Senior Applied ML Engineer
Tasks
- Design and build user facing ML features with LLMs and generative AI
- Establish best practices for prompt design, model evaluation, and experimentation
- Implement scalable services and APIs for model outputs
- Integrate ML deployments with safety fairness and performance requirements
- Own technical architecture for applied ML systems
- Prototype and deliver ML powered experiences
Perks/Benefits
- 401k match
- Annual wellness allowance
- Disability coverage
- Employee assistance program
- Employee resource groups
- Employee stock purchase plan
- Health insurance (medical, dental, vision)
- Health savings account
- Life insurance
- Paid family and parental leave
- Paid time off
- Productivity allowance
- Remote work flexibility
- Sick leave
- Wellness allowance
Skills/Tech-stack
API Development | Docker | Experimentation | Faiss | FastAPI | Flask | Generative AI | Kubernetes | Langchain | Language Models | Large Language Models | Latency optimization | Llamaindex | Model Evaluation | Observability | OpenAI API | Pinecone | Prompt engineering | Python | Real Time | Real-time Inference | Retrieval-Augmented Generation | System design | Terraform | Vector Search
Education
N/A
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