Senior Machine Learning Engineer

This is a hands-on senior IC role with significant responsibility in technical execution and Agile delivery , reporting to the ML Tech Lead .\n\nThe ideal candidate is a strong backend and ML engineer who can own sprint execution and day-to-day Scrum activities , while partnering closely with the Tech Lead on architecture, technical direction, and prioritization.\n\nYou will work at the intersection of backend engineering and applied machine learning , contributing directly to production systems while helping the team deliver consistently and effectively.\n\nKey Responsibilities\nSoftware Engineering & System Design\nDesign, develop, and maintain scalable backend services using Python and modern web frameworks.\nImplement efficient algorithms and data structures (e.g., greedy algorithms, BFS/DFS, dynamic programming).\nWrite clean, maintainable, and testable code using object-oriented design principles .\nContribute to technical design discussions and implementation decisions under guidance from the ML Tech Lead.\nMachine Learning & LLM Integration\nBuild and integrate machine-learning-powered features , with an emphasis on LLM-based systems .\nWork with ML and LLM platforms such as OpenAI API, Gemini, and Hugging Face .\nApply best practices for prompt engineering, evaluation, and production deployment of ML/LLM solutions.\nBackend, Cloud & Infrastructure\nDevelop and operate web services using frameworks such as Flask, FastAPI, or Django .\nDesign and work with SQL databases, Redis, and MongoDB .\nDeploy and support services in AWS and GCP environments.\nCollaborate on CI/CD, monitoring, and operational reliability .\nAgile Execution & Scrum Responsibilities (Nice to Have)\nServe as Scrum Master for the ML team , focusing on execution and delivery:\nBreak down work into actionable tasks\nDefine clear acceptance criteria\nFacilitate sprint planning, daily standups, reviews, and retrospectives\nMaintain and clarify the sprint backlog\nTrack progress, surface risks and blockers early, and drive resolution.\nPartner with the ML Tech Lead and Product stakeholders to ensure alignment and predictable delivery.\nCollaboration & Mentorship\nCommunicate effectively with engineers and stakeholders.\nMentor junior engineers through code reviews, technical guidance, and best practices .\nPromote a culture of high-quality execution, accountability, and continuous improvement .\n\nRequired Qualifications\n5+ years of professional software engineering experience , with strong focus on Python .\nSolid understanding of algorithms and data structures .\nStrong experience with object-oriented programming .\nExperience with at least one strongly typed language such as Java, Go (Golang), C++, or similar .\nHands-on experience building or integrating LLM-based systems .\nFamiliarity with AI-assisted coding tools such as Claude-Code, Cursor, GitHub Copilot, etc\nExperience working with ML APIs or platforms (OpenAI, Gemini, Hugging Face).\nProven experience building backend systems in cloud environments .\nNice to have - > Practical experience acting as a Scrum Master or Agile lead for an engineering team.\nStrong communication skills and comfort working in Agile/Scrum environments.