Member of Technical Staff (Product Engineer)

Reka

6d•Remote

About The Position

Join us as a Member of Technical Staff (Product Engineer) and help build the next generation of AI-native products. Reka is a multimodal AI research and product company building models that understand video, audio, and text, reason about the world, and take action. In this role, you will take ownership of product outcomes end-to-end—turning ambiguous ideas into working systems that users rely on. You will work across backend systems, product surfaces, and experimentation loops to deliver fast, reliable, and intelligent user experiences. This is a product engineering role. You won’t just implement features—you will define problems, build solutions, and iterate until the outcome is achieved.

Requirements

Experience building production systems (backend or full-stack)
Strong fundamentals in APIs, distributed systems, and system reliability
Comfort working across multiple domains (engineering, product, data, UX)
A track record of owning problems end-to-end, not just executing tasks
Ability to move quickly in a fast-paced, ambiguous environment
Strong communication and cross-functional collaboration skills
A pragmatic, solution-oriented approach to complex problems

Nice To Haves

Video or multimodal pipelines (ingestion, processing, indexing)
Generating embeddings from video/audio/text and building retrieval systems
Search over video (semantic search, timestamped moments, clips)
Metadata extraction (speech, scenes, objects, events)
Streaming and playback systems (e.g., HLS, transcoding, latency tradeoffs)
Evaluating multimodal systems (retrieval quality, relevance, cost/performance)
Haven’t worked on video directly but can reason about these systems

Responsibilities

Build and ship AI-native product features end-to-end
Design and implement backend systems, APIs, and data pipelines that support model-driven workflows
Work across the stack when needed (backend, frontend, infra, experimentation)
Collaborate closely with researchers, designers, and product to bring ideas into production
Own systems from design → implementation → monitoring → iteration
Turn ambiguous goals into concrete scopes, milestones, and shipped outcomes
Move quickly while maintaining a high bar for reliability, performance, and simplicity
Wear many hats and help build something from the ground up
Use AI tools to accelerate coding, debugging, and iteration
Treat AI-generated output as a starting point—validate with tests, reviews, and observability
Design your own workflows to maximize speed without sacrificing correctness
Build systems that themselves leverage AI (agents, retrieval, multimodal reasoning)