You'll work with Python, NumPy, SciPy, Pandas, PyTorch, JAX, and deep learning frameworks to build models using operator learning, geometric deep learning, or generative models. PhysicsX is building an AI-driven simulation software stack for multi-physics engineering and manufacturing across aerospace, energy, and other advanced industries.

Robinhood★3.4 (73)· London

Design and build backend services (transfers, settlement, account state) using AWS cloud infrastructure, focused on correctness and scalability. The Custody Services team secures digital assets and operates the full custody lifecycle at Robinhood, a financial-technology company.

Lovable★4.0 (43)· London

As the first data scientist in Lovable's new London growth team, you'll own the growth funnel end-to-end and work directly with growth engineers to ship experiments. You'll use SQL, Python, BigQuery, PubSub, Hex, and A/B testing on GCP, building the metrics and systems that drive acquisition, activation, retention, and expansion.

You'll work with Python, SQL, Snowflake, and dbt to transform and model data, build data workflows, and automate processes. The role sits on the Python Infrastructure team at Lendable, a fintech company rebuilding consumer finance products like loans, credit cards, and car finance.

Work with Snowflake, dbt, Python, and SQL to transform and model data, build data workflows, and automate processes. You’ll join the Python Infrastructure team at Lendable, a fintech building credit and savings products.

You'll work with Python, SQL, Snowflake, and dbt to transform and model data, build data workflows, and automate processes. This role sits on the Python Infrastructure team at Lendable, a fintech building technology to help people get credit and save money.

Wise★3.5 (42)· London

You will work with Java, Spring Boot, AWS, Apache Kafka, and potentially Trino. The Pricing Core team builds and maintains the main pricing platform that enables Wise to price its products, processing over 100 million requests daily across critical paths.

JPMorgan★3.9 (20k)· London

Work with KDB, Q, AWS, and optionally Terraform, Kubernetes, Python, C, C++, or Java. Develop and maintain applications storing large Options data sets for real-time and historical access within JPMorgan’s Equities Trading Data & Analytics team, migrating to AWS and re-architecting systems.

You will work with PyTorch, TensorFlow, deep learning models, recommendation and retrieval systems, and MLOps practices on cloud infrastructure. Joining ASOS’s Outfits Discovery team, you will build and operate large-scale production ML systems that power personalised outfit recommendations and AI-driven fashion discovery for millions of customers.

Design and build scalable data pipelines using Python, Scala, Spark, PySpark, Azure Data Factory, Databricks, and Delta Lake. You’ll develop reusable platform components and templates that enable data scientists and engineers across product teams (Forecasting, Recommendations, Marketing, etc.) to deliver high-quality, production-ready data solutions.

You will use deep learning frameworks, distributed computing technologies, GPU-based training environments, and MLOps practices to build and deploy batch and real-time recommendation, ranking, and personalisation models. This role is within ASOS's Search & Recommendations team, which builds the machine learning systems that help millions of customers discover products daily.

Develop novel ML architectures including GNNs and foundation models using PyTorch or JAX. You will drive the core discovery engine of an autonomous laboratory, bridging simulation and real-world physical experiments for materials innovation.

Generative AI, autonomous agents, and real-time rebalancing systems optimize paid acquisition across TikTok, Meta, and Snap. You will build a systematic marketing engine for EQUALS, a London-based music social network with 1 million monthly active users.

Post-train, fine-tune, and distil frontier language models using RL, distillation, and reward design in Python. Build production-grade simulation systems that model thousands of individuals in real-time for a Societal World Model at a YC-backed startup.

You’ll work with Python, FastAPI, TypeScript, React, and GCP. Electric Twin builds a behavioral simulation platform that creates “digital twins” of real populations, helping organizations test decisions with 95% accuracy.

Work with .NET, TypeScript, React, AWS, and CI/CD pipelines. Lead a small engineering team for a UK tech consultancy, owning technical delivery and architecture on client projects. Act as the technical face of projects from day one.

You'll work with Python (FastAPI/Django), Svelte/TypeScript, and AWS to build features across a payments and discovery platform. Tab is a YC-backed travel fintech enabling 100,000+ global tourism businesses to accept payments in 100+ currencies.