Middle AI/ML Engineer
Tasks
- Build RAG systems
- Build agent workflows
- Build and optimize machine learning models
- Collaborate with DevOps data engineering and solutions architects
- Conduct code reviews
- Create LLM application features
- Create technical documentation and presentations
- Deploy and monitor models
- Design machine learning pipelines
- Mentor junior engineers
- Monitor agent performance and costs
- Prevent model drift
- Propose reusable ML accelerators
- Stay current with machine learning research
- Write tested modular Python code
Perks/Benefits
Skills/Tech-stack
API Gateway | AWS ECR | AWS ECS | AWS Lambda | AWS S3 | AWS SageMaker | Agent Orchestration | Amazon Bedrock | Bedrock AgentCore | Bedrock Agents | CI/CD | Chroma | CloudFormation | Computer Vision | CrewAI | Deep learning | Docker | Drift Detection | Faiss | Generative AI | Infrastructure as Code | Kubernetes | LLM | MCP | MLOps | MLflow | Machine Learning | Model Context Protocol | Model Drift | Model Drift Detection | Model Monitoring | NLP | NumPy | OpenSearch | Pandas | Pinecone | Prompt engineering | Prompt evaluation | Python | RAG | SQL | Supervised Learning | Terraform | Time Series | Transformers | Unsupervised Learning | Vector Databases | Weights and Biases | “as-code”
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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