Senior Machine Learning Engineer

Responsibilities:

• Design, build, and deploy machine learning models for predictive analytics, classification, recommendation systems, NLP, or computer vision use cases.
• Collaborate with data scientists, product managers, and engineers to understand business problems and translate them into ML/AI solutions.
• Optimize model performance through feature engineering, hyperparameter tuning, and algorithm selection.
• Build end-to-end ML pipelines, ensuring seamless integration with production systems.
• Work on large-scale data processing using frameworks such as Spark, Hadoop, or distributed ML libraries.
• Monitor, maintain, and improve deployed models through MLOps best practices(CI/CD, monitoring, retraining).
• Stay up to date with the latest developments in AI/ML research and toolsand apply them to solve real-world problems.

Requirements:

• Strong programming skills in Python(knowledge of Java/Scala/C++ is a plus).
• Expertise in machine learning frameworks(TensorFlow, PyTorch, Scikit-learn, XGBoost, etc. ).
• Solid understanding of statistics, probability, and linear algebra.
• Hands-on experience with data preprocessing, feature engineering, and model deployment.
• Experience with cloud platforms(AWS, GCP, Azure) and ML services.
• Proficiency in working with SQL and NoSQL databases.
• Knowledge of MLOps tools(MLflow, Kubeflow, Airflow, Docker, Kubernetes).

Skills

Kubeflow, MLOps, MLflow, PyTorch, Python, Scikit-learn, TensorFlow, XGBoost