Engineer, AI/ML
Tasks
- Apply data privacy controls and access management
- Build CI CD pipelines for model and agent deployment
- Define data contracts and schema standards for AI readiness
- Deploy AI and agent workloads to AWS
- Design and build AI agents and multi agent systems
- Develop agentic workflows for business process automation
- Develop fine tune and evaluate machine learning models
- Document agent architectures and model cards for governance
- Implement logging observability and alerting
- Monitor production AI systems for drift and anomalies
- Perform incident response and root cause analysis
Perks/Benefits
- 401k match
- Dental and vision plans
- Employee assistance program
- Employee cruise discounts
- Employee stock purchase plan
- Health benefits
- Learning and development resources
- On-site fitness center
- Paid time off
- Sick time
- Tuition reimbursement
Skills/Tech-stack
AWS SageMaker | Agent systems | Agentic Workflow | Alerting | Amazon Bedrock | Amazon ECS | Amazon S3 | Autogen | Automl | CI/CD | Container Orchestration | Cortex AI | CrewAI | Docker | Drift monitoring | Experiment tracking | LLM orchestration | Langchain | Langgraph | Language Models | Large Language Models | Logging | MLOps | Machine Learning | Model Drift | Model Evaluation | Model drift monitoring | Model versioning | Multi-Agent | Multi-Agent Systems | Observability | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | Snowflake Cortex | Snowflake Cortex AI | Snowflake ML
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI/ML Engineer | Engineer | ML Engineer
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