AI/ML Engineer

Key Responsibilities:

• Develop, test, and deploy machine learning models and algorithms in production environments.
• Work with large datasets to perform data preprocessing, feature engineering, and model training.
• Build scalable pipelines for model training, validation, deployment, and monitoring.
• Collaborate with software development teams to integrate ML models into applications.
• Optimize model performance through hyperparameter tuning, ensembling, and algorithm selection.
• Stay updated with latest ML research and technologies, recommending adoption where appropriate.
• Mentor junior engineers and participate in code reviews.
• Develop tools for automating model testing and deployment workflows.

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, or related fields.
• 4 to 6 years of professional experience in machine learning or data science roles.
• Proficiency in Python and ML libraries like TensorFlow, PyTorch, Scikit-learn.
• Strong understanding of supervised, unsupervised, and reinforcement learning techniques.
• Experience with deep learning architectures such as CNNs, RNNs, Transformers.
• Hands-on experience with data pipelines, feature engineering, and model deployment.
• Familiarity with cloud platforms like AWS, Azure, or GCP.
• Experience with containerization tools like Docker and orchestration with Kubernetes is a plus.

Strong problem-solving skills and ability to work in a collaborative environment.

Preferred Qualifications:

• Knowledge of NLP, computer vision, or time-series analysis.
• Experience with ML lifecycle management tools (MLflow, Kubeflow).
• Familiarity with big data frameworks (Spark, Hadoop).
• Experience with DevOps/CI-CD pipelines for ML.