AI Engineer

AI Engineer

The platform for AI will not be your phone or computer. It will be intelligent ambient devices that can understand YOU. Come be a part of a trillion dollar market that is being born as we speak. Don’t just build models and agents — build the future of AI computing. As an AI Engineer, you will design and build the intelligence layer that powers real-time, context-aware interactions directly with consumers. You will transform models into adaptive, reliable, social and deeply personalized systems that operate seamlessly in everyday life. You will be working with luminaries in the field and have autonomy to drive AI features and shape how humans will interact with computing and each other. This is not a research-only role. You will be on the ground floor of taking ideas from concept → production → learning from real time data.

What You’ll Do

Build AI Systems That Actually Work

• Design and implement LLM-powered systems for real-time interaction
• Develop agentic workflows with memory, context retention, and decision-making
• Build systems that feel responsive, natural, and human-centered
• Fine-tune or train models as needed

Retrieval, Memory, and Personalization

• Architect and optimize RAG pipelines
• Design layered persistent memory systems (user context, history, preferences, relationships)
• Improve relevance, grounding, and personalization over time

Real-Time Inference & Performance

• Build low-latency inference systems for conversational AI
• Optimize model serving (streaming, batching, caching, quantization)
• Balance latency, cost, and quality across deployments

Evaluation, Iteration, AI Safety

• Develop structured strategies and evaluation frameworks
• Build tooling for automated evaluation, regression testing, and quality monitoring
• Continuously improve system behavior through data and feedback loops

AI Infrastructure & Deployment

• Contribute to ML infrastructure and deployment pipelines
• Implement CI/CD for models (validation, rollout, rollback)
• Work with backend and applied engineers to integrate AI into production systems

Cross-Functional Collaboration

• Partner with product, design, and engineering to define AI behaviors and UX
• Translate ambiguous product needs into clear system logic
• Help define what “great AI interaction” actually feels like

What You Bring

Core AI / ML Experience

• 3–8+ years working with production ML or LLM-based systems
• Hands-on experience building agentic systems
• Experience deploying and iterating on real-world LLM applications
• Experience working with APIs, backend systems, or distributed systems
• Experience designing evaluation loops and benchmarks
• Strong intuition for AI failure modes (hallucination, drift, latency issues)
• Ability to debug both model behavior and system behavior
• Experience with cloud infra for AI, data pipelines, orchestration

Bonus Experience

• Real-time systems (streaming, WebSockets, audio pipelines)
• Multimodal AI (vision, audio, sensors)
• On-device / edge inference optimization
• Consumer product experience (chat, assistants, wearables)
• Fine-tuning, PEFT, or model optimization techniques

What We Offer

• Salary + early equity
• Comprehensive benefits
• Flexible remote or hybrid work

Key skills/competency

• AI Engineer
• LLM Systems
• Agentic Workflows
• RAG Pipelines
• Real-Time Inference
• ML Infrastructure
• AI Safety
• Production ML
• Cloud Infra
• Consumer Products