Senior Machine Learning Engineer

Summary

Join Headspace as a Senior Machine Learning Engineer and lead the development of cutting-edge language-based ML applications. You will drive impactful ML technology initiatives shaping mental healthcare delivery, provide technical leadership, and contribute to a diverse technology community. This role involves building scalable AI models, promoting high-quality code, and increasing company visibility in the AI community. You will mentor junior engineers and contribute to DEIB initiatives. The position offers a competitive salary, equity, and comprehensive benefits, including healthcare, wellness stipend, retirement savings match, and generous parental leave. The role is remote in the US or hybrid in San Francisco or Los Angeles.

Requirements

• MS 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
• 3+ years of experience with modern NLP tools and machine learning libraries (scikit-learn, PyTorch, TensorFlow, spaCy)
• 3+ 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
• 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

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
• Provide technical leadership and be a role model for those pursuing technical career path in AI/ML engineering
• Contribute to an engaged, inclusive technology community that values diversity and equity
• Promote the development of high-quality code through engagement in code review and constructive feedback
• Increase internal and external company visibility in the AI community through open source, talks/presentations, etc

Preferred Qualifications

• Professional experience with clinical and/or healthcare applications of machine learning
• Familiarity with current ML literature including optimization methods and agent-based models
• Fluency in OO design and programming in Python
• Experience with implementation of robust and highly scalable services
• Experience with AWS, including SageMaker, Lambda, S3, DynamoDB, IAM

Benefits

• Comprehensive healthcare coverage
• Monthly wellness stipend
• Retirement savings match
• Lifetime Headspace membership
• Generous parental leave