Key Responsibilities

• AI Infrastructure

• Deploy and serve LLMs (OpenAI, Anthropic, HuggingFace, fine-tuned models)

• Optimize inference latency and costs

• Implement caching, rate limiting, and retry strategies

• MLOps & Pipelines

• Version models, prompts, datasets, and evaluation results

• Implement experiment tracking (Weights & Biases)

• Build CI/CD pipelines for model deployment

• Monitor model performance and drift

• Set up logging and observability for AI services

• API Development

• Design and implement APIs (FastAPI)

• Create endpoints for prompt testing, model selection, and evaluation

• Integrate AI services with backend application

• Ensure API reliability, security, and performance

• Collaboration & Enablement

• Work with AI Developers to productionize their experiments regarding improving user workflows

• Define workflows: notebook/test repository → PR → staging → production

• Document AI infrastructure and best practices

• Review code and mentor AI developers on software practices

Required Skills & Experience Must-Have

• 7+ years of software engineering experience (Python preferred)
• Experience with LLMs and AI/ML in production: OpenAI API, HuggingFace, LangChain, or similar
• Understanding of vector databases (Pinecone, Chroma, Weaviate, FAISS)
• Cloud infrastructure experience: GCP (Vertex AI preferred) or AWS (SageMaker)
• API development: FastAPI, REST, async programming
• CI/CD and DevOps: Docker, Terraform, GitHub Actions
• Monitoring and observability
• Problem-solving mindset: comfortable debugging complex distributed systems
• Operating experience with AI deployment in enterprise environment

Nice-to-Have

• Experience fine-tuning or training models
• Familiarity with LangChain, Pydantic AI or similar frameworks
• Knowledge of prompt engineering and evaluation techniques
• Experience with real-time inference and streaming responses
• Background in data engineering or ML engineering
• Understanding of RAG architectures
• Contributions to open-source AI/ML projects

Tech Stack Current Stack:

• Languages: Python (primary), Bash
• AI/ML: OpenAI API, Anthropic, HuggingFace, LangChain, Pydantic AI
• Vector DBs: Pinecone, Chroma, Weaviate, or FAISS
• Backend: FastAPI, SQLAlchemy, Pydantic
• Cloud: GCP (Vertex AI, Cloud Run), Terraform
• CI/CD: GitHub Actions
• Experiment Tracking: MLflow, Weights & Biases, or custom
• Containers: Docker, Kubernetes (optional)

What we offer: Competitive compensation

• Stock Options Plan: Empowering you to share in our success and growth.
• Cutting-Edge Tools: Access to state-of-the-art tools and collaborative opportunities with leading experts in artificial intelligence, physics, hardware and electronic design automation.
• Work-Life Balance: Flexible work arrangements in one of our offices with potential options for remote work.
• Professional Growth: Opportunities to attend industry conferences, present research findings, and engage with the global AI research community.
• Impact-Driven Culture: Join a passionate team focused on solving some of the most challenging problems at the intersection of AI and hardware.