Machine Learning Engineer

1 day ago

Multiple Locations, India Emperen Technologies Full time ₹ 6,00,000 - ₹ 18,00,000 per year

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

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