Design, build, and iterate on machine learning models and LLM-based systems that power critical decisions across fraud, compliance, growth, and operations
Work with messy, real-world data to identify signals, build features, and continuously improve model performance
Make practical tradeoffs between model performance, interpretability, and operational cost
Develop and iterate on fraud prediction models using a mix of approaches for tabular and behavioral data.
Build and scale feature pipelines and training datasets from proprietary and third-party signals.
Prototype new modeling ideas and features, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls.
Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. They appear to be a remote-first company.
Design and implement scalable ML infrastructure to support model development and deployment
Develop and maintain evaluation frameworks for Large Language Models (LLMs), including RAG-based systems
Evaluate model performance using tools such as RAGAS, DeepEval, or similar frameworks
EX Squared LATAM collaborates with global clients to build innovative digital solutions that drive real business impact. They foster a collaborative, inclusive, and innovation-driven culture where continuous learning and professional growth are at the core of everything they do.
Scope and lead ML initiatives end-to-end from identifying opportunities through production deployment.
Design, develop, and optimize ML models and AI systems for document processing and automation.
Build and maintain production ML pipelines that are robust, observable, and scalable.
Medallion is a healthcare technology company building a provider operations platform to eliminate administrative bottlenecks. They are one of the fastest-growing healthcare technology companies, with a mission to transform healthcare at scale and are backed by $130M in funding.
Expand ML Capabilities – Identify, prototype, and integrate new ML technologies and infrastructure to enhance fraud detection effectiveness and scalability.
Enable High-Velocity Experimentation – Own the design and implementation of ML pipeline components that accelerate our innovation
Collaborate Across Functions – Partner with Product, Engineering, and Risk teams to translate business requirements into technical solutions and ensure ML initiatives align with customer needs.
Signifyd helps merchants confidently grow their businesses by building trusted relationships with their customers. Thousands of leading merchants across more than 100 countries trust them and they securely process billions of transactions each year. Their people are the heart of everything they do, driving their mission forward with commitment, empathy, and creativity.
Contribute to designing, evaluating, and shipping our mental health AI Agent and its supporting infrastructure.
Develop and maintain robust data pipelines to power model training and evaluation.
Partner with AI Research, Product, and Engineering teams to define new features.
Sword Health is shifting healthcare from human-first to AI-first through its AI Care platform. They aim to make world-class healthcare available anytime, anywhere, while significantly reducing costs. Backed by clinical studies and patents, Sword Health has raised more than $500 million from leading investors.
Bring deep expertise in machine learning and applied AI to turn emerging techniques into practical solutions.
Provide broad technical leadership across teams while remaining hands-on in applied research and innovation.
Guide major technical decisions, identify opportunities for differentiation, and translate new ideas into future product capabilities.
Kinaxis is a global leader in modern supply chain orchestration that powers complex global supply chains and supports the people who manage them. They have grown to become a global organization with over 2000 employees around the world, with 6 global offices and a best-in-class HQ in Ottawa, Canada.
Design, prototype and productionize scalable machine learning and optimization models.
Develop frameworks, pipelines, libraries, utilities and tools that process massive data for ML tasks.
Build end-to-end reusable pipelines from data acquisition to model output delivery.
BetterHelp's mission is to remove the traditional barriers to therapy and make mental health care more accessible. Founded in 2013, they are now the world’s largest online therapy service, with over 30,000 licensed therapists.
Design, build, and maintain ML infrastructure across training, evaluation, serving, and monitoring
Own data pipelines including generation, cleaning, validation, and versioning
Build and improve experiment tracking, orchestration, and reproducibility tooling
Quilter is helping electrical engineers save time and accomplish more by automating the tedious and time-consuming task of designing printed circuit boards (PCBs). Their small team is composed of experts in electrical engineering, electromagnetic simulation, ML/AI, and high-performance computing (HPC).
Extend, optimize, and maintain core data models for reports, machine learning, and generative AI.
Implement automation and operationalize ML models to streamline operational processes and improve efficiency.
Partner with engineering, product, and analytics teams to deliver seamless integrations and customer-facing data products.
Boulevard provides a client experience platform for appointment-based, self-care businesses, helping customers enhance client experiences. They value diversity and inclusivity, offering equal opportunities and aiming to create a supportive work environment.
Work with designers and product managers to create high-performing product features.
Apply ML techniques to LLM-based approaches with a strong focus on reliability, performance, and maintainability.
Optro is the leading audit, risk, ESG, and InfoSec platform on the market and has surpassed $300M ARR. They inspire each other to innovate and assist each other to create the most loved platform, which has allowed them to become one of the 500 fastest-growing tech companies in North America.
Lead the design, development, and deployment of production, multi-turn LLM-powered features.
Own backend services in Python that integrate LLM agents with Fullscript’s platform and support reliable production use.
Partner with medical, product, and engineering teams to identify high-value opportunities for AI and turn them into practical, scalable product capabilities.
Fullscript is a health technology company committed to helping people get better by creating a platform that powers every part of care. More than 125,000 practitioners use Fullscript for clinical insights, lab interpretations, patient analytics, education, and access to high-quality supplements.
Define team vision and strategic direction for conversion modeling.
Oversee model development from ideation to deployment.
Recruit, mentor, and retain top ML talent.
Reddit is a platform built on shared interests, passion, and trust, and is home to open and authentic conversations. With 100,000+ active communities and approximately 121 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.
Own and operate machine learning models that run in production, including monitoring, debugging, and iterative improvement.
Develop, train, and optimize models used in a real-time or near-real-time bidding and decisioning system.
Work with stakeholders to clarify ambiguous problems, define success metrics, and translate business needs into technical solutions.
Healthcare.com is a fast-growing insurtech company revolutionizing how consumers shop for health insurance. They leverage advanced technology and data science, developing customized proprietary products to better fit consumer requirements and enhance customer satisfaction.
Improve customer and business outcomes through better automated decisioning, using Machine Learning and statistical modelling.
Drive innovations by identifying new opportunities of data and ML applications, and delivering business values across multiple Borrowing products.
Champion the quality and efficiency of model development, and ensure safe and scalable growth of their model portfolio.
Monzo is on a mission to make money work for everyone. They're waving goodbye to the complicated and confusing ways of traditional banking and want to solve problems and change lives through Monzo. The company cares deeply about their 15+ million customers.
Build scalable, production-grade LLM services and agentic workflows, alongside traditional ML systems where appropriate.
Hiflylabs is a team of 250+ data and tech enthusiasts based in Budapest. They focus on data engineering, data science, artificial intelligence and application development, working on a wide range of projects around the world. Hiflylabs values its people and is committed to nurturing their personal and professional development through a mentoring system.
Build and ship customer‑facing AI, combining Generative AI with machine‑learning techniques.
Develop new models end-to-end, from understanding product requirements to implementation and deployment.
Create an ML Ops framework to ensure models scale effectively with proper monitoring and alerts.
Qonto is creating the leading finance workspace with banking at its core for SMEs in Europe, augmented by financial tools. Founded in 2017 by Alexandre and Steve, Qonto has grown to over 1,600 employees and serves over 600,000 customers across 8 European countries, with a culture that prioritizes customer satisfaction.
You will personally own the Intelligence Engine -- Scoring & Activation and the behavioral scoring algorithms that power user-facing activation across B2C and B2B.
You will own the entire ML Pipeline Architecture, from data ingestion and feature stores to model training, evaluation, deployment, monitoring, and retraining triggers.
You will be responsible for LLM Integration & Optimization, integrating, fine-tuning, and deploying large language models for contextual inference, personalization, and behavioral pattern recognition.
Gesture is a fast-growing tech company using AI, machine learning, and intelligent logistics to power a unique platform that connects people and brands through real-world, tangible experiences. Inside their NYC headquarters, you'll find an environment that moves with the pace and precision of Silicon Valley but with the heart of something far greater.
Design, implement, and evaluate machine learning models and AI algorithms.
Develop and optimize prompts for LLMs to improve model outputs.
Collaborate with software engineers, data scientists, and product teams.
Cadre AI is focused on building and optimizing AI-powered platforms, bringing together cutting-edge technologies and expertise in machine learning and large language models. The team is dedicated to advancing AI capabilities and applying them to real-world challenges through scalable, high-impact solutions.
Architect the ML Ecosystem: You will own the end-to-end lifecycle of our ML infrastructure, designing a scalable, modern environment that enables models to thrive in production.
Productionize Innovation: Partner closely with our Data Science team to take complex algorithms from the "lab" to the "real-world", building the high-performance pipelines required to scale them.
Engineer Feature Intelligence: Design and maintain both offline and online feature stores, ensuring our models have the high-quality data they need for instant decision-making.
True Accord, a wholly owned subsidiary of TrueML, combines machine learning with a human-based approach to transform debt resolution and to get people on the path towards financial health. We are a dynamic group of people who are subject matter experts with a passion for change.