Job Summary
Position Specific Duties - Develop ML and adjacent features
Design and manage scalable AI/ML workflows and MLOps pipelines on cloud platforms.
Develop, optimize, and monitor data models, infrastructure, and pipelines across environments.
Collaborate with stakeholders to deliver technical solutions, resolve issues, and ensure quality outcomes
Required Skills are- Python, Core ML fundamentals, PyTorch, Computer Vision basics, data basics,
- Strong Python skills with experience in AI/ML platforms and cloud services.
Expertise in distributed computing, Kubernetes, and MLOps with infrastructure-as-code tools.
Good understanding of data engineering, ML pipelines, and strong communication in cross-functional teams
Key Responsibilities
Position Specific Duties - Develop ML and adjacent features
Design and manage scalable AI/ML workflows and MLOps pipelines on cloud platforms.
Develop, optimize, and monitor data models, infrastructure, and pipelines across environments.
Collaborate with stakeholders to deliver technical solutions, resolve issues, and ensure quality outcomes
Required Skills are- Python, Core ML fundamentals, PyTorch, Computer Vision basics, data basics,
- Strong Python skills with experience in AI/ML platforms and cloud services.
Expertise in distributed computing, Kubernetes, and MLOps with infrastructure-as-code tools.
Good understanding of data engineering, ML pipelines, and strong communication in cross-functional teams
Skill Requirements
Position Specific Duties - Develop ML and adjacent features
Design and manage scalable AI/ML workflows and MLOps pipelines on cloud platforms.
Develop, optimize, and monitor data models, infrastructure, and pipelines across environments.
Collaborate with stakeholders to deliver technical solutions, resolve issues, and ensure quality outcomes
Required Skills are- Python, Core ML fundamentals, PyTorch, Computer Vision basics, data basics,
- Strong Python skills with experience in AI/ML platforms and cloud services.
Expertise in distributed computing, Kubernetes, and MLOps with infrastructure-as-code tools.
Good understanding of data engineering, ML pipelines, and strong communication in cross-functional teams