Machine Learning Engineer

Emperen Technologies; Kolkata District; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Emperen Technologies is looking for a skilled Machine Learning Engineer to join their AI team in Kolkata. Candidates should possess a strong mathematical background and 5+ years of hands-on experience in machine learning.

Responsibilities include designing and deploying ML models, collaborating with various teams, and optimizing algorithm performance. Proficiency in Python and familiarity with tools like TensorFlow are essential.

Qualifications

• 5+ years of experience in machine learning.
• Strong foundation in linear algebra, probability, and calculus.
• Proficient in Python and familiar with ML libraries.

Responsibilities

• Design, develop, and deploy machine learning models.
• Collaborate with teams to integrate ML solutions.
• Conduct mathematical analysis of algorithms.

Skills

Linear Algebra

Probability and Statistics

Calculus

Python

TensorFlow

PyTorch

Education

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

Tools

NumPy

Scikit-learn

AWS

Docker

Job description

Job Title

Machine Learning Engineer

Job Type

Full-Time

Experience Level

Mid to Senior (5+ Years)

Department

Data Science / AI Engineering

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.