Machine Learning Engineer

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

Job summary

Emperen Technologies is looking for a highly skilled Machine Learning Engineer to join their AI team in Bengaluru. The ideal candidate should have over 5 years of experience in machine learning, a strong foundation in mathematics, and hands-on skills in building scalable ML systems.

The role involves designing, developing, and deploying ML models, collaborating with product teams, and optimizing model performance using advanced techniques.

Qualifications

• 5+ years of machine learning experience.
• Solid understanding of machine learning algorithms and optimization techniques.
• Experience with cloud platforms for model deployment.

Responsibilities

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

Skills

Strong foundation in Linear Algebra

Proficiency in Probability and Statistics

Proficient in Python

Experience with deep learning frameworks

Hands-on experience with supervised learning

Education

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

Tools

NumPy

Pandas

TensorFlow

MLflow

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.