AI/ML Engineer

Job Title: AI/ML Engineer Location: India (Offshore) Experience: 3–6 Years Role Type: Remote / Offshore About the Role We are looking for a hands-on AI/ML Engineer to design, develop, and productionize machine learning and Generative AI solutions for real-world business use cases. The ideal candidate should have strong experience in Python, machine learning, deep learning, LLMs, RAG, and MLOps , along with recent hands-on experience delivering Generative AI solutions in production environments. Key Responsibilities Design, develop, train, fine-tune, and evaluate machine learning and LLM-based solutions . Build and maintain end-to-end ML/AI pipelines, covering data ingestion, processing, model development, inference, deployment, and monitoring . Develop and implement Generative AI applications , including LLM-powered solutions and RAG-based systems. Apply prompt engineering, context engineering, and LLM fine-tuning techniques to improve model performance and reliability. Design and implement solutions using vector databases, embeddings, and retrieval-augmented generation (RAG) architectures. Collaborate with Solution Architects, Data Scientists, and engineering teams to translate business requirements into scalable AI/ML solutions. Optimize models and AI applications for accuracy, latency, scalability, and cost efficiency . Implement model evaluation, guardrails, observability, and monitoring for production AI/ML systems. Follow MLOps best practices, including model versioning, CI/CD, deployment automation, and model lifecycle management . Stay current with emerging developments in Generative AI, LLMs, AI engineering, and machine learning technologies . Required Skills & Experience 3–6 years of hands-on experience in Machine Learning Engineering or a closely related role. Strong proficiency in Python . Experience with machine learning and deep learning frameworks such as PyTorch, TensorFlow, and scikit-learn . Hands-on experience with Generative AI and LLM-based applications . Experience with LLM fine-tuning, prompt engineering, and context engineering . Strong understanding of RAG architectures, embeddings, vector databases, and semantic search . Experience building and deploying production-grade ML/AI pipelines . Working knowledge of MLOps practices , including model versioning and CI/CD for machine learning workloads. Experience with at least one major cloud-based ML platform: AWS SageMaker Azure Machine Learning Google Cloud Vertex AI Strong understanding of model evaluation, performance optimization, and production monitoring. Ability to work collaboratively with cross-functional technical teams and translate business requirements into practical AI/ML solutions. Nice to Have Experience working on AI/ML solutions in regulated or highly sensitive domains , such as healthcare or government technology. Experience with multi-agent AI systems and orchestration frameworks . Experience with LLM…