Senior Software Engineer (ML Infrastructure)

About the role:

You’ll be part of a high-impact, highly collaborative team — building the backbone of ML/GenAI systems, while operating with the professionalism and scalability mindset of large engineering orgs, and the flexibility and culture of a modern tech company.

What You’ll Do

• Lead design and implementation of scalable backend systems supporting AI/ML workflows and GenAI-based agents.
• Architect tools and platforms for model training, deployment, orchestration, monitoring, and observability.
• Partner with ML scientists, data engineers and product leaders to define and deliver integration of AI features into production.
• Drive reliability, performance, observability, and cost-efficiency in ML infrastructure at scale (AWS, Kubernetes, containers, etc.).
• Mentor juniors, set best practices, enforce engineering standards, and contribute to architectural decisions across the stack.
  
  

What We’re Looking For

• 5-10 years of strong software engineering experience, especially in backend or infrastructure systems (distributed systems, APIs, microservices).
• Robust coding experience (preferably Python) and solid familiarity with AWS or other cloud platforms. Comfortable with adopting and evaluating new frameworks/tools as needed.
• Prior experience working with ML/AI systems, MLOps, pipelines or similar infra is strongly preferred.
• Excellent demonstrated skills in system thinking, debugging, performance optimization and reliability engineering.
• Strong collaborator and communicator, able to partner across functions and lead technical discussions.
• Bachelor’s degree (or higher) in CS, AI/ML or equivalent experience.