Requirements
- Education: Bachelor's in Computer Science, AI, Data Science, or related field
- Experience: 3-5 years in AI/ML model development, with production deployment experience
- Programming: Python (advanced), PyTorch, TensorFlow, Keras, Scikit-learn
- MLOps: Docker, Kubernetes, MLflow, Kubeflow, TF Serving, ONNX
- Cloud Platforms: AWS SageMaker, GCP Vertex AI, Azure ML Studio
- Big Data: Spark, Hadoop, Dask, SQL/NoSQL databases
- Deployment: FastAPI, Flask, REST/gRPC APIs
- Soft Skills: Problem-solving, analytical thinking, teamwork
Responsibilities
- Research, design, and implement machine learning models for NLP, computer vision, predictive analytics, and reinforcement learning
- Develop and optimize deep learning architectures including CNNs, RNNs, Transformers, and GANs
- Work with large datasets across preprocessing, feature extraction, and augmentation
- Deploy ML models into production using containerization, model serving, and monitoring
- Collaborate with data engineers to build scalable ETL and real-time streaming pipelines
- Conduct A/B testing and performance benchmarking of models
- Stay updated with AI research, frameworks, and industry trends
- Mentor junior engineers and contribute to AI strategy planning