AI/ML Engineer
Tasks
- Build and deploy containerized applications with Docker and Kubernetes
- Build and maintain frontend and backend web application features
- Build retrieval-augmented generation pipelines
- Collaborate on architecture decisions and iterative delivery
- Design and develop agentic AI systems
- Develop RESTful APIs and database queries
- Develop and integrate AI ML capabilities into web applications
- Document technical designs and operational procedures
- Implement data ingestion embedding vector search and model serving pipelines
- Integrate SAST into the development pipeline
- Maintain CI CD pipelines for testing security scanning and deployment
- Maintain infrastructure as code and deployment automation
- Participate in code reviews and sprint planning
- Perform prompt engineering model evaluation and performance tuning
- Prototype emerging AI ML tools frameworks and techniques
- Support demos briefings and technical reviews
- Write testable documented code and follow design patterns
Perks/Benefits
- 401k match
- Dental insurance
- Flexible spending accounts
- Health insurance
- Paid Holidays
- Paid time off
- Vision insurance
Skills/Tech-stack
AWS | Azure DevOps | CI/CD | Docker | Embeddings | FastAPI | Git | GitHub Actions | GitLab CI | GitLab CI/CD | Google Cloud | Infrastructure as Code | JavaScript | Jenkins | Kubernetes | Language Models | Large Language Models | Microsoft Azure | MySQL | NLP | PostgreSQL | Python | RAG | REST APIs | React | SAST | SQL | SQL Server | TypeScript | Vector Search | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Bachelor of Science in Artificial Intelligence | Bachelor of Science in Computer Science | Bachelor of Science in Data Science
Roles
AI | AI/ML Engineer | Engineer | ML Engineer | Software Engineer
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