Primary Location: London · Canary Wharf HQ (on-site). We plan to open a US office in the next ~6 months and will sponsor transfer visa for team members open to relocation.

Plexe is building AI agents that turn simple plain-English prompts into full production ML applications, including data pipelines, models, and more. We're backed by Y Combinator (X25) and were named one of the spring batch's "Top-10 AI agent startups" by Business Insider.

We're looking for an ML engineer with deep experience in feature engineering, model development, and MLOps. You'll develop multi-agent systems, optimise distributed model training, and create AI agents that autonomously handle the entire ML development lifecycle.

Responsibilities

•\tProduct Development: build distributed ML infra, multi-agent systems, observability, client-facing APIs, and more - eventually owning your own product or product lines.

•\tTechnical Leadership: drive technical decisions and architecture design, helping shape the foundations of our platform.

•\tCross-Functional Collaboration: work closely with co-founders to translate business vision and customer feedback into actionable engineering plans.

•\tOwnership: take full product ownership from ideation to launch, including integration into existing systems. Your roadmap is one quick chat away from reality.

Qualifications

We don't have strict "formal" requirements - we just want to see you're awesome and up for the challenge! That might look like this:

Must-Have:

•\t3+ yrs building ML/AI systems that served real users.

•\tStrong Python; comfort with AWS, Docker, Terraform/CDK, Postgres, etc.

•\tSolid grounding in ML algorithms, MLOps, and data science workflows.

•\tExperience with Spark, TensorFlow, Kafka, or similar tools.

•\tExperience with SageMaker, KServe, Triton, or similar infra.

Nice-to-Have:

•\tBuilt agentic workflows / LLM tool-use.

•\tExperience with MLFlow, WandB, LangFuse, or other MLOps tools.

•\tExperience with React, FastAPI, or other common web frameworks.

Why Plexe?

•\tHard problems: we're automating the entire ML/AI lifecycle from data engineering to insights.

•\tHigh ownership: first 5 engineers write the culture as well as the code. You have the power to fix whatever issue you can point at.

•\tExciting environment: work at a fast-paced YC-backed startup with one foot in Silicon Valley.

•\tLocation and compensation: sweet office in central Canary Wharf; equity that can matter.

Compensation

£85,000 - £110,000 base salary, 0.25%-0.75% equity, eligibility for further bonuses based on company and/or individual performance.