Working Mode : Hybrid

Domain Preference : Preferably candidates with experience in the Healthcare domain (Otherwise do not reply or apply).

Key Skills & Requirements :

- GenAI, ML and production-grade ML pipelines

- CI/CD, Git, Docker, Jenkins and scripting languages

- Cloud platforms - AWS / GCP / Azure

- Kubernetes and Kafka

- Python with TensorFlow, Keras or PyTorch

- Cloud build, deployment and orchestration tools

- MLOps tools such as MLflow, Kubeflow, Weights & Biases, AWS SageMaker, Vertex AI, DVC, Airflow, Prefect, etc.

- Statistical modeling, machine learning, data mining and unstructured data analytics

- Strong understanding of ML lifecycle and MLOps

- Hands-on experience in productionizing ML models

- Experience with data engineering pipelines

- Third-party integration experience is an added advantage

- Ability to work independently and collaboratively with cross-functional teams, architects and stakeholders across geographies

- Comfortable with both low-level technical implementation and high-level architecture evolution

Please share these details with your CV :

- Rel Exp as AI/ML Architect :

- Rel Exp in Python (TensorFlow, Keras or PyTorch) :

- Rel Exp in Kubernetes :

- Rel Exp in Kafka :

- Rel Exp in Cloud platforms :

- Rel Exp in MLOps tools :

- Rel Exp in ML lifecycle and MLOps :

- Rel Exp in data engineering pipelines :

- Rel Exp in Third-party integration :

- Rel Exp in productionizing ML models :

- Rel Exp in Health care Domain :

- Current Loc :

- Pref Loc :

The job is for:

May work from home