AIML

AIML
We are hiring a Senior AIML 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 innovatiodesigning and developing RetrievalAugmented Generation (RAG) pipelines, finetuning
LLMs, and building Agentic AI systems that are robust, scalable, and insightful.
Responsibilities:
Design, develop, and optimize NLPdriven AI solutions using state-of-the-art models and
techniques (NER, embeddings, summarization, etc.).
Build and productionize RAG pipelines and agentic workflows to support intelligent, contextaware
applications.
Finetune, prompt-engineer, and deploy LLMs (OpenAI, Anthropic, Falcon, LLaMA, etc.) for
domainspecific use cases.
Collaborate with data scientists, backend developers, and cloud architects to build scalable AIfirst
systems.. Evaluate and integrate third-party models/APIs and open-source libraries for generative use
cases.
Continuously monitor and improve model performance, latency, and accuracy in production
settings. Implement observability, performance monitoring, and explainability features in deployed
models.
Ensure solutions meet enterprise-level requirements for reliability, traceability, and
maintainability.
Required Qualifications:
Master or Bachelor degree in Computer Science, Machine Learning, AI, or a related field.
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.

Mandatory Skills

Natural Language Processing (NLP)
Generative AI
RAG pipelines
LLMs