Senior ML Software Engineer

About the team

Qualifications

• 5+ years as an software engineer, MLOps Engineer, or similar, with hands-on production experience operating backend services or ML-backed APIs
• Proven expertise deploying ML models as production services, API design, and service integration
• Strong Python skills and service/backend engineering experience (ideally in FastAPI/OpenAPI, Flask, Go, or Java)
• Production experience with containerization and orchestration (ideally Kubernetes – EKS/OpenShift), Docker, and IaC (ideally Terraform or Terraform Cloud)
• Ownership of CI/CD pipelines, monitoring/alerting, and on-call/incident response
• Experience monitoring, troubleshooting, optimizing production ML systems (latency, throughput, availability)
• Excellent communication and cross-functional collaboration skills
• Demonstrated ability to work independently, navigate ambiguity, resolve blockers, and deliver results with a strong sense of urgency
• Experience with MLFlow / model versioning, SageMaker Pipelines, or Databricks
• Familiarity with real-time, high-volume data products and low-latency data stores (e.g. DynamoDB)
• Automated testing and validation frameworks for models and services
• Experience in regulated industries (e.g. PCI, HIPAA, SOC2), large companies, or mature engineering teams
• Why Join Us?
• Impact: Own high-profile ML-backed services that power customer-facing products driving measurable business outcomes
• Autonomy: Take end-to-end technical ownership of your product area, with the responsibility and freedom to drive robust technical solutions, shape best practices, and deliver results in a fast-paced, supportive environment.
• Collaboration: Join a cross-functional, high-performing team where your expertise is valued and grow with industry experts across engineering and product.

Preferred Qualifications

• It’s a bonus if you have
• Optional familiarity with LLM tooling / RAG