Applied Machine Learning Engineer

Company Overview

Quess Corp Limited is India's largest staffing and workforce solutions company and a global leader in the space. Through deep domain expertise and AI-driven digital platforms, we help businesses enhance productivity with future-ready talent.

With a workforce of 480,000+ across eight countries and 2,200 global clients, Quess has grown from a start up to an industry powerhouse in just 18 years. Our international presence spans Singapore, Malaysia, the Philippines, Vietnam, Sri Lanka, the UAE, and the US.

Our business lines include General Staffing, IT Solutions, Recruitment & RPO, International Mobility, TaskMo (Gig Workforce), Origint (GCC Solutions), Hamara Suite (Digital Platforms), and Shared Services & COE in Jaipur.

Quess ranks #19 among India's Best Workplaces 2025, is certified Great Place to Work for the seventh consecutive year (2026), and has been recognised by Staffing Industry Analysts (SIA) as India's No.1 staffing company (2025) and 37th globally (2024).

About the Role

We are looking for an Applied Machine Learning Engineer who can build production-ready ML solutions for real business use cases. The role involves working across data preparation, model development, evaluation, deployment, and monitoring.

Responsibilities

• Develop machine learning solutions for classification, prediction, recommendation, NLP, or document-processing use cases.
• Prepare, clean, and analyse structured and unstructured datasets.
• Train, evaluate, optimise, and validate machine learning models.
• Build APIs and services for model inference.
• Deploy and monitor models in production.
• Improve model accuracy, reliability, latency, and scalability.
• Work with product and engineering teams to convert business requirements into ML solutions.
• Document experiments, datasets, assumptions, and results.

Required Skills

• 3–4 years of experience in applied machine learning.
• Strong proficiency in Python.
• Hands-on experience with scikit-learn, PyTorch, TensorFlow, or similar frameworks.
• Strong understanding of machine learning algorithms and evaluation metrics.
• Experience with Pandas, NumPy, SQL, and data-processing pipelines.
• Experience deploying models as APIs or production services.
• Working knowledge of Git, Docker, and cloud environments.
• Strong analytical and problem-solving skills.

Good to Have

• Experience with NLP, LLMs, RAG, computer vision, or document AI.
• Familiarity with vector databases and embedding models.
• Experience with MLOps, experiment tracking, and model monitoring.
• Exposure to AWS, Azure, or GCP