Senior Machine Learning Engineer

We are looking for experienced Senior Machine Learning Engineers and ML Architects to design, build, and deploy scalable AI/ML solutions that solve complex business problems. In this role, you will work on enterprise-grade data platforms, develop production-ready machine learning and Generative AI applications, and help shape the future of AI-driven products. If you're passionate about Machine Learning, MLOps, Large Language Models (LLMs), and building intelligent systems at scale, we'd love to hear from you.
Responsibilities:
Design, develop, and deploy production-grade machine learning solutions across diverse business domains.
Build and optimise enterprise AI applications using Large Language Models (LLMs) and Generative AI.
Develop Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge repositories.
Build natural language interfaces for querying structured and unstructured enterprise data.
Apply MLOps best practices to automate model deployment, monitoring, versioning, and lifecycle management.
Collaborate with cross-functional teams to deliver scalable, high-performance AI solutions.
Provide technical guidance on AI/ML architecture, tooling, and best practices.
Ensure reliability, scalability, and performance of ML models in production environments.
Requirements:
Senior ML Engineer: 4+ years of relevant industry experience.
ML Architect: 6+ years of relevant industry experience.
Strong proficiency in Python and the AI/ML ecosystem.
Hands-on experience with Pandas, Scikit-learn, MLflow, Gensim, NLTK, TensorFlow, or PyTorch.
Experience building and deploying production-grade ML solutions on AWS, Azure, or Google Cloud Platform.
Practical experience with MLOps, including model deployment, monitoring, and drift detection.
Strong understanding of Machine Learning algorithms, data science workflows, and model evaluation techniques.
Experience developing LLM-based applications, including Prompt Engineering, RAG, embeddings, and enterprise AI use cases.
Excellent problem-solving, communication, and collaboration skills.
Preferred Qualifications:
Experience with Apache Spark for large-scale distributed data processing.
Hands-on experience with Databricks.
Experience building enterprise AI applications using LLMs and Generative AI frameworks.
Master's degree or higher in Computer Science, Engineering, Statistics, Mathematics, Operations Research, or a related quantitative field (or equivalent practical experience).

Experience
4-8 yrs