Build and improve machine learning models and data-driven systems that classify, cluster, label, and enrich Internet-observed assets and services.
Own the design and development of applied ML workflows that turn raw Internet telemetry into usable context for internal systems and customer-facing products.
Partner with engineering, research, security, and product teams to ensure we’re building the right models, datasets, and feedback loops.
Design, build, and deploy machine learning models for cybersecurity use cases like threat detection and risk scoring.
Own the full model lifecycle from data preparation to production deployment, working closely with engineering and product teams.
Build preprocessing and feature engineering pipelines, and monitor model performance with continuous improvement.
SpyCloud transforms recaptured darknet data to disrupt cybercrime. With over 250 employees, it is home to cybersecurity experts protecting businesses and consumers from stolen identity data.
Architect and develop robust, end-to-end machine learning solutions, managing the complete ML lifecycle from development to production.
Collaborate closely with data engineers and data scientists to create highly scalable solutions and integrate them across the software development life cycle.
Evaluate cloud solutions for performance and cost-efficiency, and communicate technical concepts clearly to stakeholders and teams.
Coderio designs and delivers scalable digital solutions for global companies, combining strong technical expertise with a product mindset to lead complex software initiatives end-to-end. They work with international clients, value autonomy and clear communication, and build long-term partnerships through technical excellence.
Drive the technical and product roadmap by contributing innovative ideas and estimating effort for high-velocity execution.
Collaborate with product managers and engineers to translate abstract business needs into scalable technical implementations.
Own end-to-end responsibility for complex initiatives, from scoping with stakeholders to production deployment and maintenance.
TrueML is a mission-driven financial software company that uses machine learning to create better digital experiences for distressed borrowers. The team includes inspired data scientists, financial services experts, and customer experience fanatics building technology to ensure nobody gets locked out of the financial system.
Design, build, deploy, and maintain scalable machine learning and AI systems in GCP to solve complex business problems and create new value.
Partner across teams to understand problem definitions, data needs, and solution approaches, and support model deployment with MLOps practices.
Take ownership of production issues, perform root cause analysis, and improve documentation and quality assurance processes for ML systems.
General Mills makes food the world loves, operating across 100+ markets. As a large company, it prioritizes being a force for good and fosters a culture of bold thinking and big hearts, where employees challenge each other and grow together.
Architect and maintain end-to-end traffic classification ML systems
Build rigorous evaluation frameworks to ensure model improvements are measurable
Partner with security and data engineering teams to integrate scoring intelligence
Airbnb is an online marketplace that connects hosts with guests, offering unique stays and experiences. Founded in 2007, the company has grown to over 5 million hosts and 2 billion guest arrivals, with a culture committed to inclusion and belonging.
Lead applied AI projects from concept to impact, building and deploying ML/GenAI solutions across product, engineering, and security teams.
Act as an internal AI consultant, scoping problems, evaluating approaches, and advising on best practices for generative technologies.
Design experiments, build models for anomaly detection and fraud analysis, and bridge research to production via scalable APIs and tools.
Sonatype is a software supply chain management company that invented componentized software development and pioneered the category. Trusted by over 2,000 organizations, including 70% of the Fortune 100, and 15 million developers, the company fosters innovation, AI/ML adoption, and an inclusive culture.
Design and maintain ML model productionization infrastructure for high-visibility product features.
Collaborate with data science to streamline model training, validation, and deployment.
Implement robust monitoring and alerting for model performance, drift, and data quality.
The Athletic is a sports media company powered by one of the largest global newsrooms in sports, delivering in-depth coverage of professional and college teams across North America and Europe. With over 500 full-time staff, they foster a collaborative culture focused on high-quality journalism and data-driven innovation.
Design, develop, and deploy foundational AI and ML models, building robust, scalable pipelines for advanced analytics.
Champion top-tier coding, testing, and MLOps practices, navigating ambiguity to refine pipelines and elevate workflows.
Partner with cross-functional stakeholders to convert strategic needs into technical specs and embed ML features into live applications.
Wave helps small businesses thrive so the heart of our communities beats stronger. They create an environment buzzing with creative energy and inspiration, valuing boldness, quick learning, and generous knowledge sharing.
Design and implement end-to-end document intelligence pipelines on AWS, including ML model development for document classification and field extraction.
Build scalable data processing systems handling PDFs up to 2000 pages, and own features from research through production deployment and monitoring.
Collaborate with subject matter experts to refine requirements, establish evaluation frameworks, and ensure extraction accuracy.
Exadel is an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients including HBO, Microsoft, Google, and Starbucks. Our culture is defined by ambitious, collaborative, and constantly evolving people who lead with trust, respect, and purpose.
Build, adapt, and operationalize ML models to estimate forest structure from remote sensing data.
Integrate trained models into automated production pipelines and maintain surrounding data infrastructure.
Contribute to scientific manuscripts and serve as a cross-team link between SciDev and Data Engineering.
Vibrant Planet is a team of leaders in fire science, applied science, forestry, policy, and tech that uses a cloud-based AI-driven platform to lower wildfire risk. The company is backed by climate and resilience leaders and values an inclusive, equitable work environment.
Drive innovation across the machine learning ecosystem and architect advanced ML solutions.
Mentor junior ML engineers and lead complex ML initiatives at scale.
Own models in production including deployment, monitoring, drift detection, and retraining.
Xsolla is a global commerce company providing tools and services to help video game developers fund, distribute, market, and monetize their games. Headquartered in Los Angeles, California, Xsolla has helped over 1,500 game developers grow their businesses worldwide.
Support training, fine-tuning, and evaluation of neural foundation models.
Build and maintain data pipelines for petascale neurobehavioural datasets.
Prototype tools and demos to apply trained models to robotics and embodied AI tasks.
Netholabs builds AI grounded in biological intelligence by recording petascale neurobehavioural data to train neural foundation models. They are a small, fast-moving research team focused on AI, robotics, and personalized intelligence.
Integrate and deploy automated event-tagger into production pipelines, running and monitoring tagging tasks at scale across petabytes of vehicle log data.
Build and maintain data engineering pipelines that organize, structure, and catalog tagged scenario data into the observations database.
Own CI/CD using GitHub Actions, write production code in Python, and operate on Databricks and AWS infrastructure.
Torc is an autonomous driving technology company that develops software for automated trucks. Founded in 2007 and now part of Daimler, the company has a collaborative culture and offers competitive benefits.
Optimize and validate targeting mechanisms for specific health conditions using classic ML.
Improve proprietary contextualization and recommendation engines handling trillions of transactions monthly.
Collaborate with internal health experts to prototype ideas for commercialization.
PulsePoint sits at the intersection of healthcare and adtech, helping brands and agencies interpret health signals by unifying digital determinants of health with real-world data. With over 300 employees and growing, they are a post-acquisition business and a leading player in the US healthcare ad market.
Own the full model lifecycle from requirements and feature engineering through deployment and monitoring, partnering with ML engineers.
Translate complex fraud patterns into well-framed ML solutions, defining what to model and where ML adds value.
Design feature engineering pipelines, monitor model quality in production, and collaborate across teams to drive fraud strategies.
Extend revolutionizes the post-purchase experience for retailers by providing AI-driven solutions that enhance customer satisfaction and drive revenue growth. Backed by prominent technology investors and headquartered in San Francisco, Extend works with over 1,000 leading merchant partners across industries, fostering a collaborative and supportive culture.
Lead and grow a team of machine learning engineers, guiding career development, managing conflicts, and nurturing a positive work environment.
Run a portfolio of experiments, balancing near-term improvements with longer-horizon innovation bets, and make decisions on hypothesis resourcing.
Partner with Risk stakeholders to set direction from data, own delivery cadence, and represent team results to engineering leadership and the wider company.
Signifyd helps merchants grow their businesses by building trusted customer relationships through advanced technology that eliminates fraud and creates frictionless shopping experiences. The company is trusted by thousands of leading merchants across more than 100 countries, securely processing billions of transactions annually, and fosters a culture of commitment, empathy, and creativity.
Architect and lead the development of next-generation, large-scale machine learning techniques.
Define and execute the ML strategy, identifying opportunities to enhance personalization and recommendation quality across Reddit.
Partner with ML infrastructure teams to build high-performance, distributed training systems that efficiently scale across multiple GPUs and cloud environments.
Reddit is a community of communities, built on shared interests, passion, and trust. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.
Deliver on business-critical outcomes by owning backend and data services end-to-end, from design to production operation.
Design, build, and operate scalable data pipelines and streaming ingestion for high-volume security telemetry.
Contribute to data modeling and warehouse/lakehouse architecture decisions that serve detection, analytics, and product features.
Blackpoint Cyber is the leading provider of world-class cybersecurity threat hunting, detection and remediation technology. Founded by former National Security Agency (NSA) cyber operations experts, the company is in hyper-growth mode, fueled by a recent $190m series C round.
Build security systems that make decisions from incomplete and noisy data.
Work across detection systems, distributed infrastructure, product surfaces, and AI inference.
Own hard problems, set technical direction, and make engineers around you better.
Aegis is a security startup founded by ex-Google engineers who built Safe Browsing and reCAPTCHA, now tackling adversarial AI attacks. They are a small, technical, and ambitious Series A company with a rapidly growing market.