Senior ML Software Engineer
Role details
Job location
Tech stack
Job description
We are seeking an experienced Senior ML Software Engineer to join our Data Science Enablement team. You will be the primary software engineering expert for a product area, working as part of a cross-functional agile team and owning the successful launches and ongoing operations of high-profile products in production. Your focus will be on driving new feature delivery, maintaining operational excellence, and collaborating on enhancements to our shared ML platform. You will work closely with cross-functional collaborators-including ML research engineers, product managers, and platform engineers-to deliver scalable, reliable, and low-latency ML solutions.
In addition to technical expertise, this job requires strong collaboration skills.
What you'll own
Feature Development & Delivery:
- 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:
- Technical ownership of existing and new production ML products in your area, ensuring alignment of technical investments with business goals (in collaboration with a product owner) and engineering best practices.
- End-to-end technical stewardship of ML products, ensuring ongoing reliability and performance.
Contribute to ML platform:
- Contribute to the evolution of the shared ML platform alongside other engineers to drive best practices and shared tooling across all products.
Operational Excellence:
- 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.
Continuous Improvement:
- Identify and implement opportunities for process, tooling, and system improvements, proactively addressing technical debt and scaling challenges.
Release Management:
- Oversee pre-release testing, coordinate releases and ensure smooth enablement of new features.
Leadership:
- 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.
- Foster a culture of collaboration, continuous improvement, and knowledge sharing.
Act Like an Owner:
- 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
- Experience with OpenAPI, FastAPI, or similar
It's a bonus if you have
- 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)