Founding Engineer, Backend & ML Systems

About Soobu
Soobu is an AI-powered fashion search and discovery platform. We're building the systems behind search, personalized feeds, and product intelligence, the infrastructure that lets people find and engage with fashion in a way that's genuinely tailored to them.

We're in closed beta, building toward public launch. This is a ground-floor engineering hire that builds the infrastructure that makes that experience possible.

About the Role
We're hiring our Founding Engineer to build and own the backend and production ML infrastructure behind Soobu. This role starts part-time and equity-only, and converts to full-time with salary once our seed round closes. You'll work directly with the founder and our AI/ML lead, to ship the systems that power search, personalized recommendations, and visual discovery, and to get models into production reliably without building infrastructure we don't need yet.

This is a high-ownership seat spanning backend and MLOps: you'll write the APIs and data pipelines, and you'll own the full lifecycle of getting models into production (deployment, versioning, monitoring, evaluation, and retraining) as a real discipline, not an afterthought bolted onto backend work.

What You'll Do

• Own the backend architecture powering the core product: APIs, databases, auth, and services.
• Build the data pipelines behind search, ranking, and recommendations, including user events, content/brand indexing, and feature generation.
• Own MLOps end to end: take models our ML lead builds and turn them into reliable production systems, including deployment, versioning, monitoring, evaluation, and automated retraining.
• Optimize model inference for latency, throughput, reliability, and cost.
• Build real observability across backend and ML systems, including logging, metrics, and alerting, of the kind that lets you catch model drift or degraded performance before it's a problem.
• Make the early architecture and tooling calls (including which MLOps stack to standardize on) that the rest of engineering will build on.
• Help define engineering practice (CI/CD, testing, security) as the team grows past this seat.

What We're Looking For
8–10+ years building production backend systems, including experience leading technical decisions.

• Strong with Python and NodeJS/ Typescript, and at least one of Go/Java/similar.
• Experience designing APIs and services that need to hold up as usage and data grow.
• Hands-on with cloud platforms (AWS, GCP, or Azure) and container orchestration (Docker, Kubernetes), Helm Charts and Terraform
• Hands-on experience with MLOps tooling such as MLflow, Kubeflow, SageMaker, Vertex AI, or equivalent. You've actually run one of these, not just read about it.
• Familiarity with model-serving frameworks (vLLM, Triton, Ray Serve, BentoML, or similar) and ML/LLM hosted services like Open AI, Gemini and Anthropic APIs
• Solid grounding in data engineering and event/streaming pipelines.
• Experience with recommendation systems, vector search, or visual/image search, this is core to what Soobu is built on, not a peripheral skill.
• Knowledge of GPU infrastructure and inference optimization.
• Genuinely comfortable with ambiguity and being the first backend/infrastructure engineer on a small team. You'll make calls with incomplete information and revisit them as we learn. Ie willing to experiment and fail sometimes.

Nice to Have

• Experience deploying and scaling LLMs or other generative AI systems.
• Previous founding/early engineer experience.
• Interest or background in fashion, retail, or consumer marketplaces.