Note: The job is a remote job and is open to candidates in USA. TWELVE10 is a healthtech company developing a connected device that transforms real-world sensor data into personalized health insights. The Principal Head of Machine Learning Systems Engineer will own the company’s machine learning capability, setting technical direction while remaining hands-on in model development, data systems, production inference, and team building.
Responsibilities
- Build the technology. Shape the team. Stay hands-on
- You’ll set direction and build alongside an existing junior ML engineer, with scope to help shape an additional hire as the team develops with budget for additional headcount already allocated to you
- You’ll be writing code, training models and making the architectural decisions yourself
- Your decisions will shape the product. You’ll influence the models, datasets, infrastructure and evaluation methods that underpin the technology
- You’ll own problems through to the outcome. From investigating sensor data to deploying a reliable system, you’ll have room to follow the evidence and solve the underlying issue
- You’ll help build the capability around you. Mentor the existing mid level engineers, establish strong technical practices and influence how the team grows
- You’ll create well-curated datasets, from collection through annotation. Train, evaluate and improve models. Build the pipelines and backend services that move device data into production inference and customer-facing insights
- You’ll be trusted to work out where the problem sits and take responsibility for solving it
- You’ll also work closely with hardware, firmware, product and R&D colleagues to evaluate sensing approaches and turn experiments into practical improvements
Skills
- You have substantial experience delivering real-world ML and software systems, typically gained over seven or more years
- You've personally trained and improved models, built the data foundations behind them, and deployed systems that needed to keep working after launch
- Strong Python and hands-on model development using frameworks such as PyTorch
- Backend engineering, APIs and distributed data-processing systems
- Dataset construction, annotation, evaluation and failure analysis
- Cloud infrastructure and production ML inference
- Sound judgment when the objective is clear but the route to achieving it isn't
- The environment includes AWS, PostgreSQL and Terraform
- Computer vision, sensor data or connected-device experience would be particularly relevant
- Healthcare or medtech experience would also be valuable
- Go experience desirable
Benefits
- Fully remote across the US, with a preference for candidates in Boston or Austin and occasional in-person meetups.
- Meaningful equity
Company Overview