Work on impactful AI and machine learning projects and contribute to solutions. Help build and support machine learning models and AI systems that power Experian's products and services. Participate in research and experimentation with new AI techniques and tools and machine learning models focusing on real-world applications.
Experian is a global data and technology company, powering opportunities for people and businesses around the world.
Build cutting edge Generative AI models, using techniques like Supervised Finetuning (SFT), Reinforcement Learning (RL), prompt improvements and synthetic data generation
Collaborate closely with product managers and engineers to transform user feedback into requirements for AI systems.
Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI.
Lead the design, development, and deployment of AI/ML models.
Build and maintain production-grade ML pipelines and model monitoring.
Mentor and develop junior AI engineers, laying the foundation for AI best practices.
Payabli enables any software company to become a payments company through its payment infrastructure and monetization platform to boost enterprise value.
Design, build, and productionize ML models for fine-tuned, Retrieval-Augmented Generation (RAG), and generative AI features.
Build and maintain scalable data pipelines to collect high-quality training and evaluation datasets, including annotation systems and human-in-the-loop workflows.
Collaborate with product and engineering to iterate on datasets, evaluation metrics, and model architectures to improve quality and relevance.
Mural is pioneering how generative AI transforms visual collaboration and decision-making.
Build embedding & similarity search pipelines at planetary scale
Fine‑tune multimodal foundation models for Earth‑observation tasks
Planet designs, builds, and operates the largest constellation of imaging satellites in history. Planet is both a space company and data company all rolled into one with a people-centric approach toward culture and community striving to iterate to puts its team members first.
Prototype, iterate, and ship algorithms to production in close collaboration with Product, Data Engineering, and Software teams.
Mirakl provides eCommerce software solutions that enable enterprises to drive growth and efficiency in their online business. With over 350 employees in France and offices in 7 countries, Mirakl is considered a Great Place to Work company that is pioneering the platform economy.
Develop production data science applications in Python, end to end. Design and develop new AI services from scratch. Maintain and enhance current data science pipelines in complex high-load applications.
Founded in 1999, the company has a premium listing on the Main Market of the London Stock Exchange and is focused on regulated and regulating markets.
Lead the full data science lifecycle, from data acquisition and preparation to model development, deployment, and performance monitoring. Leverage advanced machine learning, deep learning, and generative AI techniques to solve challenging problems and deliver impactful solutions. Collaborate with cross-functional teams, including product managers, engineers, and analysts, to translate business needs into scalable, production-ready AI/ML solutions.
Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.
Design and deploy production-ready ML solutions, leveraging cutting-edge platforms.
Conduct causal analysis to guide high-stakes business strategy.
Integrate models into production systems and monitor their performance using advanced observability tools.
CSC Generation is the AI-native holding company re-engineering omni-channel retail by acquiring iconic brands and transforming them with their operating platform.
Draft detailed natural-language plans and code implementations for machine learning tasks. Convert novel machine learning problems into agent-executable tasks for reinforcement learning environments. Identify failure modes and apply golden patches to LLM-generated trajectories for machine learning tasks.
Mercor is building the talent engine that helps leading labs and research orgs move AI forward.
Develop and implement machine learning models to enhance Uber Freight's logistics capabilities.
Collaborate with cross-functional teams to integrate AI solutions into existing systems.
Contribute to the design and architecture of scalable and robust AI platforms.
Uber Freight is a market-leading enterprise technology company powering intelligent logistics with a suite of end-to-end logistics applications and an expansive carrier network.
Explore, analyze, and visualize large datasets from mobile + web observability data and user session data
Develop statistical measures and applied models to identify meaningful classifications, trends, anomalies, or predictive signals in event data
Partner with Embrace staff (product + data science) to prioritize research projects and translate research insights into potential product features
Embrace is the only user-focused observability solution built on OpenTelemetry, delivering insights across DevOps, web, and mobile teams. Customers like The New York Times and Home Depot use Embrace's platform to make complicated data actionable, reflecting the company's values of continuous improvement.
Formulate and execute small, high-leverage research projects aligned with our product roadmap.
Independently build and validate end-to-end prototypes.
Design and run experimental pipelines autonomously, including setting up research environments and defining evaluation metrics.
ZetaChain is building the first universal blockchain and AI platform that connects everything—Bitcoin, Ethereum, Solana, and more—while pioneering in the GenAI space. They are backed by top investors, live on mainnet, and building the future of blockchain and AI technology.
Design, implement, and deploy AI-powered features, including model training, fine-tuning, and prompt engineering workflows.
Translate product requirements into robust, production-ready AI solutions, working with Product Managers, Software Engineers, and Data Scientists.
Optimize models and infrastructure for scalability, latency, and cost efficiency, partnering with DevOps and MLOps to ensure reliable and maintainable AI pipelines.
Paper is reimagining how schools support students so that every learner can reach their full potential.