Principal Machine Learning Engineer

About the Principal Machine Learning Engineer at Headspace:

Machine Learning at Headspace is a dynamic group that improves our members and clinicians through thoughtful application of machine learning, developing conversational AI, healthcare assistance tools, recommendation systems, and personalization solutions. The Principal Engineer will own and deliver cutting‑edge language‑based ML applications that power Headspace’s core features.

• Technical Leadership
  :
  Lead the development of complex, scalable AI models and applications from inception to production. Drive impactful ML technology initiatives that shape the delivery of and access to mental healthcare. Serve as a go‑to expert and mentor, exemplifying excellence in AI/ML engineering.
• 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.

Required Skills:

• Master’s of Science degree or higher in Computer Science, Statistics, Mathematics, or 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 fundamental technologies such as vector search, embedding models, recommender systems, supervised and unsupervised learning, deep learning, reinforcement learning, LLM orchestration, and RAG systems.
• 5+ years of experience with modern NLP tools and libraries (scikit‑learn, PyTorch, Tensor Flow, spaCy).
• Experience with unit, integration, and end‑to‑end testing, and version control.
• Strong problem‑solving, communication, and influence across internal organizations.
• Mentorship of junior engineers and contribution to DEIB initiatives.

Preferred

Skills:

• PhD in a relevant field or equivalent experience.
• Professional experience with clinical and/or healthcare applications of machine learning.
• Familiarity with current ML literature, optimization methods, and agent‑based models.
• Experience implementing robust and highly scalable services.
• Experience with AWS services (Sage Maker, Lambda, S3, Dynamo
  
  DB, IAM).

Location:

This role is open to candidates across the United States, with preferred locations in San Francisco, CA (hybrid), New York City, NY (remote), and Seattle, WA (remote). Candidates must permanently reside in the U.S. full‑time.

The anticipated new hire base salary range for this full‑time position is $162,000–$225,000, plus equity and benefits. For candidates based in San Francisco, New York City, or Seattle, a separate salary range of $207,000–$258,700 applies.

• Competitive base salary, stock awards, and a comprehensive benefits package.
• Healthcare coverage, monthly wellness stipend, retirement savings match, lifetime Headspace membership, and generous parental leave.

As an equal opportunity employer, we prohibit unlawful discrimination against a job applicant on the basis of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, family or parental status, disability, age, veteran status, or any other status protected by the laws or regulations where we operate. We comply with EEOC guidelines and are committed to fostering a diverse, equitable, inclusive, and belonging workplace.

Applicants with disabilities may be entitled to reasonable accommodation under the Americans with Disabilities Act and applicable state or local laws. Please inform our Talent team by filling out the form to request assistance with any application or interview process.