We are hiring a Senior AI/ML Engineer specializing in Natural Language Processing (NLP) and Generative AI to join our high-impact AI Solutions team, focused on delivering advanced, production-grade AI solutions in the Electrification domain. In this role, you will work at the frontier of AI innovation—designing and developing Retrieval-Augmented Generation (RAG) pipelines, fine tuning LLMs, and building Agentic AI systems that are robust, scalable, and insightful
1. Design, develop, and optimize NLP-driven AI solutions using state-of-the-art models and techniques (NER, embeddings, summarization, etc.). 2. Build and productionize RAG pipelines and agentic workflows to support intelligent, context aware applications. 3. Fine-tune, prompt-engineer, and deploy LLMs (OpenAI, Anthropic, Falcon, LLaMA, etc.) for domain-specific use cases. 4. Collaborate with data scientists, backend developers, and cloud architects to build scalable AI first systems. 5. Evaluate and integrate third-party models/APIs and open-source libraries for generative use cases. 6. Continuously monitor and improve model performance, latency, and accuracy in production settings. 7. Implement observability, performance monitoring, and explainability features in deployed models. 8. Ensure solutions meet enterprise-level requirements for reliability, traceability, and maintainability
Master’s or Bachelor’s degree in Computer Science, Machine Learning, AI, or a related field. 5+ years of overall experience in AI/ML, with at least2+ years in NLPand1–2 years in Generative AI. Strong understanding of LLM architectures, fine-tuning methods (LoRA, PEFT),embeddings, and vector search. Experience in designing and deploying RAG pipelines and working with multi-step agent architectures. Proficiency in Python and frameworks like LangChain, Transformers (HuggingFace), LlamaIndex, SmolAgents, etc. Familiarity with ML observability and explainability tools (e.g., TruEra, Arize, WhyLabs). Knowledge of cloud-based ML services like AWS Sagemaker, AWS Bedrock, Azure OpenAI Service, Azure ML Studio, and Azure AI Foundry. Preferred Qualifications: Experience in integrating LLM-based agents in production environments. Understanding of real-time NLP challenges (streaming, latency optimization, multi-turn dialogues). Familiarity withLangGraph, function calling, and tools for orchestration in agent-based systems. Exposure to infrastructure-as-code (Terraform/CDK) and DevOps for AI pipelines. Domain knowledge in Electrification, Energy, or Industrial AI is a strong plus
