Guide the technical direction of Bondora’s ML engineering stack by selecting, evaluating, and implementing technologies to improve scalability and reliability.
Lead complex, high-risk, or cross-departmental projects that directly influence Data Science delivery, risk model performance, and production stability.
Act as the bridge between Data Science, Data Engineering, and Development to identify and solve systemic technical challenges.
Bondora's mission is to empower people to enjoy life more while alleviating the stress of managing finances. Founded in 2008, Bondora has served over 1 million customers for 16 years and is rapidly growing as a fintech company, set to acquire a banking license and expand investment and loan products across Europe.
Analyze 4+ years of reservation data from live restaurant partners to understand demand patterns
Build predictive models that account for factors like table type, day of week, time slot, booking lead time, seasonality, and more
Design a dynamic pricing engine that can adjust prices based on real-time demand signals
Peak is redefining reservations and views them as unique experience tickets, created with hospitality experts. They are a small, remote team of approximately 10 people based in NYC, bringing their Peak experience to the top dining scene.
Work in a small, cross-functional team of 3-4 people focused on AI/ML systems.
Take ownership of projects from ideation to deployment with a high degree of autonomy.
Collaborate with product managers and stakeholders to understand customer pain points and deliver impactful solutions.
TriumphPay is building the transportation payments network for the future. Their software touches a combined $37.1B in annualized freight volume. They foster an environment that provides exceptional customer service, entrepreneurial spirit, and building successful partnerships with their clients.
Own ML powered features from design through deployment, partnering with product, design, and engineering to scope work and define success metrics.
Calendly's product enables millions of people to coordinate easily. They are experiencing exciting product growth, making it a great time to consider joining their journey.
Design and implement MLOps pipelines to automate model training, deployment, monitoring, and management
Lead/mentor a team of MLOps Engineers, fostering an inclusive and collaborative environment that encourages innovation and continuous learning
Collaborate with Data Scientists and ML Engineers to ensure models are production-ready, scalable, and maintainable
Egen is a fast-growing and entrepreneurial company with a data-first mindset. They bring together the best engineering talent working with the most advanced technology platforms, including Google Cloud and Salesforce, to help clients drive action and impact through data and insights.
Perform comprehensive evaluations of data assets across the full credit and fraud lifecycle, ensuring strong regulatory compliance and risk governance.
Conduct rigorous benchmarking and champion/challenger analyses to compare external data assets against internal attributes, scores, and predictive models, ensuring measurable lift, ROI and benefits.
Develop advanced machine learning solutions and algorithms to solve complex analytical challenges.
Experian is a global data and technology company, powering opportunities for people and businesses around the world. They operate across a range of markets, from financial services to healthcare, automotive, agrifinance, insurance, and many more industry segments. A FTSE 100 Index company listed on the London Stock Exchange (EXPN), they have a team of 23,300 people across 32 countries.
Manage, mentor, hire and grow 8+ ML Engineers and Data Engineers across three distinct teams
Be a strong technical partner for engineers to guide ML system architecture, model deployment, and data platform design & execution
Ensure ML solutions are production-grade, scalable, observable, cost effective and maintainable
Apella is applying computer vision and machine learning to improve the standard of care in surgery. They build applications to enable surgeons, nurses, and hospital administrators to deliver the highest quality care; they are committed to equal employment opportunity.
Engaging directly with current and prospective clients to understand business needs, translate them into technical requirements, and communicate findings in a clear, actionable way
Partnering with internal and client stakeholders to shape solutions, develop proposals, and contribute to go-to-market initiatives
Design, develop and deploy efficient data pipeline for both structured and unstructured data
Resultant consists of a team of engineers, mathematicians, data analysts, project managers, and business consultants. They partner with clients in the public and private sectors to help them overcome complex challenges, empowering clients to drive meaningful change.
Designing, deploying, and optimizing data-driven machine learning solutions on AWS.
Creating secure and scalable ML systems, enabling effective data management and model deployment.
Leading the enhancement of best practices within the data and ML lifecycle, making a substantial impact across projects and teams.
Jobgether uses an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company.
Set the technical direction for the data engineering team and own the strategy of the data platform.
Lead a team of data engineers while staying hands-on with architecture decisions and technical leadership.
Maintain and build feature stores and ML infrastructure to power machine learning models.
Vivian Health empowers every healthcare professional to find their perfect job faster and easier than ever before. As the largest healthcare jobs marketplace, they support over 2 million clinicians in finding their next career opportunities and is backed by world-class investors, including Thoma Bravo and IAC.
Design, implement, and maintain high-performance ML training and inference platforms.
Ship tools that allow any ML engineer to deploy a model in minutes, not days.
Improve scalability, reliability, and cost efficiency of model training and serving systems.
Speechify's mission is to make sure that reading is never a barrier to learning. With nearly 200 people around the globe working in a 100% distributed setting, Speechify's team includes frontend and backend engineers, AI research scientists, and others.
Lay down the first ML and statistical components of the data science platform
Translate business problems and feature needs to machine learning problems
Implement always-on training pipelines
Kamino Retail, powered by Equativ, is a pioneering SAAS platform at the forefront of retail media innovation. They equip retailers with advanced tools and solutions to revolutionize their advertising strategies, amplify customer engagement, and drive concrete results.
Design, develop, and deploy robust ML systems and multi-model AI agents that solve real-world retail challenges.
Lead the entire lifecycle, including prototyping, deployment, monitoring, and maintenance using modern CI/CD and containerisation practices.
Build high-performance data pipelines (ETL/ELT) for both training and real-time inference, ensuring our systems are scalable and reliable.
EDITED is the world’s leading AI-driven retail intelligence platform. They empower the world’s most successful brands and retailers with real-time decision making power. Their environment is dynamic and supportive, encouraging team members to take initiative, innovate, and continuously grow.
Define the vision and roadmap for the data function, prioritizing initiatives for maximum business impact.
Build, mentor, and manage a high-performing Data team while coordinating with external agencies until internal resources are established.
Partner with product, engineering, marketing, operations, and leadership to translate business goals into measurable outcomes.
Jobgether is using AI-powered matching process to ensure application is reviewed quickly by identifying the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps are managed by their internal team.
Lead the development and application of machine learning and LLM-powered models across various functions.
Translate business problems into clear modeling objectives and experimentation plans.
Manage and mentor applied ML practitioners, setting high standards for modeling rigor.
Gametime helps people connect through shared experiences by making it easy to discover and access live events. They operate platforms across the US and Canada, reimagining the event ticket industry to move at the speed of life.
Build and optimize data pipelines and backend services to process device and behavioral data in real time.
Develop and deploy ML models for fraud detection, ensuring they run reliably and efficiently in production.
Turn raw data into production-ready features that feed our fraud detection systems.
Sardine is a leader in fraud prevention and AML compliance. Their platform uses device intelligence, behavior biometrics, machine learning, and AI to stop fraud before it happens. Over 300 banks, retailers, and fintechs worldwide use Sardine; they have a remote-first work culture, valuing performance over hours and hiring self-motivated individuals.
Own end-to-end modelling of LTV, user segmentation, retention, and marketing efficiency to inform media optimization and value attribution.
Conduct deep-dive analysis of user behaviour, funnel performance, and product engagement to uncover actionable insights.
Build predictive models for conversion, churn, revenue, and engagement using regression, classification, or time-series approaches.
Forbes Digital Marketing Inc. helps consumers make confident, informed decisions about their money, health, careers, and everyday life. Our global teams bring deep expertise across journalism, product, performance marketing, data, and analytics.
Define the vision, strategy, and roadmap for data science and modeling across the company.
Partner with data scientists to validate, test, and monitor models for performance, fairness, and business impact.
Conduct research with internal and external stakeholders to understand decision-making workflows and data-driven opportunities.
Buyers Edge Platform is revolutionizing the foodservice industry through technology, purchasing power and partnerships. They empower stakeholders across the entire foodservice ecosystem with efficiency and unprecedented visibility and have over 200K operator locations across North America and over $50 billion of aggregated spend volume.
Design, implement, and maintain robust, containerized, and reproducible pipelines for model training, evaluation, and deployment—across both batch and real-time settings.
Build and manage ML services, APIs, and model serving infrastructure using tools like MLflow, Amazon SageMaker, and Feature Store.
Set up and maintain monitoring, observability, and alerting systems to ensure high availability and performance (including model/data drift, feature logging, and inference latency).
AUTO1 Group Technology drives innovation in the used car market across Europe. They operate at the intersection of software engineering, data science, and DevOps, helping bring state-of-the-art ML models—such as large-scale recommendation systems and transformer-based neural networks—safely into production.