We are seeking a Senior ML Engineer / Machine Learning Solutions Lead to drive innovative ML strategies, design and deploy production-grade models, and deliver business-wide impact through cutting-edge solutions. The role requires expertise in end-to-end ML system design, Generative AI, and distributed cloud-based platforms.
Key Responsibilities
- Act as a thought leader , shaping the ML vision across products and platforms and driving strategic innovation.
- Lead the full software development lifecycle (SDLC) including design, testing, deployment, and operations.
- Develop high-performance, production-ready ML code for real-time ML platforms and extend existing ML frameworks and libraries.
- Collaborate with engineers and data scientists to accelerate model development, validation, and experimentation , integrating algorithms into scalable production systems.
- Participate actively in design reviews, code reviews, and technical strategy discussions to ensure high-quality ML solutions.
Requirements
Degree in Computer Science, Mathematics, or a related field.5+ years of experience across SDLC including design, coding, testing, deployment, and operations.5+ years of hands-on experience building and deploying end-to-end ML solutions in production .Practical experience in Generative AI (RAG, AI Agents, LLM fine-tuning) in production environments.Experience with cloud platforms (AWS, Azure, GCP) and distributed systems.Strong problem-solving skills with the ability to tackle complex, ambiguous challenges.Preferred Qualifications
MS or PhD in Computer Science, Machine Learning, or related disciplines.Experience with Graph ML and technologies like GNNs or Graph RAG.Knowledge of distributed Big Data technologies such as Spark, Flink, Kafka, PySpark, Lakehouse, Druid, Hudi, or Glue.Skills Required
Generative AI (RAG, Distributed Cloud ML Systems, SDLC Expertise, Graph ML, Big Data Technologies (Spark / Kafka / PySpark), Production-Grade ML Code Development