Software Engineer, Machine Learning

About the Staff Software Engineer, Machine Learning at Headspace:
Machine Learning 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 Machine Learning. These applications include building conversational AI systems, healthcare assistance tools, and recommendation and personalization systems. In this team, you’ll be tasked with owning and delivering cutting edge language-based ML applications that will power the core features of Headspace.

You’ll have the opportunity to lead the vision, alignment, development, deployment, and evangelization of these solutions, helping to bring Headspace to the forefront of AI and to realize its mission to improve health and happiness of the world.

Location:

This is a hybrid role located in our San Francisco office, working 3 days per week from the office.

• Technical Leadership: 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.
• Shape ML Platform Architecture: Drive the design, development, and evolution of our internal ML platform, taking it from high-level vision to robust implementation.
• Collaborative Problem-Solving: Partner with cross-functional teams to align technical decisions with organizational goals, ensuring cohesive and impactful solutions.
• Champion Code Quality: Advocate for and contribute to high-quality engineering standards through rigorous code reviews and constructive, actionable feedback.

• 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

• 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 including optimization methods and agent-based models
• Experience with implementation of robust and highly scalable services
• Experience with AWS, including Sage Maker, Lambda, S3, Dynamo
  
  DB, IAM

The anticipated new hire base salary range for this full-time position is $140,400-$224,250 + 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.

Your recruiter will provide more details on the specific salary range for your location during the hiring process.

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. Additional details about our Total Rewards package will be provided during the recruitment process.

Headspace exists to provide every person access to lifelong mental health support. We…