Senior Machine Learning Engineer | $35/hr

HelixRecruit; India; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

A leading AI research lab is seeking a Machine Learning Engineer in India to design, implement, and evaluate high-performance ML systems. Ideal candidates will have a minimum of 2 years of experience in ML model development and be proficient in Python and frameworks like PyTorch and TensorFlow. Responsibilities include optimizing ML models and running experiments. This is an excellent opportunity for individuals passionate about driving AI advancements in a collaborative environment.

Qualifications

• 2+ years of full-time experience in machine learning model development.
• Proficient in building reproducible machine learning pipelines.
• Competitiveness in machine learning challenges like Kaggle.

Responsibilities

• Frame unique ML problems to enhance ML capabilities.
• Design and optimize machine learning models for various tasks.
• Run rapid experimentation cycles and iterate continuously.
• Implement adversarial testing and model robustness checks.
• Document datasets, experiments, and model decisions.

Skills

Machine Learning Engineering

Python

PyTorch

TensorFlow

Statistical Analysis

Problem Solving

Cloud Environments

Education

Technical degree in Computer Science, Electrical Engineering, Statistics, Mathematics or a related field

Tools

ML/NLP frameworks

AWS

GCP

Azure

Job description

This opportunity is shared as part of a referral program

Role Description

Mercor is hiring on behalf of a leading AI research lab to bring on highly skilled Machine Learning Engineers with a proven record of building, training, and evaluating high-performance ML systems in real-world environments. In this role, you will design, implement, and curate high-quality machine learning datasets, tasks, and evaluation workflows that power the training and benchmarking of advanced AI systems.

This position is engineers who have excelled in competitive machine learning settings such as Kaggle, possess deep modelling intuition, and can translate complex real-world problem statements into robust, well-structured ML pipelines and datasets. You will work closely with researchers and engineers to develop realistic ML problems, ensure dataset quality, and drive reproducible, high-impact experimentation.

Candidates should have 2+ years of applied ML experience or a strong record in competitive ML, and must be based in India. Ideal applicants are proficient in Python, experienced in building reproducible pipelines, and familiar with benchmarking frameworks, scoring methodologies, and ML evaluation best practices.

Responsibilities

• Frame unique ML problems for enhancing ML capabilities of LLMs.
• Design, build, and optimise machine learning models for classification, prediction, NLP, recommendation, or generative tasks.
• Run rapid experimentation cycles, evaluate model performance, and iterate continuously.
• Conduct advanced feature engineering and data preprocessing.
• Implement adversarial testing, model robustness checks, and bias evaluations.
• Fine-tune, evaluate, and deploy transformer-based models where necessary.
• Maintain clear documentation of datasets, experiments, and model decisions.
• Stay updated on the latest ML research, tools, and techniques to push modelling capabilities forward.

Required Qualifications

• At least 2 years of full-time experience in machine learning model development
• Technical degree in Computer Science, Electrical Engineering, Statistics, Mathematics, or a related field
• Demonstrated competitive machine learning experience (Kaggle, DrivenData, or equivalent)
• Evidence of top-tier performance in ML competitions (Kaggle medals, finalist placements, leaderboard rankings)
• Strong proficiency in Python, PyTorch/TensorFlow, and modern ML/NLP frameworks
• Solid understanding of ML fundamentals: statistics, optimisation, model evaluation, architectures
• Experience with distributed training, ML pipelines, and experiment tracking
• Strong problem-solving skills and algorithmic thinking
• Experience working with cloud environments (AWS/GCP/Azure)
• Exceptional analytical, communication, and interpersonal skills
• Ability to clearly explain modelling decisions, tradeoffs, and evaluation results
• Fluency in English

Preferred / Nice to Have

• Kaggle Grandmaster, Master, or multiple Gold Medals
• Experience creating benchmarks, evaluations, or ML challenge problems
• Background in generative models, LLMs, or multimodal learning
• Experience with large-scale distributed training
• Prior experience in AI research, ML platforms, or infrastructure teams
• Contributions to technical blogs, open-source projects, or research publications
• Prior mentorship or technical leadership experience
• Published research papers (conference or journal)
• Experience with LLM fine-tuning, vector databases, or generative AI workflows
• Familiarity with MLOps tools: Weights & Biases, MLflow, Airflow, Docker, etc.
• Experience optimising inference performance and deploying models at scale

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