Staff Software Engineer, MLOps

Summary

Join Headspace's AI Engineering team as a Staff Software Engineer, MLOps and play a pivotal role in designing and delivering cutting-edge MLOps platforms and services. You will empower data scientists and other AI practitioners by building scalable and reliable ML systems on AWS. Responsibilities include contributing to ML architecture, implementing CI/CD pipelines, developing self-service tools, and ensuring operational excellence. The ideal candidate possesses a Bachelor's degree in a related field, 4+ years of AWS experience with MLOps practices, proficiency in TypeScript and Terraform, and a proven track record of delivering impactful technical initiatives. Headspace offers a competitive salary, comprehensive healthcare, wellness stipend, retirement savings match, and other benefits.

Requirements

• Bachelor of Science degree or higher in Computer Science, Engineering, or a related technical field
• 4+ years of experience with AWS, particularly in ideating and applying MLOps practices to streamline and optimize ML workflows
• Proficiency in TypeScript and Terraform with at least 3+ years of hands-on experience, demonstrating practical use in modern development and infrastructure management
• 4+ years of software engineering experience, including working on scalable, production-grade systems, preferably in enterprise or large business environments
• 3+ years of experience implementing and maintaining software configuration management, CI/CD pipelines, build and deployment processes, and other lifecycle tools on AWS
• Demonstrated success in executing technical initiatives end-to-end, focusing on design, implementation, and deployment
• Developing junior talent and implementing best practices
• Proven expertise in building robust, scalable, and reliable services, with a focus on operational excellence in production environments
• Strong problem-solving skills and technical communication, with the ability to collaborate effectively with cross-functional teams to deliver impactful solutions

Responsibilities

• Take responsibility for delivering impactful initiatives in your specific area of expertise
• Work across layers of architecture and collaborate with cross-functional teams to ensure alignment with business objectives and technical excellence
• Contribute to the design and optimization of ML-related architecture in AWS, leveraging Infrastructure as Code (IaC) tools like Terraform
• Focus on implementation and improvement to ensure scalability and reliability
• Implement and maintain CI/CD pipelines for ML systems, focusing on automating testing and deployment processes
• Actively monitor production ML systems to ensure they adhere to best practices
• Develop and refine tools that improve productivity for ML and AI practitioners, enabling more efficient experimentation and deployment cycles
• Work on creating and maintaining self-service and automation tools to minimize operational overhead
• Aim to simplify processes for broader team usage
• Design and implement alerting, detailed metrics, and monitoring solutions for key ML pipelines
• Focus on maintaining operational excellence and enabling quick resolution of issues
• Work closely with peers and contribute to team success by sharing knowledge and insights
• Assist in mentoring newer engineers to elevate team capabilities and maintain high standards of technical delivery

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 are also included for those in eligible roles