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Tech Stack
Tools & technologiesAWSAzureCloudDockerGoogle Cloud PlatformPythonPyTorchScikit-LearnTensorflow
About the role
Key responsibilities & impact- Lead the design, development, and deployment of ML/AI solutions
- Architect end-to-end ML systems and set technical direction
- Mentor junior engineers and analysts
- Drive best practices in MLOps and ML infrastructure
- Define and implement efficient ML workflows
Requirements
What you’ll need- Expert in Python
- Strong experience with PyTorch, TensorFlow, and scikit-learn
- Deep understanding of model training, evaluation, inference, and optimization
- Proven experience building AI agents and automated workflows
- Strong experience designing REST APIs and deploying/serving ML models in production
- Solid experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker)
Benefits
Comp & perks- Health insurance
- Retirement plans
- Professional development
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonPyTorchTensorFlowscikit-learnmodel trainingmodel evaluationmodel inferencemodel optimizationREST APIsMLOps
Soft Skills
mentoringleadershipbest practices
