Machine Learning Engineer
11 hours ago
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 & 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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