Designs, develops, and maintains high-performance ML services and agentic AI systems, collaborating with ML engineers to scale from prototype to production. Requires 5+ years backend/ML experience, cloud-native tech, and strong architecture skills.
190 – 220/hr
On-site5+ YOEML Engineering
About the role
Key Responsibilities
Be a driving force for the team's agentic coding practice - establishing patterns for spec-driven development, context engineering, and multi-agent orchestration that compound team output.
Design, develop, and maintain AI-powered applications and services, focusing on high availability, performance, and reliability.
Work closely with Machine Learning Engineers, building AI capabilities from early R&D prototyping to scalable operation in multiple production stacks.
Build ML services designed for low-latency or high-throughput, and optimized for high cost efficiency.
Lead cross-functional initiatives, collaborating with Machine Learning Engineers, Product Managers, and other teams to align technical solutions with business needs.
Drive innovation by making strategic technical decisions, setting best practices, and mentoring engineers to elevate the team’s technical bar.
Improve ML development process by enhancing the internal ML platform, facilitating data sourcing, and enabling ML observability for deployed services.
Required Skills
Fluency with agentic coding tools (Claude Code, Codex or equivalent). Experience writing effective specs, managing repo context, and reviewing/verifying agent output.
5+ years of experience in software development, with a strong backend and ML engineering background.
Experience working with cloud native technologies (Docker, Kubernetes).
Experience working with cloud platforms (AWS, GCP, or Azure).
Experience with building ML systems, from early prototype, to operating at scale in production.
Strong software architecture skills, with experience designing and scaling distributed systems and cloud-based applications.
Experience mentoring engineers and contributing to team-wide technical direction.
Strong communication skills, with the ability to translate technical challenges into business impact.
Nice to Have
Experience with ML frameworks like PyTorch.
Experience with serving ML models and LLMs using frameworks like vLLM.
Experience with developer-facing products and building intuitive APIs.
Owns evaluation frameworks, datasets, and automations to enhance AI system performance in operations. Requires 3+ years experience with AI tools, LLM workflows, scripting (SQL/Python), and driving ambiguous tasks to execution.
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