Note: The job is a remote job and is open to candidates in USA. Headspace is a company dedicated to providing mental health support through innovative technology. The Principal Machine Learning Engineer will lead the development of advanced AI applications to enhance member and clinician experiences, focusing on building language-based ML solutions.
Responsibilities
- Lead the development of complex, scalable AI models and applications from inception to production
- Drive impactful ML technology initiatives that will shape the delivery of and access to mental healthcare
- Serve as a go-to expert and mentor, exemplifying excellence in AI/ML engineering and inspiring others to pursue technical career growth
- Drive the design, development, and evolution of our internal ML platform, taking it from high-level vision to robust implementation
- Partner with cross-functional teams to align technical decisions with organizational goals, ensuring cohesive and impactful solutions
Skills
- Master's of Science degree or higher in Computer Science, Statistics, Mathematics or a related field OR equivalent experience
- 8+ years of ML engineering experience in an academic or professional setting, programming in Python
- 8+ years of experience with any of the following fundamental technologies: vector search, embedding models, recommender systems, supervised, unsupervised machine learning, deep learning, reinforcement learning, LLM orchestration, RAG systems
- 5+ years of experience with modern NLP tools and machine learning libraries (scikit-learn, PyTorch, TensorFlow, spaCy)
- Experience with unit, integration, and end-to-end testing, version control
- Strong problem solving and communication skills and ability to influence across internal organizations
- Mentorship of junior engineers and contribution to DEIB initiatives
- PhD in relevant field or equivalent experience
- Professional experience with clinical and/or healthcare applications of machine learning
- Familiarity with current ML literature including optimization methods and agent-based models
- Experience with implementation of robust and highly scalable services
- Experience with AWS, including SageMaker, Lambda, S3, DynamoDB, IAM
Benefits
- Equity
- Benefits
- Base salary, stock awards, comprehensive healthcare coverage, monthly wellness stipend, retirement savings match, lifetime Headspace membership, generous parental leave, and more
- Hybrid model, with 3 days per week in office to support in-person collaboration (for candidates in the greater San Francisco Bay Area)
Company Overview