Lead the development and optimization of machine learning models to detect and prevent AI security risks like prompt injection and jailbreaks.
Build reproducible training and evaluation pipelines on Reddit's ML platform, partnering with platform engineers to improve performance and reliability.
Set the technical vision and multi-quarter modeling roadmap, mentoring engineers and establishing best practices for responsible ML development.
Develop advanced ML models and agentic workflows to accelerate model development.
Use AI-assisted tools like Claude and Cursor to investigate model behavior and automate analysis.
Set technical direction, mentor engineers, and raise the bar for modeling rigor.
Reddit is a community of communities, built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.
Shape AI security at the edge by turning new threats into protections customers can use.
Think like an attacker to find new ways AI systems can be exploited and stop them.
Build for real time, catching threats without slowing down the applications we protect.
bunny.net is a content delivery network and edge computing company that accelerates the internet. Founded in 2015, the company has 95+ employees and fosters a culture of ownership, improvement, and challenging what's possible.
Build cutting-edge technology using deep learning and machine learning to personalize Pinterest.
Partner with teams to improve ML models for product surfaces like Homefeed and Search.
Use data-driven methods to improve content recommendation and ads delivery.
Pinterest is a platform where millions of people find creative ideas and plan for memories. The company is mission-driven, focusing on innovation and inclusion, with a large and diverse user base.
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.
Lead security reviews of architecture, code, and security-sensitive changes.
Secure AI-powered products against prompt injection, unsafe tool use, and tenant isolation risks.
Threat model new capabilities and build scalable guardrails that reduce recurring risks.
Cohere is a security-first enterprise AI company building foundation models and products for business. It is a global team of researchers, engineers, and designers headquartered in Toronto with offices worldwide.
Act as the bridge between architectural intent and operational reality, mediating conflicts between security requirements and feasible implementation.
Implement preventive, default-on security controls across cloud and enterprise environments, codified as policy- and infrastructure-as-code.
Define and enforce security requirements for AI-powered features, including model access controls, prompt-injection mitigations, and output validation.
Rithum is the world's most trusted commerce network, accelerating how brands, suppliers, and retailers work together to deliver seamless e-commerce experiences. More than 40,000 companies trust Rithum to grow their business across hundreds of channels, representing over $50 billion in annual GMV.
Own a major subsystem of a novel exploitability engine end-to-end, including design, delivery, and quality.
Drive design and code reviews, raise the engineering bar, and mentor engineers through influence.
Partner with product, security R&D, and SecOps to turn customer problems into subsystem design.
ServiceNow provides an AI platform that automates workflows to free people from busywork, serving as the AI control tower for business reinvention. It serves 85% of the Fortune 500 and fosters an AI-native culture where technology and talent are unstoppable.
Lead Affirm's enterprise AI security review process, evaluating architecture, data flows, and design of AI tools and agentic systems.
Threat model AI/LLM systems for risks like prompt injection, insecure output handling, and data poisoning, and drive remediation.
Build security guardrails, tooling, and policy-as-code to automate AI security and support cross-functional initiatives.
Affirm is a financial technology company that offers clear, predictable point-of-sale installment loans with no hidden fees. The company is remote-first and values transparency, care, and flexibility, with a focus on building a diverse and inclusive team.
Own the ML/AI platform, including training infrastructure, model serving, inference pipelines, and production integrations.
Set technical direction for ML/AI architecture, tooling, standards, and strategy in partnership with data science and engineering.
Drive GenAI and LLM engineering, including RAG, prompt engineering, fine-tuning, and agentic workflows.
This company builds AI/ML infrastructure for financial technology products used by over 1,600 financial institutions. It operates as a globally distributed team with a focus on innovation and collaboration.
Design and implement layered AI guardrails and sandboxing to constrain AI behavior and secure enterprise workflows.
Partner with users to bake secure-by-default patterns into AI-assisted workflows and maintain an inventory of AI-to-service connections.
Continuously test guardrails through red-teaming and evaluate new AI tools to find secure ways to enable adoption.
Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI, developing autonomous transportation technology for commercial trucks and robotaxis. Backed by world leaders in AI and automotive, the company has offices in Toronto, San Francisco, Dallas, and Pittsburgh and is growing quickly with a diverse, innovative team.
Design, implement, and operate benchmark execution and evaluation harnesses for AI models and agentic workflows.
Develop evaluation methodologies that combine automated metrics with structured human subject matter expert judgment.
Produce defensible evaluation reports comparing candidate capabilities with current mission workflows, including documented limitations and failure modes.
OpenTeams helps enterprises and governments build AI they control, govern, and evolve themselves. Founded by NumPy and SciPy creator Travis Oliphant, the company is built by people with deep roots in the open-source ecosystem.
Design, build, and improve production agentic AI systems used to solve complex real-world problems.
Develop agent architectures, model integrations, and evaluation frameworks for reliable, production-grade AI.
Build scalable APIs, services, and infrastructure supporting agent execution and AI-powered product experiences.
Air is the leader in Enterprise Readiness, providing an AI-native platform to align development, production, delivery, and sustainment for government agencies and industrial suppliers. The company is a startup with a focus on mission-driven work and innovation.
Lead the architectural design and development of scalable AI/ML pipelines for enterprise initiatives.
Provide technical leadership and mentorship to AI/ML engineers and data scientists.
Deploy and manage advanced models including LLMs and Generative AI in production environments.
They are an organization focused on delivering enterprise AI and Machine Learning solutions. They offer a fully remote, flexible work environment with a strong emphasis on professional growth and collaboration.
Build the foundations of the EdgeRunner Research organization, including data pipelines, model evaluation, and efficient parallelization.
Own codebases in areas like distributed training, quantization, compression, or compute cluster management.
Collaborate with a team of self-starters who operate independently and translate business objectives into technical solutions.
EdgeRunner AI builds state-of-the-art AI models for the tactical edge, enabling warfighters to make faster decisions and interact with robotic platforms. As a Series-A startup, we move quickly, fostering a culture of initiative, ownership, and comfort with ambiguity.
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.
Design and implement novel training optimization techniques for large-scale neural networks.
Investigate approaches to improve training efficiency, stability, and convergence speed.
Collaborate with infrastructure and inference engineering teams to translate research into production performance.
This partner company focuses on AI research and training optimization for large-scale models. They maintain a small, senior-level team that values deep technical thinking and thoughtful execution.
Own the technical vision and roadmap for ML systems powering forecasting, supply positioning, and fleet optimization.
Lead end-to-end execution of complex, cross-functional ML initiatives, from problem framing through production impact, ensuring alignment with business goals.
Mentor and develop engineers, providing technical guidance and raising the overall bar for ML and software engineering excellence.
Lime is the largest global shared micromobility business, on a mission to build a future where transportation is shared, affordable, and carbon-free. A Time Magazine 100 Most Influential Company, Lime has powered more than one billion rides in close to 30 countries across five continents, spurring a new generation of clean alternatives to car ownership.
Design, build, and improve machine learning training and inference pipelines for AI-driven music experiences.
Apply machine learning and prompt engineering across complex ML pipelines to support large language model features.
Create evaluation frameworks with LLM-as-judge pipelines to measure quality and enable rapid iteration.
Spotify is a digital music service that provides access to millions of songs. With over 700 million monthly active users, Spotify fosters a culture of innovation and collaboration, prioritizing artist-first principles in its AI music lab.
Design and build AI agents and automation to solve real problems across engineering, product, and delivery.
Partner with stakeholders to identify high-leverage opportunities and deliver end-to-end solutions.
Stay current with LLM and agentic frameworks to drive innovation in healthcare technology.
HealtheDGE provides AI-powered operational infrastructure for health insurance companies, helping them modernize operations. The company is experiencing strong market momentum and invests in its people, offering a collaborative culture focused on innovation.
Design and write high-performing, scalable software for training models.
Develop new tools to support and accelerate research and LLM training.
Collaborate with engineering and scientific teams to create a strong post-training ecosystem.
Cohere is a security-first enterprise AI company building cutting-edge foundation models and end-to-end products to solve real-world business problems. They are a global team of researchers, engineers, and designers passionate about their craft, with offices in Toronto, London, New York, San Francisco, Montreal, Paris, Berlin, and Seoul.