# Senior Machine Learning Engineer

> Weekday AI · Noida, India · Full-time · Posted 2026-07-16

**Salary:** INR 4,000,000–7,000,000

**Workplace:** on_site

**Department:** Weekday's Client via platform

## Description

**This role is for one of the Weekday's clients**

**Salary range: Rs 4000000 - Rs 7000000 (ie INR 40-70 LPA)**

Experience: 5+ yrs

Location: Noida, Uttar Pradesh, India

Job Type: Full-Time

We are looking for an experienced **Machine Learning Engineer** with strong expertise in **Large Language Models (LLMs)** to build, fine-tune, and optimize AI models for domain-specific applications. This role is ideal for professionals who enjoy working on cutting-edge generative AI technologies, adapting foundation models for real-world use cases, and delivering scalable AI solutions in a fast-paced, innovation-driven environment.

As an ML Engineer, you will own the complete model adaptation lifecycle—from dataset preparation and fine-tuning to evaluation, optimization, and deployment. You will work with modern open-source LLMs, implement efficient fine-tuning techniques, and develop AI models that deliver high-quality, context-aware outputs. This is a high-ownership role where you will collaborate with cross-functional engineering and product teams to build production-ready AI systems while continuously improving model quality, efficiency, and scalability.

## Requirements

### Key Responsibilities

-   Fine-tune and optimize Large Language Models (LLMs) for domain-specific tasks such as question answering, content generation, summarization, and intelligent automation.
-   Own end-to-end model adaptation workflows, including dataset preparation, training, hyperparameter tuning, evaluation, and model versioning.
-   Implement efficient fine-tuning approaches such as LoRA, QLoRA, DoRA, adapters, and other parameter-efficient training techniques.
-   Build and optimize reinforcement learning and preference optimization pipelines using techniques such as RLHF, DPO, PPO, and reward modeling.
-   Develop scalable training pipelines using distributed and multi-GPU environments.
-   Optimize GPU utilization through DeepSpeed, FSDP, mixed precision, gradient checkpointing, and other performance optimization techniques.
-   Design and maintain multilingual and instruction-tuning datasets to improve model performance across diverse use cases.
-   Evaluate model quality using automated benchmarks, task-specific metrics, human evaluations, and regression testing.
-   Continuously assess emerging open-source foundation models and recommend suitable architectures for production adoption.
-   Define model performance benchmarks, monitor quality metrics, and drive continuous optimization across multiple model versions.
-   Collaborate with engineering, product, and data teams to integrate AI models into scalable production environments.
-   Contribute to AI infrastructure, model deployment, and best practices for enterprise-grade machine learning systems.

### What Makes You a Great Fit

-   5+ years of experience in Machine Learning, Deep Learning, or AI Engineering.
-   Strong hands-on expertise in **Python**, **PyTorch**, and the Hugging Face ecosystem, including Transformers, PEFT, and TRL.
-   Proven experience fine-tuning and optimizing Large Language Models using techniques such as LoRA, QLoRA, SFT, DPO, RLHF, or similar methods.
-   Experience working with distributed training, multi-GPU environments, and large-scale model optimization.
-   Strong understanding of model evaluation methodologies, benchmarking, and performance optimization.
-   Hands-on experience with DeepSpeed, Megatron-LM, FSDP, or comparable large-scale training frameworks.
-   Knowledge of AI/ML pipelines, dataset preparation, model deployment, and production AI systems.
-   Familiarity with Hugging Face tools, GPU optimization, and open-source LLM ecosystems is highly desirable.
-   Strong analytical, debugging, and problem-solving skills with a passion for building high-quality AI solutions.
-   Comfortable working in high-ownership, fast-moving environments with the ability to adapt quickly, solve ambiguous problems, and contribute to building innovative AI products from the ground up.

## Apply

[Apply at Weekday AI](https://apply.workable.com/weekday-1/j/52E3BE30F8/apply)

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