Senior Software Engineer, MLOps

Summary

Join Headspace's AI Engineering team as a Senior Software Engineer, MLOps and play a pivotal role in designing and delivering cutting-edge MLOps platforms and services. You will lead initiatives, design ML architecture in AWS using Terraform, implement CI/CD pipelines, build productivity-enhancing tools, and drive self-service automation. The role requires strong leadership, technical expertise in AWS, TypeScript, and Terraform, and experience in large-scale software engineering and MLOps. You will mentor junior engineers and collaborate with cross-functional teams. Headspace offers a competitive salary, comprehensive healthcare, wellness stipend, retirement savings match, and generous parental leave, among other benefits.

Requirements

• Bachelor of Science degree or higher in Computer Science, Engineering, or a related field
• 3+ years of experience with AWS and MLOps practices
• 2+ years of experience with TypeScript and Terraform, showcasing proficiency in modern development and infrastructure tools
• 4+ years of software engineering experience, including at least 2 years in large businesses or enterprise environments
• 3+ years of experience deploying and configuring software configuration management, build and deployment processes, CI/CD pipelines, and other application lifecycle management tools on AWS
• Proven ability to lead cross-functional initiatives and deliver solutions end-to-end, from inception to production
• Strong experience designing and implementing robust, highly scalable, and reliable services in production environments
• Demonstrated problem-solving and communication skills, with the ability to influence decisions and collaborate effectively across internal teams

Responsibilities

• Lead and drive initiatives end-to-end, spanning multiple layers of architecture and business domains
• Provide strategic guidance to ensure alignment with organizational goals
• Design, implement, and optimize ML-related architecture in AWS using Infrastructure as Code (IaC) tools like Terraform, ensuring scalability, reliability, and efficiency
• Establish and maintain robust CI/CD pipelines to automate testing, deployment, and monitoring of ML models and services
• Ensure best practices for production-level ML systems
• Build and improve productivity-enhancing tools and frameworks for AI and ML practitioners, enabling efficient experimentation and deployment
• Drive the development and adoption of advanced self-service capabilities and automation frameworks, reducing operational overhead and improving scalability
• Develop and provision automated alerts, detailed metrics, and advanced monitoring solutions for critical ML pipelines, ensuring operational excellence and rapid issue resolution
• Mentor junior engineers and collaborate with cross-functional teams to deliver scalable and impactful ML infrastructure solutions

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