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Research AI ML Engineer || Noida || Hybrid

Research AI ML Engineer || Noida || Hybrid

Michael Page
Early Applicant
  • Posted 15 hours ago
  • Be among the first 10 applicants

Job Description

  • Work in a fast paced environment
  • Work with a global firm

About Our Client

Our client is a global technology services organization specializing in AI, data engineering, and advanced machine learning solutions. They partner with leading enterprises and AI innovators to develop, evaluate, and improve next-generation AI models.

Job Description

  • 2-3+ years of experience in Machine Learning, AI Systems, or Research Engineering with hands-on exposure to LLMs.
  • Strong experience in LLM fine-tuning, post-training workflows, SFT, DPO, RLHF/RLAIF, or foundation model adaptation.
  • Proficiency in Python and modern ML frameworks such as PyTorch, TensorFlow, JAX, and Hugging Face.
  • Experience designing and implementing evaluation pipelines, benchmarking frameworks, and experiment tracking systems.
  • Strong understanding of ML systems engineering, data pipelines, reproducibility, debugging, and distributed training environments.

The Successful Applicant

We're Looking For Someone Who Has

  • Hands-on experience building, fine-tuning, and evaluating LLMs or multimodal AI models.
  • Strong software engineering capabilities with production-grade Python development experience.
  • Expertise in experimentation, model benchmarking, performance optimization, and evaluation methodologies.
  • Ability to collaborate effectively with researchers, data engineers, and technical stakeholders in complex AI environments.
  • Strong problem-solving skills with the ability to translate research concepts into scalable engineering solutions.

What's on Offer

  • A permanent role based in Noida.
  • Opportunities to work in the not-for-profit business school sector.
  • Exposure to cutting-edge AI/ML technologies.

If this role matches what you're looking for, you can apply.

Quote job ref: JN-092026-7097834

More Info

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Key Skills

RLAIF

Research Engineering

data pipelines

SFT

LLMs

DPO

reproducibility

distributed training

Hugging Face

experiment tracking systems

LLM fine-tuning

AI Systems

evaluation pipelines

foundation model adaptation

ML systems engineering

benchmarking frameworks

RLHF

About Company