Senior AI/ML Engineer
Tasks
- Automate data and model pipelines
- Build deploy and scale machine learning systems
- Build reusable AI platform components
- Create evaluation and monitoring pipelines
- Design generative AI platforms
- Develop Vector Search capabilities
- Establish engineering standards and best practices
- Implement guardrails and compliance controls
- Implement rag pipelines
- Mentor engineers and lead architecture reviews
- Optimize cost latency and scalability
- Orchestrate LLM agents
- Set up model training and serving infrastructure
Perks/Benefits
- 401k
- Commuter benefits
- Employee referral program
- Fertility care benefits
- Free testing
- Medical, Dental, Vision, Life, & Disability insurance
- Pregnancy and baby bonding leave
Skills/Tech-stack
AWS | Access Controls | Agent Orchestration | Audit trails | CI/CD | Caching | CrewAI | Datadog | Drift Detection | Embeddings | Encryption | Experimentation | Feature Store | Fine Tuning | Guardrails | Hybrid search | Kubeflow | Kubernetes | LLM | LLMOps | Langchain | Llamaindex | MLflow | Observability | Policy-as-Code | Prompt engineering | PyTorch | Python | RAG | Rate Governance | Retrieval-Augmented Generation | Semantic Kernel | Semantic Search | Spark | TensorFlow | Terraform | Token Rate Governance | Vector Database | Vector Search | “as-code”
Education
N/A
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