Improve customer and business outcomes through automated decisioning with ML and statistical modelling.
Focus on credit risk modelling, predicting/optimizing utilization, pricing, collection and marketing.
Innovate in data, methodologies, and tooling.
Monzo is on a mission to make money work for everyone, waving goodbye to the complicated ways of traditional banking. They have over 15 million customers and a long history of creating magical moments for their customers; they are not about selling products - they want to solve problems and change lives.
Set product direction using data, strengthen commercial decision-making.
Lead the evolution from analytics to AI and ML-enabled product capability.
Shape product strategy and prioritization, champion the use of data and experimentation.
Monzo is on a mission to make money work for everyone, waving goodbye to the complicated and confusing ways of traditional banking. Monzo is embracing diversity by fostering an inclusive environment for all people to do the best work of their lives.
You’ll own the development and testing of deep learning architectures that define how Tilt understands risk.
You’ll partner with peers in Engineering and Product to ensure our models are effective and scalable in the real world.
You’ll look past the symptoms of a data problem to find the root cause and turn complex findings into clear, actionable solutions for our lending platform.
Tilt is creating a new credit system that backs the working, whatever they're working toward. They have millions of customers worldwide and they are changing how people access financial products. At Tilt, they see a side of people that traditional lenders miss.
Own SentiLink’s real-time ML model monitoring domain.
Own our ML experimentation, model tracking, and versioning infrastructure.
Drive improvements to the model development process.
SentiLink provides identity and risk solutions for secure transactions. They are backed by investors like Craft Ventures and Andreessen Horowitz, recognized by Forbes Fintech 50, and have offices across the U.S. and India.
Build and deploy AI models with RAG and tool calling for various product features.
Collaborate with frontend and backend engineers to bring AI features into production.
Stay updated with the latest AI research and propose innovative applications relevant to Finom’s mission.
Finom is a European tech startup headquartered in Amsterdam, revolutionizing financial services for entrepreneurs. They offer an all-in-one B2B financial solution integrating banking, accounting, financial management, and invoicing into a seamless, mobile-first platform, actively expanding across key EU markets.
Act as the overall technical authority for the programme, owning architectural decisions, execution patterns, and technical quality across all workstreams.
Define and enforce standard migration patterns for moving ML workloads from Databricks into AWS SageMaker, while managing exceptions for complex or legacy cases.
Lead and contribute across areas such as AWS SageMaker-based ML execution, Databricks to SageMaker migration, and Python-based ML workloads.
CreateFuture is a digital consultancy that builds digital products and services. They have over 500 people and a safe, supportive, and friendly culture.
Build and manage the full ML lifecycle—from experiment tracking to model deployment and retraining.
Implement ML-specific CI/CD (e.g., CML, Kubeflow Pipelines) to automate the promotion of models to production.
Architect distributed systems for large-scale model inference.
Deutsche Telekom IT Solutions is a subsidiary of the Deutsche Telekom Group, recognized as Hungary’s most attractive employer in 2025. They provide IT and telecommunications services with more than 5300 employees, serving hundreds of large customers in Germany and other European countries.
Serve as Zencore’s senior-most technical authority on the practical application of advanced artificial intelligence and machine learning.
Partner with the sales and business development teams in a pre-sales capacity to scope opportunities, design solutions for proposals, and act as the senior technical voice in client pitches.
Lead the architecture and design of sophisticated, secure, and scalable AI solutions for our clients, moving beyond standard API integrations to create genuine competitive advantages.
Zencore is a fast-growing company founded by former Google Cloud leaders, architects, and engineers. Our engagements eliminate obstacles, reduce risk, and accelerate timelines for customers adopting and scaling modern AI solutions.
Design and implement tooling that enables researchers to quickly deploy and evaluate new models in production
Design, build, and maintain high-performance, cost-efficient inference pipelines, making architectural decisions about scaling, reliability, and cost trade-offs
Proactively identify and resolve infrastructure bottlenecks, proposing and scoping improvements to iteration speed and production reliability
AssemblyAI builds best-in-class Speech AI models that power the next generation of voice applications. They are a remote team building one of the next great AI companies where teammates define and build their company culture.
Provide strategic direction for the design, deployment, and lifecycle management of ML and AI models across clinical and operational use cases.
Drive advanced analytics initiatives — including predictive modeling, NLP, and population health analytics — that directly inform strategic fundraising, clinical operations, and resource planning.
Recruit, develop, and lead a high-performing team of AI Engineers and Data Scientists within the CDAO and CAIO Offices.
Emory Healthcare is Georgia's most comprehensive academic health system. They are investing in its AI-powered data future and offer ongoing mentorship, development, and leadership programs.
Conduct end-to-end analyses, wrangling data via SQL or Python, to statistical modeling, to hypothesizing and presenting business ideas.
Mentor and guide junior engineers, fostering a culture of learning and technical excellence.
Support the development and deployment of projects involving machine learned models for offline, batch-based data products as well as models deployed to online, real-time services.
Yelp's mission is connecting people with great local businesses, requiring the use of cutting-edge Machine Learning (ML) and Artificial Intelligence (AI). Their engineering culture values individual authenticity and encourages creative solutions, supporting growth in a collaborative environment.
Work with subject matter experts to curate, generate, and annotate data, and create optimal datasets.
Develop and tune Machine Learning models, following best practices to select datasets, architectures, and model parameters.
Write clean, efficient, and modular code, with automated tests and appropriate documentation.
Turnitin partners with educational institutions to promote honesty, consistency, and fairness across all subject areas and assessment types. They are a global organization with team members in over 35 countries that embraces diversity, respects local cultures, and has a remote-centric culture.
Design and implementation of reliable, maintainable, and scalable GenAI systems.
Serve as a subject matter expert for machine learning systems owned by the team.
Mentor junior and mid level engineers through code reviews and design collaboration.
Trajector specializes in medical evidence services, guiding clients through disability benefits complexities. They are a global team of over 1,800 dedicated individuals, streamlining the path to benefits and ensuring access to rightful compensation for those with disabilities.
Build and productionize reusable MLOps components supporting scalable and reliable ML workflows.
Establish strong ML lifecycle practices including experiment tracking, evaluation, and reproducibility.
Enable robust and monitored ML systems aligned with healthcare-grade reliability and compliance requirements.
Neko Health aims to shift healthcare from treating illness to preventing it, using advanced, non‑invasive technology and clinical expertise to deliver early, actionable health insights. The company has nearly 100 full-time engineers and supports a flexible workplace that prioritizes work-life balance.
Partner with stakeholders to tackle technical problems at scale, building framework agnostic services.
Establish roadmap and architecture for Wealthsimple’s Machine Learning platform.
Build highly performant scalable systems, contributing to our ML platform on Kubernetes, Bedrock and Sagemaker.
Wealthsimple aims to provide financial freedom by making financial services transparent and low-cost. As the largest fintech company in Canada, with over 1,500 employees, they manage over $100 billion in assets and foster a collaborative and quality-focused culture.