Build LLM-powered agents and production ML systems to automate security analysis.
Collaborate with threat-research and data engineering to turn risk identification into scalable solutions.
Own deployment, monitoring, and quality of solutions in CI/CD frameworks.
Zscaler accelerates digital transformation with its Zero Trust Exchange platform, protecting customers from cyberattacks and data loss. The company is the world's largest in-line cloud security platform, distributed across 160+ exchanges, with an AI-native culture focused on ownership, collaboration, and trust.
Design and maintain reliable, low-latency ML APIs to integrate Safety AI model outputs into cloud applications.
Build scalable data pipelines for continuous model iteration, backtesting, and online evaluation.
Optimize model artifacts for production and monitor rollout health, ensuring predictable failure modes.
Samsara builds a Connected Operations Cloud that helps physical operations use IoT data to improve safety, efficiency, and sustainability. Samsara is a recently public company with an employee-led remote culture and a long-term focus.
Build and operate the real-time inference service that scores models for the risk decision engine, with low latency and high availability.
Own model deployment infrastructure including registry, versioning, CI/CD, and staged rollouts.
Build model observability with availability, latency, error monitoring, and drift detection.
Mercury is a fintech company that builds banking services for startups. They are committed to diversity and inclusion, and are an equal opportunity employer.
Design and maintain the MLOps platform for experiment tracking, model registry, and CI/CD practices.\n- Productionize ML models into scalable, low-latency serving infrastructure with monitoring and rollback.\n- Automate retraining, evaluation, and deployment pipelines to reduce manual intervention.
Yuno builds payment infrastructure that connects companies to over 300 payment methods worldwide via a single API, using AI for intelligent routing and fraud prevention. It is a growing company with a global reach, founded by veterans from payments and technology, and emphasizes innovation and remote collaboration.
Architect and execute Machine Learning solutions, develop Large Language Models (LLMs), and build the AI stack to automate complex Data Analytics workflows.
Own the AI stack roadmap from opportunity sizing through prototyping to deployment and impact measurement.
Translate complex technical work into clear recommendations for senior stakeholders and mentor analysts.
JumpCloud is an AI-powered unified IT management platform that secures the modern workforce by consolidating identity, device, and access management. With teams in 15+ countries, it is a fast-paced, SaaS-based environment that values innovation and collaboration.
Develop tools and automate manual processes to improve operational efficiency and accelerate experimentation.
Build, integrate, and monitor end-to-end lifecycles of large-scale distributed machine learning systems.
Enhance ML pipelines for forecasting platforms with automated retraining and deployment.
Apella applies computer vision and machine learning to improve the standard of care in surgery. They are a remote-first startup focused on building reliable ML solutions for healthcare.
Build and own training pipelines for ML models, including data prep, fine-tuning, and experiment tracking.
Develop inference and serving layer with model gateway, routing, caching, and cost optimization.
Own release path for model-layer artifacts with canary deployments and monitoring for regressions.
Horizon3 is a fast-growing cybersecurity company that provides autonomous pentesting through its NodeZero platform. The team is a fusion of former special operations cyber operators, startup engineers, and cybersecurity practitioners, fostering a culture of respect, collaboration, and ownership.
Apply deep learning and foundation models to solve fraud detection and financial risk problems using large-scale behavioral and sequential datasets.
Take models through the complete ML lifecycle including data preparation, pretraining, deployment, and production optimization.
Collaborate with cross-functional teams and clients to translate model capabilities into actionable risk decisions.
The company is a fintech organization focused on fraud detection and financial risk using AI and deep learning. It operates with a remote-first culture and a collaborative, autonomous team.
Partner with the Business Unit Lead to identify gaps in decisioning performance and implement solutions.
Build production machine learning models to identify fraud in collaboration with other data scientists.
Communicate complex ideas to a variety of audiences, from Customer Success to Sales.
Signifyd helps merchants confidently grow their businesses by building trusted relationships with customers. Their advanced technology creates frictionless shopping experiences, and they are trusted by thousands of merchants across over 100 countries.
Architect, design, build, deploy, and maintain Model Serving infrastructure for a world-class Detection Engine.
Own projects that scale model serving and data processing to handle 10x traffic, including real-time streaming pipelines and online feature serving.
Collaborate with MLE and Data Science teams to build the ML Training platform, improving MLE velocity and model precision and recall.
Abnormal protects the humans behind the world's most critical organizations from AI-powered cybercrime. 4,500+ enterprises trust our behavioral AI platform, and we foster a culture of innovation and impact.
Own the success of TRM's most strategic North America private-sector accounts by using AI to create success plans and drive adoption, retention, and expansion.
Protect and grow private-sector revenue by defending GRR and surfacing expansion opportunities to increase NRR.
Use AI to accelerate QBR preparation, customer health monitoring, and build reusable workflows for the team.
TRM Labs provides AI-powered intelligence solutions that help public and private sector agencies investigate and disrupt crime. It is a Series C company with $220M in funding, operating as a distributed-first team with a high-ownership, mission-driven culture.
Build and operate production ML systems for recommendations, ranking, and personalized action selection across Stripe's Growth Platform.
Improve contextual bandit and policy-learning approaches, including exploration, reward design, and adaptive user feedback.
Develop reliable data and feature pipelines, reusable tooling, and online experiments to drive measurable business outcomes.
Stripe is a financial infrastructure platform for businesses of all sizes, enabling payments and revenue growth. With millions of companies as customers, Stripe fosters a culture of passion, grit, and integrity while working to increase the GDP of the internet.
Own the full ML delivery lifecycle from data discovery to deployment, monitoring, and retraining.
Build forecasting and detection models robust to real-world data quality issues and defend tradeoffs.
Maintain client-facing presence and feedback loop, shipping usable capability like FastAPI, React, or scheduled jobs.
We accelerate positive impact in critical industries through AI transformation, specializing in physics-informed ML and enterprise AI solutions for climate and sustainability. We're a fast-growing, profitable public benefit corporation founded in 2024, working with category leaders in real estate, energy, logistics, and utilities.
Own the full lifecycle of production machine learning models from handoff to deployment and monitoring.
Ensure model reliability through drift detection, performance monitoring, and incident response.
Extend the shared ML platform to make it stronger and cheaper for future models.
CarOnSale is the AI-powered platform for B2B used car trading in Europe, connecting over 40,000 buyers from 20+ countries. We are a team of engineers and data scientists building the operating system for the industry, with a culture of direct ownership and short decision paths.
Lead the engineering strategy for fraud, financial crime, and ongoing monitoring platforms.
Manage a distributed team across backend, frontend, data science, ML, and analytics engineering.
Drive measurable outcomes: lower fraud losses, higher automated alert throughput, and reduced monitoring costs per member.
Tide helps SMEs save time and money by offering business accounts, banking services, and administrative solutions like invoicing and accounting. With over 2 million members globally, Tide has offices in multiple countries and is Great Place to Work certified three years in a row.
Build and ship ML and GenAI systems from research to production.
Communicate technical concepts clearly to non-technical stakeholders.
Foster an atmosphere of experimentation, continuous learning, and improvement.
Expel is a cybersecurity company that uses machine learning and generative AI to detect threats in customers' environments. They offer a small, highly transparent environment where your voice matters and decisions have direct impact.
Productionize ML models into reliable, scalable systems with CI/CD, data versioning, and model governance.
Implement monitoring for data quality, drift, model performance, and pipeline health with clear alerting.
Refactor research code into reusable components and enforce engineering best practices.
Nift is disrupting performance marketing, delivering millions of new customers to brands every month. We are a data-driven, cash-flow-positive company that has experienced 731% growth over the last three years, backed by Spark Capital & Foundry.
Analyze large-scale network telemetry to identify malicious behavior and anomalies.
Design and refine ML models for threat detection, including evaluation on imbalanced data.
Provide technical leadership and collaborate with engineers to ship production-ready models.
ExtraHop protects enterprises with Network Detection and Response, revealing cyber threats and network issues. A leader recognized by major analysts, it fosters a values-driven culture of integrity, innovation, and teamwork.
Own the ML charter across identity resolution, fraud detection, risk scoring, and consumer intelligence, including strategy, roadmap, and delivery.
Build and grow a globally distributed team of ML engineers through hiring, coaching, and development.
Set the technical bar for model building, evaluation, deployment, and monitoring while holding the organization accountable.
Narvar is a platform that simplifies post-purchase experiences for retailers, driving customer loyalty through seamless interactions. With hubs in San Francisco, Atlanta, London, and Bangalore, the company serves over 125 million consumers and fosters a culture of low ego, high trust, and innovation.