Mancer Consulting Services
Lead AIML
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Gurugram, Haryana, India
Work mode:
Onsite
Published on:
21 September 2026
What they need
Lead AI/ML Engineer About the Role
We are seeking an experienced Lead AI/ML Engineer to drive the design, development, and deployment of advanced Artificial Intelligence and Machine Learning solutions at enterprise scale.
The role will work closely with senior data scientists, machine learning engineers, software engineers, product teams, and subject matter experts to develop innovative AI solutions and translate advanced research into production-ready applications.
The ideal candidate will have deep expertise in Machine Learning, Deep Learning, Natural Language Processing, Large Language Models, Information Retrieval, Information Extraction, and Generative AI, along with a proven track record of taking AI solutions from proof of concept to production.
Job Description
The role will focus on enhancing and developing advanced NLP and AI technologies and extending them into scalable cloud-based applications.
The candidate will be responsible for developing novel machine and deep learning techniques for information extraction, document understanding, semantic search, retrieval, and synthesis.
The role involves the complete AI development lifecycle, including research, experimentation, proof-of-concept development, model training and fine-tuning, performance evaluation, optimization, and production deployment.
Primary Responsibilities
- Lead end-to-end training and fine-tuning of Large Language Models (LLMs) across open-source and closed-source ecosystems.
- Design and implement GraphRAG pipelines, including knowledge graph representation and retrieval for improved contextual grounding.
- Design, train, and optimize semantic and dense vector embeddings for document understanding, search, and retrieval.
- Develop advanced semantic retrieval systems using effective document segmentation, preprocessing, and indexing strategies.
- Build and scale distributed training environments for multi-GPU and multi-node model training.
- Apply reinforcement learning techniques such as RLHF, RLAIF, PPO, DPO, and GRPO to improve model alignment and performance.
- Translate business and technical requirements into scalable AI-driven solutions.
- Collaborate with cross-functional teams to develop and deploy AI/ML solutions into production environments.
- Conduct experimentation, benchmarking, and performance characterization of AI models.
- Translate research concepts and published methodologies into practical proof-of-concepts and production-grade solutions.
- Drive innovation in NLP, Generative AI, LLMs, information extr
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
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