Senior ML Software Engineer

About the role

We are seeking an experienced Senior ML Software Engineer to join our Data Science Enablement team. This role involves driving new feature development, maintaining operational excellence, and contributing to the evolution of our shared ML platform.

Responsibilities

• Design, implement, and deploy new features and enhancements to ML products, collaborating with Product and ML Research teams to refine requirements.
• Technical ownership and stewardship of existing and new production ML products in your area, ensuring alignment with business goals and engineering best practices.
• Contribute to the evolution of the shared ML platform alongside other engineers to drive best practices and shared tooling across all products.
• Maintain and improve automated CI/CD pipelines, testing frameworks, and monitoring/logging, ensuring high operational standards.
• Conduct comprehensive code reviews to enforce coding standards, improve code quality, and share knowledge.
• Identify and implement opportunities for process, tooling, and system improvements, proactively addressing technical debt and scaling challenges.
• Oversee pre-release testing, coordinate releases, and ensure smooth enablement of new features.
• Provide technical guidance and support to other engineers and data scientists to solve complex technical challenges.
• Mentor and coach other engineers, supporting their professional growth and fostering a culture of collaboration, continuous improvement, and knowledge sharing.
• Proactively identify and resolve blockers, navigate processes, and independently seek out information and connect with relevant teams to drive solutions in the face of ambiguity.
• Operate with a strong sense of urgency, consistently prioritizing and executing tasks to meet timelines and deliver results.

Requirements

• 5+ years as an ML-focused software engineer, ML Engineer, MLOps Engineer, or similar, with hands-on production experience.
• Proven expertise with ML model deployment, API design, and integration into production environments.
• Strong Python programming and relevant ML/data libraries.
• Experience with containerization, orchestration, and AWS cloud services.
• Building and operating CI/CD pipelines, monitoring, troubleshooting, and optimizing production ML systems.
• Pre-release testing and release management.
• Demonstrated ability to work independently, navigate ambiguity, and deliver results.
• Excellent communication skills and ability to collaborate both within engineering organizations and on cross-functional teams.

Qualifications

• Experience with OpenAPI, FastAPI, or similar.
• Experience with MLFlow, model versioning, and storage.
• Familiarity with Databricks or similar platforms.
• Experience supporting high-volume, real-time data products.
• Automated testing and validation frameworks.
• Experience designing and configuring low-latency databases to serve real-time features, such as DynamoDB.
• Experience with Terraform Cloud.
• Experience in large companies, mature engineering teams, and/or highly regulated industries.
• AI-assisted coding experience (e.g. GitHub Copilot).

Skills

• Hands-on production experience with ML model deployment and API design.
• Expertise with Python and relevant ML/data libraries.
• Experience with containerization, orchestration, and AWS cloud services.
• Proficiency in building and operating CI/CD pipelines.
• Knowledge of monitoring, troubleshooting, and optimizing production ML systems.
• Ability to conduct comprehensive code reviews and share knowledge.
• Experience with ML platform evolution and best practices.
• Proven ability to work independently and navigate ambiguity.
• Excellent communication and collaboration skills.

Benefits

Join a global team that values innovation, autonomy, and collaboration. Be part of a company that impacts the lives of millions through cutting-edge technology and supports your professional growth.

Pay

Competitive salary and benefits package tailored to your experience and qualifications.

Schedule

Flexible work schedule to accommodate your needs and the demands of the role.