Machine Learning Engineer

Roles & Responsibilities:

• Design, develop, and deploy machine learning models for real-world business problems
• Work on data preprocessing, feature engineering, model training, evaluation, and optimization
• Build and maintain end-to-end ML pipelines (training, inference, monitoring)
• Collaborate with product, data engineering, and backend teams to integrate ML solutions into production
• Apply appropriate ML/DL algorithms (regression, classification, NLP, CV, recommendation, etc.) based on use cases
• Optimize models for performance, scalability, and latency
• Implement model monitoring, retraining, and versioning
• Stay updated with latest advancements in AI/ML research and tools
• Participate in code reviews, design discussions, and technical documentation

Preferred Candidate Profile:

• 3 to 7 years of hands-on experience in Machine Learning / Applied AI roles
• Strong foundation in statistics, linear algebra, probability, and algorithms
• Proficiency in Python and ML libraries such as NumPy, Pandas, Scikit-learn, TensorFlow / PyTorch
• Experience with SQL and working with large datasets
• Practical exposure to model deployment (APIs, batch/real-time inference)
• Familiarity with MLOps tools (Docker, MLflow, Airflow, Kubernetes, CI/CD) is a strong plus
• Experience with cloud platforms (AWS / GCP / Azure)
• Knowledge of at least one specialization:
• NLP
• Computer Vision
• Recommendation Systems
• Time-series forecasting
• Strong problem-solving and communication skills
• Ability to work independently and mentor junior engineers (especially for 57 yrs profiles)