Full stack engineer

About Us
We’re a fast-growing AI-focused product studio building real-time ML-powered experiences for developers and enterprises. Our team combines research-grade ML, pragmatic engineering, and product design to ship features that scale to millions of users. We move fast, value ownership, and ship quality.

Role Overview
We’re hiring a pragmatic Full Stack Developer to build and maintain backend services (FastAPI) and responsive frontends that deliver ML/AI capabilities. You’ll work closely with ML engineers to productionize models, design APIs, and implement UI/UX flows that let users interact with AI systems safely and reliably.

What you’ll do

• Design, implement, and maintain REST/GraphQL APIs using FastAPI for AI/ML model serving and orchestration.
• Collaborate with ML engineers to containerize and deploy models (Docker, Kubernetes), implement model versioning and A/B testing.
• Build and maintain frontend applications (React/Next.js or Vue) with clean, accessible UI and strong client-server integration.
• Implement authentication, role-based access control, and secure data handling (OAuth2/JWT, encryption, data masking).
• Optimize API performance and reliability (async endpoints, caching, batching, rate limiting).
• Create observability for ML services (metrics, tracing, structured logs, alerts).
• Lead code reviews, contribute to architecture decisions, and mentor junior engineers.
• Write automated tests and CI/CD pipelines for both backend and frontend components.

Must-have qualifications

• 3+ years professional experience in full stack development.
• Strong experience building APIs with FastAPI (or comparable ASGI frameworks) and async Python.
• Proficiency with Python data/ML ecosystem basics (pydantic, uvicorn, model serialization formats like ONNX/Pickle/torchscript).
• Frontend expertise with React and ecosystem (hooks, state management, Next.js preferred).
• Production experience with Docker and cloud deployment (AWS, GCP, or DigitalOcean).
• Knowledge of databases: PostgreSQL and a NoSQL option (Redis/MongoDB).
• Solid understanding of REST/GraphQL, WebSockets, and authentication patterns (OAuth2/JWT).
• Familiarity with CI/CD tools (GitHub Actions, GitLab CI, or equivalent).
• Strong engineering fundamentals, code quality practices, and testing mindset.

Nice-to-have

• Experience working with ML lifecycle tools (MLflow, Triton, Seldon, BentoML).
• Familiarity with Kubernetes and helm charts for production deployments.
• Experience with streaming / real-time pipelines (Kafka, Redis streams).
• Background building developer platforms, SDKs, or public APIs.
• Knowledge of LLMs, prompt engineering, and safety mitigations.

What we offer

• Competitive salary and equity component.
• Flexible work hours and hybrid/remote options.
• Learning stipend & conference budget to stay current in AI.
• Modern engineering stack, ownership of features from prototype to production.
• Supportive team culture with regular knowledge-sharing sessions.