Lead AI/ML Engineer
Tasks
- Build agentic workflows
- Deploy models in secure containerized environments
- Design and implement ML pipelines
- Develop LLM and RAG solutions
- Ensure model reliability and observability
- Establish enterprise AI ML strategy and roadmap
- Fine tune and optimize small language models
- Implement Kubernetes and CI CD workflows
- Lead AI ML architecture and development
- Mentor engineers and set technical best practices
- Train deploy and evaluate models
Perks/Benefits
- 401k match
- Dental insurance
- Education and training benefits
- Health insurance
- Paid Holidays
- Paid time off
- Referral bonuses
- Travel
- Vision insurance
Skills/Tech-stack
APIs | AWS | Agentic Workflows | CI/CD | Containerization | Data Ingestion | Data Streaming | Event Driven | Event-driven architecture | Inference | Kafka | Knowledge Distillation | Kubernetes | Language Models | Large Language Models | MLOps | Machine Learning | Microservices | Model Evaluation | Model Monitoring | PyTorch | Python | Quantization | Retrieval-Augmented Generation | Scikit-learn | Secure Environments | TensorFlow | Testing | Training pipelines | Version control
Education
Roles
AI | AI/ML Engineer | Engineer | Lead | Lead AI/ML Engineer | ML Engineer
Regions
Countries
States
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