AL/ML Engineer

Key Responsibilities:

• Design, develop, and implement machine learning models and algorithms.
• Analyze large datasets to extract actionable insights.
• Build and optimize data pipelines for model training and deployment.
• Deploy ML models into production using appropriate MLOps practices.
• Collaborate with software engineers and domain experts to integrate models into applications.
• Evaluate and improve model performance over time.
• Stay updated with the latest research and techniques in AI/ML.

Required Skills & Qualifications:

• 2–5 years of experience in AI/ML, data science, or a similar role.
• Proficiency in Python and libraries such as scikit-learn, TensorFlow, PyTorch, or XGBoost.
• Strong understanding of supervised, unsupervised, and deep learning techniques.
• Experience with data preprocessing, feature engineering, and model evaluation.
• Solid knowledge of statistics and probability.
• Hands-on experience with model deployment tools (e.g., Flask, FastAPI, Docker).
• Familiarity with cloud platforms (AWS, GCP, Azure) and ML services.
• Experience with SQL and NoSQL databases.

Preferred Qualifications:

• Exposure to NLP, computer vision, or time-series forecasting.
• Experience with MLOps tools like MLflow, Kubeflow, or SageMaker.
• Familiarity with big data tools (e.g., Spark, Hadoop).
• Publications in AI/ML conferences or open-source contributions.