Senior AI/ML Engineer NLP & Generative AI

Role: Senior AI/ML Engineer NLP & Generative AI

About the Role

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 innovationdesigning and developing Retrieval-Augmented Generation (RAG) pipelines, fine- tuning LLMs, and building Agentic AI systems that are robust, scalable, and insightful.

Responsibilities

• 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.

Required Qualifications:

• Masters or Bachelors degree in Computer Science, Machine Learning, AI, or a related field.
• 5+ years of overall experience in AI/ML, with at least 2+ years in NLP and 12 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 with LangGraph, 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.