Senior Software Engineer (Scala, ML Platform)

Quick Facts

• Role: Senior Software Engineer (Scala, ML Platform)
• Focus: Backend engineering for a production Machine Learning platform
• Work model: Fully remote (NYC preferred)
• Duration: 12 months

Description

You’ll join a technical engineering team responsible for a large-scale, distributed, latency-sensitive ML platform that serves as a central entry point for organization-wide ML capabilities. This is primarily a backend software engineering role where you’ll build and enhance Scala services, APIs, and orchestration components supporting production workloads.

You’ll improve reliability, test coverage, and observability while collaborating across engineering, applied science, data, and model-serving teams.

Responsibilities

• Design, build, enhance, and support high-scale backend services using Scala
• Improve reliability, maintainability, and developer experience of the production ML platform
• Increase automated test coverage and identify edge cases in a complex distributed codebase
• Use AI development tools (Claude, Codex) to improve productivity across PR review, approvals, testing, and code-quality workflows
• Develop and enhance APIs, request-routing services, and orchestration capabilities for production workloads
• Work with distributed, low-latency systems where performance and availability are critical
• Operate and troubleshoot production services running on Kubernetes
• Improve observability with metrics, tracing, alerting, profiling, and performance monitoring
• Collaborate with software engineers, applied scientists, data teams, and model-serving stakeholders
• Help make ML infrastructure increasingly reliable, automated, and self-service

Requirements

• 7+ years of backend/software engineering experience
• Strong hands-on Scala development experience in production environments
• Strong software engineering fundamentals and experience with complex distributed systems
• Experience building and operating scalable, production-grade backend services
• Functional programming foundation: immutability, composition, concurrency, and effects
• Experience designing or integrating APIs and request-routing systems, messaging systems, or queues (e.g., gRPC)
• Experience with Kubernetes: deployment, scaling, resource management, and production troubleshooting
• Strong production engineering skills: monitoring, observability, alerting, performance profiling, and reliability
• Ability to independently execute within an org of Senior/Staff engineers
• Strong communication skills and a product-oriented engineering mindset
• Understanding or interest in production ML infrastructure concepts (model inference/serving, feature retrieval, model evaluation, latency/throughput, batch vs real-time, production deployment of predictive/transformer-based models)

Benefits

• Work on sophisticated backend infrastructure at the intersection of Scala, distributed systems, ML platforms, developer productivity, and generative AI