AI Engineer

AI Engineer | Venture-Backed HealthTech Startup

Cambridge, MA

$200,000 - $220,000 + bonus + equity

4 days per week on-site

Join a well-funded, mission-driven start-up using AI to transform the way serious diseases are detected and monitored.

Having secured over $30M in early-stage funding and backed by leading investors, the company is entering an exciting growth phase as it prepares for its next major funding milestone. Their platform generates personalised health insights over time, with a live product already being used through a dedicated mobile application.

The Role

You'll be responsible for taking machine learning solutions from concept through to production, working across:

• ML model design, training and deployment
• Infrastructure, scalability and MLOps
• Productionising AI systems
• Monitoring, optimisation and performance improvement
• Collaborating closely with engineering, product and domain experts

This is an engineering-focused role suited to someone who enjoys shipping robust ML systems rather than pure research.

What We're Looking For

• Strong AI & machine learning and software engineering experience
• Track record of deploying ML models into production
• Experience with cloud infrastructure and MLOps
• Startup mindset and high ownership mentality
• Healthcare, biotech or life sciences experience is beneficial but not essential

Why Join?

• Opportunity to work on technology with meaningful real-world impact
• Backed by an experienced founding team with deep expertise in AI and life sciences
• Over $30M raised to date, providing the resources of a well-funded scale-up with the agility of a startup
• Join at an exciting stage of growth ahead of a major funding event
• High autonomy and influence within a small, highly technical team

Interview Process

1. Introductory conversation with the hiring manager

2. Three technical interview stages

3. Final onsite cultural and team-fit assessment

Ideal for AI engineers who enjoy building and scaling production-grade machine learning systems in a fast-paced, well-funded startup environment.