Business Analyst - Data Scientist

End-to-End Pipeline Automation: Build and maintain ML pipelines for computer vision tasks (data ingestion, preprocessing, model training, evaluation, inference). Use tools like MLflow, Kubeflow, DVC, and Airflow to automate workflows.

Model Deployment & Serving: Package and deploy CV models using Docker and orchestration platforms like Kubernetes. Use model-serving frameworks (TensorFlow Serving, TorchServe, Triton Inference Server) to enable real-time and batch inference.

Monitoring & Observability: Set up model monitoring to detect drift, latency spikes, and performance degradation. Integrate custom metrics and dashboards using Prometheus, Grafana, and similar tools.

Model Optimization: Convert and optimize models using ONNX, TensorRT, or OpenVINO for performance and edge deployment. Implement quantization, pruning, and benchmarking pipelines.

Edge AI Enablement (Optional but Valuable): Deploy models on edge devices (e.g., NVIDIA Jetson, Coral, Raspberry Pi) and manage updates and logs remotely.

Collaboration & Support: Partner with Data Scientists to productionize experiments and guide model selection based on deployment constraints. Work with DevOps to integrate ML models into CI/CD pipelines and cloud-native architecture.

Qualifications we seek in you!

Minimum Qualifications: