Staff Software Engineer, Machine Learning

Summary

Join Headspace's Machine Learning team as a Staff Software Engineer and play a pivotal role in building and scaling our core ML platform. You will shape the architecture, engineer scalable systems, automate model lifecycle management, and collaborate with cross-functional teams. This leadership role requires expertise in DevOps, infrastructure, and MLOps, along with a proven track record in delivering robust, scalable services. You will mentor other engineers and champion code quality. Headspace offers a competitive total rewards package including base salary, stock awards, comprehensive healthcare, wellness stipend, retirement savings match, and generous parental leave.

Requirements

• Bachelor's or Master’s degree in Computer Science, Engineering, or a related field, or equivalent hands-on experience
• Exceptional problem-solving abilities with the communication skills to influence decisions across teams and drive alignment
• Proven track record in designing and delivering robust, scalable, and highly reliable services in production environments
• A deep passion for technical excellence, continuous learning, and innovation
• 5+ years of DevOps experience, with hands-on expertise in AWS services, including SageMaker, Lambda, S3, DynamoDB, and IAM
• Proficiency with Infrastructure as Code (IaC) tools such as Terraform and development languages like TypeScript
• Strong background in implementing unit, integration, and end-to-end testing, along with setting up and managing CI/CD workflows
• 2+ years of experience in MLOps, including developing, standardizing, and automating machine learning workflows
• Hands-on experience managing machine learning systems in production, ensuring reliability and scalability
• Proficiency in object-oriented programming and design, particularly in Python
• Experience driving ML initiatives from inception to deployment, with a focus on measurable business impact

Responsibilities

• Shape ML Platform Architecture: Drive the design, development, and evolution of our internal ML platform, taking it from high-level vision to robust implementation
• Engineer Scalable Systems: Build and support complex, scalable, and multi-component data and ML systems that integrate seamlessly across the organization
• Automated Model Lifecycle Management: Develop frameworks for continuous retraining of production models, enabling online learning and adaptive system improvements
• Collaborative Problem-Solving: Partner with cross-functional teams to align technical decisions with organizational goals, ensuring cohesive and impactful solutions
• Technical Leadership: Serve as a go-to expert and mentor, exemplifying excellence in AI/ML engineering and inspiring others to pursue technical career growth
• Champion Code Quality: Advocate for and contribute to high-quality engineering standards through rigorous code reviews and constructive, actionable feedback

Preferred Qualifications

• Strong knowledge of AI/ML technologies, including supervised and unsupervised learning, deep learning, and reinforcement learning
• Hands-on experience building applications leveraging Large Language Models (LLMs)
• A genuine interest in applying technical skills to solve challenges in mental health, healthcare, or related fields

Benefits

• Base salary
• Stock awards
• Comprehensive healthcare coverage
• Monthly wellness stipend
• Retirement savings match
• Lifetime Headspace membership
• Unlimited, free mental health coaching
• Generous parental leave
• Paid performance incentives