML solutions that power personalized clinical care at scale. Our work includes end-to-end AI treatment management systems that handle complete care pathways - from initial assessment through intervention selection and progress monitoring across various therapeutic domains. We are also building Phoenix, an AI Care Specialist that engages in ongoing dialogue with patients and provides clinical guidance throughout their recovery journey.
This work spans the full AI stack: prompt engineering, RAG implementations, model fine-tuning, and agentic workflows. We leverage both generative AI and classical machine learning depending on what the problem requires. All of our projects contribute to delivering digital care that reaches new levels of clinical quality and accessibility.
What you'll be doing:
- Ship production ML systems that power clinical care - Write code daily, design architectures, and make technical decisions across our AI treatment management platform and Phoenix
- Lead a lean team of 2-4 ML engineers - Set technical direction, unblock your team, review code, and ensure you’re building the right things the right way
- Drive 0-1 ML initiatives - Identify high-leverage opportunities across the AI stack (prompt engineering, RAG, fine-tuning, agentic workflows), prototype fast, and push to production
- Raise the technical bar - Establish best practices for AI development, mentor engineers, and scale our ML engineering culture
- Partner with Product and Clinical teams - Shape what gets built and ensure our AI solutions actually improve patient outcomes
- Proven ability to ship production ML systems - You’ve built and deployed models that real users depend on, and can show the impact
- Experience leading technical teams - You’ve led engineers before (whether as a tech lead, team lead, or manager), with an emphasis on pragmatic execution and delivery
- Hands-on experience with end-to-end ML pipelines - From data preparation through model deployment, monitoring, and iteration in production
- Strong engineering fundamentals - You write production-quality code in Python, work effectively with data (SQL), and can debug complex ML systems
- GenAI experience - You’ve worked with LLMs in production environments (RAG, tool use, orchestration, complex workflows, or fine-tuning)
- Bias toward action - You ship iteratively, make decisions with incomplete information, and prioritize effectively to deliver value quickly
- Clear communication - You can explain technical tradeoffs to clinicians, product managers, and engineers
- Experience with healthcare AI or clinical applications - you understand the unique challenges of building ML for high-stakes domains
- Track record of designing and running experiments to measure real-world impact (A/B tests, online evaluation, etc.)
- A stimulating, fast-paced environment with lots of room for creativity;
- A bright future at a promising high-tech startup company;
- Career development and growth, with a competitive salary;
- The opportunity to work with a talented team and to add real value to an innovative solution with the potential to change the future of healthcare;
- A flexible environment where you can control your hours (remotely) with unlimited vacation;
- Access to our health and well-being program (digital therapist sessions);
- Remote or Hybrid work policy;
- To get to know more about our Tech Stack, check here
- 30-minute call with the recruiter
- 30-minute call with an initial screener
- 1 take-home assignment (to be delivered within 1 week)
- 1h general skills and working principles interview
- 1h leadership and people management interview
- 1h mindset and cultural fit interview
- Health, dental and vision insurance
- Meal allowance
- Equity shares
- Remote work allowance
- Flexible working hours
- Work from home
- Discretionary vacation
- Snacks and beverages
- English class
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.
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