Design, build, and maintain machine learning model productionization infrastructure.
Streamline model training, validation, and deployment in collaboration with the data science team.
Implement robust monitoring and alerting for model performance, drift, and data quality.
The Athletic delivers in-depth coverage of sports, teams, and athletes. Their newsroom of 500+ full-time staff covers hundreds of professional and college teams across North American markets and football clubs.
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.
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.
Lead our AI & Data department with autonomy as a proactive tech enthusiast.
Develop, train, validate, optimize, and maintain Machine Learning models.
Extract, clean, validate large datasets, and interpret data for business opportunities.
Everfield buys, builds, and grows European vertical market and specialist software companies, providing them with the tools they need to move to the next level. Companies in the Everfield ecosystem follow a decentralised model, maintaining their team, brand, and offices, while focusing on what they do best - building products and supporting customers.
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.
Support the full operational lifecycle of both traditional machine learning systems and emerging generative AI driven applications.
Enable scalable training, evaluation, deployment, and monitoring for a wide range of ML and GenAI workloads.
Manage model upgrades, framework versions, regression testing, maintenance tasks and maintaining performance across systems and solutions.
Achievers' employee recognition and rewards platform empowers organizations to build cultures where people feel seen and valued, everyday. They're a team of passionate, thoughtful builders with more than 4.3 million users across 190 countries, who care deeply about their product, their customers, and each other.
Manage machine learning model versioning, lineage tracking, and compliance with governance policies, ensuring reproducibility and secure deployment.
Implement and monitor ML infrastructure, optimizing compute resource allocation across cloud and on-premises environments.
Validation of AI/ML pipelines, ensuring models remain accurate, explainable, and aligned with operational objectives.
SOSi, founded in 1989, is a large private technology and services integrator in the defense and government services industry. They deliver tailored solutions, tested leadership, and trusted results to enable national security missions worldwide.
Extend, optimize, and maintain core data models that support customer-facing reports, machine learning, and generative AI workloads.
Implement automation and operationalize ML models workflows that streamline operational processes, reduce manual work, and improve system efficiency.
Partner with engineering, product, and analytics teams to deliver seamless integrations and customer-facing data products.
Boulevard provides the first and only client experience platform for appointment-based, self-care businesses, empowering customers to give their clients more of the magical moments that matter most. They value diverse backgrounds and believe in equal opportunity for all.
Lead hands-on development of EnableComp’s predictive intelligence platform.
Own ML model development for work prioritization, business insights, and strategic decisions.
Architect and build the platform before scaling a team.
EnableComp solves complex claims. With Complex Revenue Intelligence™ (CRI), they help hospitals recover $3 billion annually, recognized as Black Book’s #1 Specialty RCM provider and a Top Workplaces honoree, with a SOC 2 Type II and HITRUST e1-certified platform.
Work with large, messy, and complex data sets using analytical, statistical, ML, and AI approaches.
Collaborate with Data and Analytic Engineers to improve data quality and generate reusable assets.
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product and business strategy.
Weedmaps is a global leader in the cannabis industry, dedicated to transparency, education, and community. Founded in 2008, Weedmaps fosters a bustling and collaborative culture that focuses on the benefits of weed and the community that supports it.
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.
Drive alignment across teams on ML strategy, standards, and long-term technical direction.
Guide recommendations for ML infrastructure, tooling, and architecture.
Define and evolve ML development processes, including model review, experimentation rigor, deployment, optimization, and operations
Lime is the largest global shared micromobility business. They operate in close to 30 countries across five continents with a mission to build a future where transportation is shared, affordable and carbon-free. Named a 2025 Time 100 Most Influential Company, Lime continues to set the pace for shared micromobility globally.
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.
Design and build robust, highly scalable data pipelines and lakehouse infrastructure with PySpark, Databricks, and Airflow on AWS.
Improve the data platform development experience for Engineering, Data Science, and Product by creating intuitive abstractions, self‑service tooling, and clear documentation.
Own and maintain core data pipelines and models that power internal dashboards, ML models, and customer-facing products.
Parafin aims to grow small businesses by providing them with the financial tools they need through the platforms they already sell on. They are a Series C company backed by prominent venture capitalists, with a tight-knit team of innovators from companies like Stripe, Square, and Coinbase.
Design, build, and maintain secure, compliant ML infrastructure and automation adapted for high-sensitivity environments.
Develop and productionize machine learning and data pipelines serving real-time models that fight fraudulent traffic, spam, and bots.
Extract valuable signals from massive datasets, using your expertise to turn raw data into actionable insights.
Yelp is driven by their values, they’re a cooperative team that values individual authenticity and encourages creative solutions to problems. They are all about helping their users, growing as engineers, and having fun in a collaborative environment and are an equal opportunity employer.
Collaborate with cross-functional teams and business units to understand and communicate Ion’s needs and goals.
Develop, improve, and maintain robust data pipelines for extracting and transforming data from log files and event streams.
Design models and algorithms to derive insights and metrics from large datasets.
Intuitive is a global leader in robotic-assisted surgery and minimally invasive care. Their technologies, like the da Vinci surgical system and Ion, have transformed how care is delivered for millions of patients worldwide. They are a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human.
Build scalable Edge infrastructure, designing, developing, and maintaining delivery systems to deploy models to fleets of devices.
Work with cross-functional teams, collaborating with Data Scientists, Embedded Engineers and Product Managers to ensure smooth integration of complex features and capabilities.
Drive automation and reliability, implementing infrastructure to silently test candidate models on production devices, and build telemetry pipelines to monitor drift.
Hudl builds great teams and hires the best of the best to ensure you’re working with people you can constantly learn from. They work hard to provide a culture where everyone feels supported, and their employees feel it, helping them become one of Newsweek's Top 100 Global Most Loved Workplaces.
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.
Architect, build, and operate data infrastructure that powers Tebra’s intelligent features.
Translate business requirements into software solutions that accelerate our ability to deploy AI.
Monitor data pipelines, detect anomalies, and implement automated recovery systems.
Tebra unites Kareo and PatientPop, providing a digital backbone for practice well-being, supporting both products with a shared vision for modernized care. Over 100,000 providers trust Tebra to elevate patient experience and grow their practice, building the future of well-being with compassion and humanity.