About
Orbis is partnered with a fast-growing e-commerce client that is scaling its Machine Learning function, with plans to expand the team by four engineers before the end of Q2. This is a key opportunity to join a product-led business where machine learning plays a central role in shaping user experience, driving personalisation, and supporting the company's broader growth vision.
The Role
This role sits within a high-impact ML engineering group focused on three core pillars: Personalisation
- delivering tailored, data-driven user experiences Generative AI
- including LLMs and Agentic AI development Trust & Safety
- fraud prevention, impersonation detection, and securing the user environment The successful candidate will be involved in the end-to-end lifecycle of machine learning systems - from architecture and model development to deployment and real-time performance optimisation.
Key Requirements
4-10+ years of experience in machine learning, data, or platform engineering Proven experience deploying production-grade ML systems (e.g. real-time inference, recommendations, or model training pipelines) Proficiency in Python, Go, or Java Cloud experience with one or more platforms: AWS, GCP, Azure Familiarity with infrastructure and orchestration tools: Kubernetes, Terraform, Airflow, Databricks, Feast, Tecton, Ray, or Kubeflow Bonus: experience with LLMs, RAG pipelines, CLIP embeddings, or real-time/streaming systems (Kafka, Flink, Spark) What's on Offer
12-month contract with high potential for extension or permanent conversion Competitive daily rate and hybrid working model in New York City The opportunity to make a direct impact on the business across multiple high-priority domains
Please note: this role does not offer sponsorship and is not open to third parties.
Apply now if you're interested in being part of a cutting-edge ML team within a product-first e-commerce environment.
Languages
- English
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