About the position
The Headspace Machine Learning team plays a pivotal role in driving innovation, developing and launching key product features, and creating internal tools that power our mission. Our team is at the forefront of transforming mental healthcare through cutting-edge technology, leveraging the power of AI and ML to make a meaningful difference in people's lives. As a member of the ML Platform team, you will be at the heart of this transformation, building the foundational tools and systems that empower our ML engineers to deliver high-impact solutions efficiently and at scale. Your work will enable the team to develop, deploy, and maintain robust, resilient, and high-performing ML systems faster than ever before, creating a seamless pipeline from innovation to production. In your role as a Staff Machine Learning Engineer, you will take the lead in shaping the vision and architecture of our core ML Platform. You will drive key decisions that define the future of how ML systems are built, scaled, and deployed at Headspace. By combining your technical expertise with strategic foresight, you will spearhead initiatives that enhance productivity, ensure scalability, and support our mission to improve the health and happiness of the world.
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.
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.
Nice-to-haves
- 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 range of $140,400-$224,250 + equity + benefits.
- Comprehensive healthcare coverage.
- Monthly wellness stipend.
- Retirement savings match.
- Lifetime Headspace membership.
- Generous parental leave.
