Key Responsibilities:
Design, develop, and deploy machine learning models and algorithms to solve business challenges.
Collaborate with Data Scientists, Data Engineers, and Product teams to collect requirements, clean datasets, and engineer features.
Perform exploratory data analysis and identify key patterns, insights, and trends from structured and unstructured data.
Build scalable and efficient ML pipelines for training, testing, and deploying models into production environments.
Evaluate and improve the performance of existing machine learning models.
Research and implement state-of-the-art machine learning and deep learning techniques.
Work on real-time ML applications including recommendation systems, natural language processing, computer vision, anomaly detection, and predictive analytics.
Monitor, maintain, and optimize deployed models to ensure high availability and accuracy over time.
Document processes, workflows, and methodologies for internal knowledge sharing and future reference.
Mentor junior team members and provide technical leadership on ML initiatives.
Key Skills & Qualifications:
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Mathematics, or a related field.
5+ years of hands-on experience in Machine Learning / Artificial Intelligence.
Proficient in programming languages such as Python (preferred), R, or Java.
Strong understanding of machine learning algorithms: supervised, unsupervised, reinforcement learning, deep learning, etc.
Experience with ML/DL frameworks and libraries: TensorFlow, PyTorch, Keras, Scikit-learn, XGBoost, etc.
Solid knowledge of data preprocessing, feature engineering, and model evaluation techniques.
Familiarity with NLP, Computer Vision, or Recommendation Systems (based on project requirements).
Experience with cloud platforms such as AWS, Azure, or GCP, and tools like SageMaker, MLFlow, or Kubeflow.
Understanding of MLOps practices and experience deploying models into production environments.
Proficiency with data querying languages (SQL) and big data tools (Spark, Hadoop) is a plus.
Excellent problem-solving skills and the ability to work independently or in a team.
