About the Staff Machine Learning Engineer at Headspace:
The AI & Machine Learning group at Headspace is a dynamic and innovative group whose mission is to improve the experiences of our members and clinicians through the mindful application of AI. Our group builds conversational AI systems including Ebb, as well as search, recommendation & personalization systems that power the Headspace experience. The Staff ML Engineer for Personalization will be part of the team developing and delivering the holistic system to enable the personalization of the Headspace experience, including content recommendation, personalized nudges & notifications, and a tailored conversational AI experience with Ebb. You’ll have the opportunity to lead the vision, alignment, development, deployment, and adoption of these solutions, helping to realize Headspace’s mission to improve the health and happiness of the world.
What you will do:
- Technical Leadership: Lead the development of recommender systems for Headspace meditation & mindfulness content as well as other backend services that enable a personalized member experience including search, a user knowledge graph, and conversational AI memory. This will involve developing and deploying complex, scalable AI models and applications. 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.
- Shape Personalization Architecture: Contribute to the design, development, and evolution of our AI systems, taking it from high-level vision to robust implementation, enabling production-ready AI capabilities.
- Collaborative Problem-Solving: Partner with our team of software engineers, ML engineers, and MLOps engineers, and our Product & Clinical leads to build high quality features that improve members’ lives.
What you will bring:
Required Skills:
- Bachelor of Science degree or higher in Computer Science, Statistics, Mathematics or a related field OR equivalent experience
- 5+ years of ML engineering experience in an academic or professional setting, programming in Python
- 5+ 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.
- 3+ 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
Preferred Skills:
- Master’s degree in relevant field or equivalent experience
- Professional experience with clinical and/or healthcare applications of machine learning
- Familiarity with current ML literature
- Experience with implementation of robust and highly scalable services
- Experience with AWS, including SageMaker, Lambda, S3, DynamoDB, IAM