AI/ML Engineering Manager
Tasks
- Build reference architectures and accelerators
- Conduct end to end ML assessments
- Define ML architecture and technical direction
- Drive pre sales scoping and proposals
- Ensure delivery quality standards
- Govern production ML systems
- Hire and build machine learning team
- Lead end-to-end client engagements
- Lead staffing and engagement alignment
- Manage team performance and milestones
- Mentor engineers and architects
- Provide feedback and support career development
- Run technical assessments for ML roles
- Translate MLOps and LLMOps into standards
- Unblock team on complex technical problems
Perks/Benefits
- 401k plan
- Company laptop
- Dental insurance
- Equipment and office stipend
- Flexible spending account
- Learning and development stipend
- Medical insurance
- Paid Holidays
- Term disability insurance
- Term life insurance
- Unlimited paid time off
- Vision insurance
Skills/Tech-stack
AWS | AWS CDK | AWS CloudFormation | AWS Glue | Agent systems | Agentic Systems | Airflow | Amazon Bedrock | Amazon Kinesis | Amazon SageMaker | Apache Hudi | Apache Iceberg | Apache Kafka | Apache Spark | Artificial Intelligence | CI/CD | DPO | Dagster | Delta Lake | Distributed Training | Docker | Dspy | Fine Tuning | HuggingFace Transformers | Inference Optimization | Infrastructure as Code | JAX | Kubeflow Pipelines | Kubernetes | LLM Evaluation | LLMOps | Langchain | Llamaindex | LoRA | MLOps | MLflow | MWAA | Machine Learning | Model Governance | Multi-Agent | Multi-Agent Systems | Ollama | OpenSearch | PEFT | PGVector | Pinecone | PySpark | PyTorch | Q LoRA | Quantization | RAG | RLHF | Responsible AI | Scikit-learn | TensorFlow | Terraform | Triton | VLLM | Vector Databases | Weaviate | Weights and Biases | XGBoost | “as-code”
Education
N/A
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