Machine Learning Engineer

About the Staff Machine Learning Engineer at Headspace

The AI & Machine Learning group at Headspace is a dynamic and innovative team whose mission is to improve the experiences of our members and clinicians through mindful application of AI. Our group builds conversational AI systems, including Ebb, as well as search, recommendation, and 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 that enables the personalization of the Headspace experience, including content recommendation, personalized nudges, notifications, and a tailored conversational AI experience with Ebb.

You’ll 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.

• 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 shape the delivery 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 them from high‑level vision to robust implementation, enabling production‑ready AI capabilities.
• Collaborative Problem‑Solving: Partner with software engineers, ML engineers, MLOps engineers, and Product & Clinical leads to build high‑quality features that improve members’ lives.

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, Tensor Flow, 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 a 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 Sage Maker, Lambda, S3, DynamoDB, IAM

We are currently hiring this role remotely. Candidates must permanently reside in the US full‑time.

The anticipated new hire base salary range for this full‑time position is $140,400‑$200,000 + equity + benefits.

Our salary ranges are based on the job, level, and location, and reflect the lowest to highest geographic markets where we are hiring for this role within the United States. Within this range, individual compensation is determined by a candidate’s location as well as a range of factors including but not limited to unique relevant experience, job‑related skills, and education or training.

At Headspace, base salary is but one component of our Total Rewards package. We’re proud of our robust package inclusive of: base salary, stock awards, comprehensive healthcare coverage, monthly wellness stipend, retirement savings match, lifetime Headspace membership, generous parental leave, and more.

Headspace is committed to bringing together people from different backgrounds and perspectives,…