Machine Learning Engineer

Job Title:

Location:

Employment Type:

About the Role

Machine Learning Engineer

Key Responsibilities

• Design, develop, train, and deploy machine learning models and pipelines.
• Work with large datasets to build predictive and recommendation systems.
• Collaborate with Data Scientists to productionize ML models.
• Optimize models for performance, scalability, and reliability.
• Build end-to-end ML pipelines including data preprocessing, training, evaluation, and monitoring.
• Deploy models using APIs and integrate them into production systems.
• Monitor model performance, drift, and retraining needs.
• Document ML workflows, experiments, and system designs.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.
• 2–5 years of experience in machine learning or applied AI roles.
• Strong proficiency in Python and ML libraries (Scikit-learn, TensorFlow, PyTorch).
• Solid understanding of machine learning algorithms, statistics, and data modeling.
• Experience with data processing tools and frameworks (Pandas, NumPy, Spark).
• Familiarity with deploying ML models using REST APIs or microservices.
• Experience with cloud platforms (AWS, Azure, or GCP).
• Knowledge of version control (Git) and MLOps fundamentals.

Preferred / Good-to-Have

• Experience with MLOps tools (MLflow, Kubeflow, Airflow).
• Knowledge of deep learning, NLP, or computer vision.
• Exposure to containerization tools like Docker and Kubernetes.
• Understanding of data pipelines and big data systems.
• Experience working in Agile development environments.

Why Join Us

• Work on impactful AI and ML projects at scale.
• Collaborate with experienced data and engineering teams.
• Opportunity to deploy real-world ML solutions end-to-end.
• Competitive compensation with strong learning and career growth opportunities.