Machine Learning Engineer

Emperen Technologies; Kolkata District; On-site; INR 15,00,000 - 25,00,000; Full time

Job summary

A leading technology firm in Kolkata is looking for a highly skilled Machine Learning Engineer to join their AI team. The candidate should have over 5 years of experience in machine learning, with a strong grasp of algorithms, statistical modeling, and optimization techniques. Responsibilities include designing scalable ML systems, collaborating with various teams, and conducting mathematical analyses for optimization. A Master's or Ph.D. in a relevant field is preferred, along with proficiency in Python and experience with deep learning frameworks.

Qualifications

• 5+ years of ML experience with a deep understanding of machine learning algorithms.
• Proficient in Python and experienced with popular ML libraries.
• Hands-on experience designing, developing and deploying scalable ML models.

Responsibilities

• Design and deploy machine learning models for real-world applications.
• Collaborate with teams to integrate ML solutions into production systems.
• Conduct mathematical analysis of algorithms to ensure performance and scalability.

Skills

Linear Algebra

Probability and Statistics

Calculus

Python

Deep Learning frameworks (TensorFlow, PyTorch)

Education

Master's or Ph.D. in Computer Science, Mathematics, Statistics, or related field

Tools

NumPy

Pandas

Scikit-learn

TensorFlow

Docker

Job description

Job Summary

We are seeking a highly skilled and mathematically grounded Machine Learning Engineer to join our AI team. The ideal candidate will have 5+ years of ML experience with a deep understanding of machine learning algorithms, statistical modeling, and optimization techniques, along with hands‑on experience in building scalable ML systems using modern frameworks and tools.

Key Responsibilities

• Design, develop, and deploy machine learning models for real-world applications.
• Collaborate with data scientists, software engineers, and product teams to integrate ML solutions into production systems.
• Understand the mathematics behind machine learning algorithms to effectively implement and optimize them.
• Conduct mathematical analysis of algorithms to ensure robustness, efficiency, and scalability.
• Optimize model performance through hyperparameter tuning, feature engineering, and algorithmic improvements.
• Stay updated with the latest research in machine learning and apply relevant findings to ongoing projects.

Required Qualifications

Mathematics & Theoretical Foundations

• Strong foundation in Linear Algebra (e.g., matrix operations, eigenvalues, SVD).
• Proficiency in Probability and Statistics (e.g., Bayesian inference, hypothesis testing, distributions).
• Solid understanding of Calculus (e.g., gradients, partial derivatives, optimization).
• Knowledge of Numerical Methods and Convex Optimization.
• Familiarity with Information Theory, Graph Theory, or Statistical Learning Theory is a plus.

Programming & Software Skills

• Proficient in Python (preferred), with experience in libraries such as: NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn.
• Experience with deep learning frameworks: TensorFlow, PyTorch, Keras, or JAX.
• Familiarity with ML Ops tools: MLflow, Kubeflow, Airflow, Docker, Kubernetes.
• Experience with cloud platforms (AWS, GCP, Azure) for model deployment.

Machine Learning Expertise

• Hands‑on experience with supervised, unsupervised, and reinforcement learning.
• Understanding of model evaluation metrics and validation techniques.
• Experience with large‑scale data processing (e.g., Spark, Dask) is a plus.

Preferred Qualifications

• Master's or Ph.D. in Computer Science, Mathematics, Statistics, or a related field.
• Publications or contributions to open‑source ML projects.
• Experience with LLMs, transformers, or generative models.