Lead AI Engineer
Tasks
- Administer AI infrastructure for model serving
- Build and train custom large language models
- Build data pipelines for AI projects
- Create CI quality gates
- Define evaluation metrics and test sets
- Fine tune and align machine learning models
- Implement cost control for AI workloads
- Implement retrieval and agent frameworks
- Integrate AI models into codebases via APIs
- Manage vector stores and feature stores
- Mentor delivery team engineers
- Run model evaluation harness
- Select model tuning approaches for projects
- Set up orchestration and autoscaling
- Support AI governance with model cards and lineage
- Track data lineage
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | AWS Bedrock | Amazon SageMaker | Arize Phoenix | Azure | CI/CD | DPO | Data Lineage | Databricks | Deep learning | DeepEval | Docker | Feature Stores | Fine Tuning | GCP | GPU infrastructure | Go | Inference Server | Infrastructure as Code | Instruction Tuning | Kubernetes | Langfuse | Language Models | Large Language Models | LoRA | Machine Learning | OpenAI evals | Promptfoo | PyTorch | Python | QLoRA | RAG | RLHF | Ragas | Ray Serve | Retrieval-Augmented Generation | Rust | Snowflake | TGI | Triton Inference | Triton Inference Server | TypeScript | VLLM | Vector Stores | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI Engineer | Engineer | Lead | Lead AI Engineer | Learning Engineer | Machine Learning Engineer
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