Senior Associate – AI ML Engineer
Tasks
- Apply secure AI development practices
- Build and deploy end to end machine learning applications
- Collaborate with Product, Data Science, and Engineering teams
- Containerize and deploy with Docker and Kubernetes
- Create evaluation pipelines and regression datasets
- Create technical documentation and runbooks
- Design retrieval-augmented generation solutions
- Develop agentic AI workflows with tools and guardrails
- Develop production services with Python and REST APIs
- Implement prompt engineering and structured output validation
- Integrate foundation models and AI services
- Maintain version control and implement CI CD workflows
- Monitor models and prompts in production
Perks/Benefits
Skills/Tech-stack
AWS | Agentic Workflows | Azure | CI/CD | Data Pipelines | Docker | Embeddings | Experiment tracking | Few-Shot Learning | Few-shot | Function Calling | GCP | Generative AI | Git | GitHub | Guardrails | Human-in-the-loop | Integration Testing | JSON | Kubernetes | LLMOps | Language Models | Large Language Models | MLOps | Machine Learning | Model Evaluation | Model Monitoring | NumPy | Observability | Pandas | Prompt engineering | PyTorch | Python | REST APIs | Reranking | Retrieval-Augmented Generation | SQL | Scikit-learn | Structured Output | TensorFlow | The Loop | Tool use | Unit Testing | Vector Databases | Vector Search
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI/ML Engineer | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer
Regions
Countries
States
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