Senior Associate - AI - ML Engineer

Overview

The AI Platform Lead Engineer builds and maintains scalable, efficient, and reliable systems that support AI and machine learning applications. The role designs, deploys, and optimizes production-grade Generative AI solutions, including RAG pipelines, AI agents, model evaluation, observability, and multimodal AI capabilities.

What you'll do

• Deploy, manage, and scale AI systems and support model activity and deployment infrastructure in cloud environments.
• Work with infrastructure and application development teams, data engineers, and model owners to integrate AI applications into mainstream enterprise applications.
• Put ML models into production with consideration for scalability, optimization, resource availability, and security.
• Design and implement end-to-end Generative AI solutions focused on scalability, reliability, and production readiness.
• Build and maintain Retrieval-Augmented Generation pipelines using vector databases, embedding models, and large language models.
• Develop and optimize prompting strategies, templates, and workflows for LLM accuracy, consistency, and performance.
• Customize and fine-tune foundation models using SFT, RLHF, LoRA, and QLoRA.
• Establish model evaluation frameworks covering accuracy, latency, cost-efficiency, hallucination rates, and task-specific metrics.
• Conduct A/B testing and comparative analysis to inform model selection and configuration decisions.
• Implement observability and monitoring systems, including logging, tracing, and alerting, for production model behavior and performance.
• Design and deploy production-grade AI agents using low-code platforms and custom high-code implementations.
• Integrate natural language processing, computer vision, document intelligence, and traditional machine learning models into multimodal solutions.
• Research and adopt emerging AI models, frameworks, and tools.
• Collaborate with product, engineering, and business stakeholders to translate requirements into scalable AI architectures.
• Contribute to best practices, reusable components, and internal standards for Generative AI development and responsible AI use.

What you'll need

• University degree.
• 5+ years of work experience.
• Total experience required between 9 to 15 years.
• Proven hands-on experience building and deploying Generative AI solutions, including RAG pipelines, prompt engineering, and LLM fine-tuning using frameworks such as LangChain, LlamaIndex, or simila.
• Strong proficiency in Python.
• Experience working with LLM APIs including OpenAI, Anthropic, and Hugging Face.
• Experience with vector databases such as Pinecone, Weaviate, or FAISS.
• Strong understanding of model evaluation methodologies, including benchmarking, A/B testing, hallucination detection, and performance monitoring in production environments.
• Experience with SFT, RLHF, LoRA, and QLoRA, along with familiarity with parameter-efficient training approaches for domain-specific model customization.
• Ability to design and deploy production-grade AI systems with robust observability, logging, and monitoring capabilities.

Nice to have

• 7+ years of work experience.
• Exposure to multimodal AI capabilities including computer vision, document intelligence, or speech processing integrated within broader AI/ML pipelines.
• Familiarity with low-code AI agent platforms such as Microsoft Copilot Studio, Flowise, or similar, alongside the ability to build custom high-code agent implementations.
• Experience working within AWS, Azure, or GCP cloud environments and using managed AI/ML services for model training, deployment, and scaling.
• Knowledge of responsible AI principles, including bias detection, fairness evaluation, and compliance considerations relevant to regulated industries such as financial services.
• Familiarity with MLOps practices and tools such as MLflow, Weights & Biases, or similar platforms for experiment tracking, model versioning, and deployment automation.

Details

• Job location: Mumbai / Pune.
• Physical requirement: Sedentary work.