Learning Systems Engineer

About Our TeamThe Education team at OpenAI is dedicated to creating systems that transform ChatGPT into a powerful learning ally. As advancements in AI unfold rapidly, we aim to develop educational tools that empower individuals, educators, developers, and organizations to progress from curiosity to expertise with the aid of AI technologies.Our team operates at the crossroads of artificial intelligence, educational psychology, and large-scale platforms, building the foundation for AI-driven learning experiences worldwide.About the RoleWe are looking for a Learning Systems Engineer to join us in establishing the infrastructure that supports AI-enhanced educational experiences. This role integrates backend architecture, learning science, research, and product development.You will convert educational objectives into scalable systems: learner models, tracking progress, adaptive feedback mechanisms, formative assessments, and analytics that demonstrate effective learning outcomes.Your contributions will help millions globally learn efficiently and harness the full potential of AI.What You Will Work OnDevelop AI-Driven Learning Infrastructure: Create essential systems for AI education, including dynamic learning experiences, progress tracking, and assessments.Facilitate Adaptive Learning: Design capabilities that enable learning experiences to evolve according to learners’ knowledge, goals, and behaviors over time.Construct Data Systems for Insights: Develop data pipelines and analytical systems that help educators grasp learner outcomes, engagement trends, and skill advancement.Empower Educators: Create systems that allow non-technical users to design, configure, and experiment with learning experiences without needing direct engineering assistance.First 12 Months Success IndicatorsLaunch innovative AI learning experiences that cater to a diverse range of learners.Enhance infrastructure that enables educators to offer adaptive learning and assessments.Validate the learning analytics pipeline for deeper insights into AI-driven education.Enable education teams to leverage AI tools for scalable development and iteration.

About Waymo Waymo develops autonomous driving technology with the goal of making transportation safer and more accessible. Originally launched in 2009 as the Google Self-Driving Car Project, Waymo has logged over 100 million autonomous miles and completed more than ten million rider-only trips. The company focuses on building the Waymo Driver to support safe, efficient travel across a range of vehicle platforms. Team Overview: Prediction & Planning - System Architecture The Predictive Planning (PrePlan) team builds machine learning systems that help the Waymo Driver anticipate possible scenarios and plan actions accordingly. By transforming large-scale driving data into robust deep neural networks, the team enables vehicles to navigate complex, real-world environments with confidence. The system architecture group ensures these models work smoothly within Waymo's technology stack. This includes attention to kinematics, interfaces, and data representations. The team works across projects involving data pipelines, model integration, evaluation metrics, and the planner systems that guide autonomous vehicles. Role Details Title: Staff Machine Learning Engineer, Prediction & Planning - System Architecture Location: Mountain View, CA; San Francisco, CA; New York City, NY (hybrid) Reports to: Technical Lead Manager

Your OpportunityJoin our innovative team at LM Studio as a Software Engineer specializing in AI/ML Systems. We seek a dynamic individual who thrives at the crossroads of machine learning and systems engineering, enjoys tackling complex challenges, and is dedicated to crafting exceptional products.In this role, you will be responsible for developing and enhancing on-device inference engines and integrations for local large language models (LLMs) and advanced AI technologies within LM Studio. You will design and maintain the runtime that facilitates on-device model inference, provide immediate support for new models on launch day, and optimize performance across diverse hardware setups.Collaboration is key here. You will engage closely with model authors and upstream open-source communities (such as llama.cpp, MLX, and others) to ensure that LM Studio users access cutting-edge AI experiences.If you're passionate about bridging the gap between models and systems and care about delivering outstanding local AI-powered experiences for both users and developers, this position could be your next great adventure!

About AdaptiveAdaptive Security stands at the forefront of AI cybersecurity, recognized as NVIDIA and OpenAI’s exclusive investment in this domain. Our mission is to thwart AI-driven cyberattacks. In December 2025, we proudly announced an $81M Series B funding round led by NVIDIA and Bain Capital Ventures, joined by esteemed investors including Capital One Ventures, Citi Ventures, and ongoing support from Andreessen Horowitz (a16z), the OpenAI Startup Fund, and Abstract Ventures. This round signifies NVIDIA’s inaugural foray into AI cybersecurity investments.Founded by seasoned entrepreneurs Brian Long and Andrew Jones, who have a proven track record of building and scaling industry-defining companies, Adaptive is set to shape the security landscape for the AI era. Brian and Andrew previously co-founded Attentive, which achieved over $500M in annual revenue and a valuation exceeding $10B, and TapCommerce, acquired by Twitter. Their wealth of experience in creating high-growth, product-focused businesses is instrumental as Adaptive secures enterprises against ever-evolving threats.With a growing clientele that includes leading banks, technology firms, and healthcare organizations, Adaptive is dedicated to safeguarding teams from emerging threats like deepfakes, smishing, and AI-generated voice scams. As we experience rapid enterprise adoption and explore a market exceeding $200B, we are just scratching the surface of our potential.Role OverviewWe are on the lookout for a Staff Machine Learning Engineer to spearhead the development of Adaptive's ML capabilities. As an AI cybersecurity firm, our products leverage LLMs and ML models to identify, classify, and respond to threats in real time. The role of ML is pivotal to the future of our offerings, and we seek an individual who can define our strategy, establish the infrastructure, and execute hands-on initiatives.Currently, we lack dedicated ML infrastructure or a team; you will have the unique opportunity to build this from the ground up. You will set the technical direction for ML applications across the organization, establish the necessary infrastructure, and engage in hands-on development.Key ResponsibilitiesCraft and define Adaptive's ML strategy: identify optimal applications of ML across our product suite, determine required infrastructure, and guide build vs. buy decisions.Design and implement end-to-end production ML systems, including data pipelines, model training, evaluation frameworks, and inference serving.Establish a robust evaluation methodology to measure model quality, identify regressions, and facilitate data-driven decisions regarding model modifications.Take ownership of data strategy: ensure the acquisition of necessary data in the required formats, define labeling processes, and establish feedback loops to enhance model performance over time.Collaborate with product engineers to integrate ML capabilities seamlessly into our products.

About the Role Waymo is looking for a Senior Machine Learning Engineer focused on Prediction & Planning to join the System Architecture team. This position is based in Mountain View, CA, San Francisco, CA, or New York City, NY. What You Will Do Design and implement advanced machine learning algorithms for autonomous vehicle prediction and planning. Develop systems that improve the safety and efficiency of self-driving technology. Collaborate with engineers and researchers across teams to advance core capabilities in autonomous driving. Impact Your work will help shape the systems that guide Waymo’s vehicles, supporting safer and more reliable autonomous transportation.

Join our dynamic team at Blacksmith as a Principal Systems Engineer, where you will play a crucial role in designing, developing, and implementing innovative systems solutions. Your expertise will guide projects from conception to execution, ensuring they meet both technical and user requirements.

Join Our Team at RebarRebar is revolutionizing the operating systems used by commercial HVAC, electrical, and plumbing suppliers and subcontractors. In the past year, our initial quoting product has successfully scaled to processing thousands of quotes weekly, and we've doubled our revenue in 2026 while gaining traction among top suppliers across North America. Fresh from securing a $14M Series A investment from leading construction technology investors, we are poised for our next growth phase with AI at the core of our innovations.We are seeking a Principal Deep Learning Engineer who possesses a strong background in modern neural network techniques and proficiency in PyTorch. You will be instrumental in advancing computer vision applications in real-world settings. As part of a tight-knit, highly skilled team, you will focus on delivering practical, production-ready machine learning systems—from building data pipelines to developing finely-tuned models—within a dynamic startup environment.This position is ideal for individuals who thrive on working closely with models, refining training workflows, and tackling novel engineering challenges. Our work transcends mere model inference; we create training workflows, develop robust evaluation pipelines, and construct systems that enhance standard model usage.

At Garner Health, we are dedicated to revolutionizing the healthcare economy by making high-quality and affordable care accessible to all.We are fundamentally reimagining the healthcare landscape in the U.S. by collaborating with employers to redesign healthcare benefits using transparent incentives and powerful, data-driven insights. Our innovative approach directs employees toward higher-quality, lower-cost care, fostering a healthcare system that benefits everyone. This means improved health outcomes for patients, more effective spending of healthcare dollars for employers, and rewarding physicians for providing exceptional care rather than performing unnecessary procedures.Garner is recognized as one of the fastest-growing healthcare technology companies nationally. Our products are trusted by the most sophisticated employers and providers in the industry, and we are building a team of talented, mission-driven individuals who are eager to make a significant impact on healthcare at scale.About the Role:We are on the lookout for an outstanding Staff Machine Learning Engineer to join our dynamic team. At Garner, our Engineering team addresses complex technical challenges that have a meaningful impact on our mission. Our systems analyze billions of medical records to evaluate healthcare providers nationwide. We operate on AWS with Kubernetes and consistently integrate new technologies as our system load grows exponentially each year. We encourage our engineers to advocate for cutting-edge industry practices as we wholeheartedly incorporate AI into every aspect of our operations and standards. We value teammates who take pride in delivering exceptional work and nurturing a robust team culture.Where You Will Work:This position is based in our New York City office located in the Financial District. Candidates must be available to work in the office three days a week: Tuesday, Wednesday, and Thursday.What You Will Do:Lead technical strategy and execution at the team level over multi-quarter time frames.Utilize AI to build, optimize, and maintain machine learning, data, and software systems.Elevate the technical capabilities of engineers throughout the organization.Collaborate across disciplines to deepen domain understanding and iterate on projects.Ensure user privacy and security through adherence to best practices.

Role Overview root-access is hiring a Machine Learning Engineer in New York City. This role works closely with the tech team to design and build machine learning algorithms that support and improve our products. The position involves hands-on development, data analysis, and delivering solutions that scale as our business grows. What You Will Do Develop machine learning models tailored to product needs Analyze complex data sets to extract insights and guide model improvements Create solutions that can scale to meet increasing demand Collaborate with engineers and product teams to integrate AI-driven features Who We’re Looking For Experience building and deploying machine learning algorithms Strong interest in artificial intelligence and its practical applications Ability to work with large, complex data sets Comfort working in a collaborative, evolving tech environment

About TennrAt Tennr, we are transforming the way healthcare referrals are managed. When patients are referred to specialists, they often face frustrating delays. Our innovative platform, powered by RaeLM™, ensures that every referral is processed swiftly and accurately, allowing healthcare providers to capture more referrals and reduce denials. Join us in revolutionizing the healthcare experience.About the RoleAs the pioneering ML Ops Engineer at Tennr, you will be instrumental in developing and refining our Machine Learning and AI infrastructure. You will be responsible for creating and optimizing machine learning training and inference pipelines that can manage escalating traffic demands and an expanding range of products. Your expertise will ensure that our AI-driven healthcare platform operates on robust, scalable, and efficiently deployed models.Our Machine Learning team is at the forefront of innovation, developing proprietary VLMs, LLMs, and other specialized models tailored to address critical healthcare challenges. This is not just a position of maintaining existing systems; it is an opportunity to lead groundbreaking experimentation and the introduction of new capabilities. Your contributions will significantly impact our ML and data systems, enhancing Tennr's ability to solve vital issues for patients and healthcare providers.Key ResponsibilitiesDesign, architect, and implement scalable ML software systems for model deployment and management.Maintain infrastructure that supports efficient ML operations, including data pipelines, model evaluations, and large-scale training.Work collaboratively with ML engineers, software developers, and cross-functional teams to integrate models seamlessly with data pipelines and products.Identify and resolve production issues while continuously enhancing system performance and efficiency.Develop tools for online and offline evaluation of ML and LLM systems.

Trunk Tools seeks a Senior Machine Learning Engineer to join its team onsite in New York City. This role centers on creating and deploying models that drive the company’s main objectives. Working alongside colleagues from various backgrounds is a key part of the job. Responsibilities Design and build machine learning models for practical use cases Collaborate with cross-functional teams to gather requirements and deliver effective solutions Deploy models into production environments and monitor their scalability Work Location This position is based at the Trunk Tools headquarters in New York City. Regular onsite presence is required.

Join Our Team as a Machine Learning Engineer! At FanDuel, we recognize that data is the lifeblood of our organization. As a Machine Learning Engineer, you will harness the power of our extensive real-time and relational datasets to drive insights that enhance user experiences. Your analytical skills will transform every interaction—from user clicks to game outcomes—into actionable intelligence, enabling us to make faster, more informed decisions that keep us ahead of the competition. Your role will be pivotal in fostering collaboration across teams. You will serve as the bridge between engineering teams, facilitating the development of our online applications while ensuring that essential data is available for feature engineering. Collaborating with Data Scientists and Analysts, you will help bring AI-driven insights into production and validate their effectiveness. Your efforts will be instrumental in organizing, modeling, and presenting data in a manner that provides a unified information structure, empowering FanDuel to respond intelligently to market dynamics and on-field events. If you are a Machine Learning Engineer with aspirations to thrive in a big data environment, we encourage you to apply! Your Responsibilities: Design and implement intelligent search systems incorporating typeahead search, vector search, and ML personalization to optimize user experience. Contribute to the creation of scalable serving systems for ML and GenAI/LLM models. Develop platform features and tools (e.g., CLI, SDK, Infrastructure Automation) that enhance the ML model lifecycle and GenAI/LLM application deployment. Utilize business intelligence tools such as Tableau, Knime, and Looker. Ensure data security and privacy compliance (e.g., GDPR, CPP). Implement data governance and testing frameworks. Support continuous integration and delivery of data products. Participate in an inclusive culture that prioritizes excellence, personal growth, and well-being.

About SandbarSandbar is a pioneering interface company based in New York City, dedicated to enhancing individual autonomy in an agentic world. Our team comprises experts who have developed cutting-edge software, machine learning, and hardware products at renowned companies like Meta, CTRL-labs, Google, Apple, Fitbit, Peloton, and Equinox.Our flagship product, Stream, represents a revolutionary human-agent interface—a private voice ring and conversational computer. This innovative product has received accolades in major publications such as the Wall Street Journal, Bloomberg, and Wired, with shipping scheduled for Summer '26.Join us in redefining self-augmentation through advanced interfaces.

OverviewAt OXMAN, a pioneering nature-focused research and design firm based in Manhattan, we leverage nature-centric solutions to tackle pressing challenges at the intersection of Nature and Humanity. Our interdisciplinary approach spans various sectors, fostering innovative concepts that redefine the interaction between the built environment and the natural ecosystem.Our initiative, EDEN, is dedicated to applied ecological systems operating on architectural, urban, and landscape scales. We are at the forefront of creating a digital design framework that engineers biodiverse and resilient ecosystems by developing software that empowers designers and engineers to incorporate essential ecosystem services—such as carbon sequestration, thermal buffering, and biodiversity—into their master planning and design processes. Our mission is to elevate ecosystem services from undervalued byproducts to vital infrastructure elements. We invite talented professionals to join us in revolutionizing the future of nature-centric design.We are currently seeking a Machine Learning Research Engineer to integrate into our dynamic design team in New York City. This role will be pivotal in supporting our efforts to deliver exceptional, data-driven design proposals utilizing EDEN’s innovative suite of ecosystem engineering tools.

At Confido, we are revolutionizing the AI infrastructure for consumer packaged goods (CPG) brands, streamlining everything from deductions to production planning. Our platform integrates cash applications, deductions, disputes, trade promotion management, forecasting, demand planning, and analytics into a cohesive system. The outcome is significant time savings, enhanced decision-making capabilities, and accelerated growth potential.We proudly serve over 200 brands, managing more than $20 billion in revenue, with clients like OLIPOP, Simple Mills, Dr. Squatch, and Tropicana.With our recent successful $15 million Series A funding round led by Footwork Ventures and Y Combinator, we are poised for rapid expansion.As a Staff AI / ML Engineer, you will play a crucial role in developing and implementing the core AI systems that power our platform, including LLM-driven document understanding and predictive models that assist brands in making informed decisions.This foundational position will involve direct collaboration with our CEO and CTO to define our long-term AI strategy and architecture.

About the Role qloo is looking for a Machine Learning Engineer focused on Large Language Models (LLMs) and personalization. This position is based in New York City. What You Will Do Design and build machine learning models to improve user experience and increase engagement. Work closely with teams across the company to implement advanced algorithms. Support data-driven decisions by contributing expertise in LLMs and personalization techniques. Collaboration This role involves frequent collaboration with cross-functional groups, including product and data teams.

About MercivMerciv is an innovative AI and data analytics startup committed to redefining how businesses leverage strategic intelligence. Our mission is to revolutionize the way organizations utilize data, derive insights, and make informed strategic decisions through state-of-the-art AI pipelines and dynamic forecasting tools.We envision a future where every business decision is backed by timely and relevant data, merging AI capabilities with human intuition. Our technology:Integrates various data sources into a unified intelligence layerEnhances human decision-making through autonomous AI analyticsReveals insights and opportunities often overlooked by traditional toolsPredicts outcomes and assists teams in navigating uncertainty with clarityEmpowers organizations to shape their markets proactively instead of merely reactingWe are developing robust, scalable, and genuinely intuitive solutions that empower teams across all levels of an organization, not just the data team. Having successfully raised $14M in seed funding, we have cultivated a strong engineering culture and are poised to launch publicly after nearly two years in stealth mode.About the TeamOur team is dedicated to building an agentic AI platform that transforms how enterprises engage with data. Merciv connects an organization’s entire data landscape with external sources—such as social media trends, industry reports, and consumer behavior signals—enabling swift insights and automating workflows that previously took analysts weeks.We prioritize simplicity in powerful tools. Every feature is designed to be intuitive, and every component is interactive. We want users to feel empowered and capable of achieving more with Merciv than ever before.Our agile, lean team thrives on innovation and the autonomy to make impactful decisions. We operate under a DRI (Directly Responsible Individual) model, where you will take ownership of major product features from conception to launch—not merely contributing to them. You will wear multiple hats, and this is by design.Our work environment fosters creativity and cutting-edge technology, ideal for those eager to influence the future of human-AI collaboration. If you are excited to be part of a fast-paced, innovative startup culture and make a significant impact on client businesses, Merciv is the perfect place for you. Join us as we broaden the horizons of retail intelligence and deliver unparalleled value to our clients.

About SandbarSandbar is a pioneering technology company based in New York City, dedicated to enhancing human capabilities in an agentic world. Our mission is to empower individuals to think, act, and move with freedom. Our innovative team has developed software, machine learning, and hardware solutions that have been instrumental in the success of leading companies such as Meta, CTRL-labs, Google, Apple, Fitbit, Peloton, and Equinox.Our flagship product, Stream, represents a groundbreaking human-agent interface—a private voice ring and conversational computer. Stream has garnered attention in prestigious publications like the Wall Street Journal, Bloomberg, and Wired, with shipments set to commence in Summer '26.We invite you to join us in shaping a new paradigm for self-augmentation.

Confido is revolutionizing the AI infrastructure that empowers Consumer Packaged Goods (CPG) brands by streamlining critical processes from deduction to production planning. Our integrated platform unifies cash application, deductions, disputes, trade promotion management, forecasting, demand planning, and analytics. This integration results in significant time savings, enhanced decision-making, and accelerated scaling capabilities.With over 200 trusted brands managing more than $20 billion in revenue—including notable names like OLIPOP, Simple Mills, Dr. Squatch, and Tropicana—Confido has demonstrated exceptional growth. Recently, we secured a $15 million Series A funding round led by Footwork Ventures and Y Combinator to further drive our expansion.As a Senior Machine Learning / AI Engineer, you will play a pivotal role in developing the AI systems that form the backbone of the Confido platform. Your responsibilities will span from LLM-powered document understanding to creating predictive models that assist brands in making informed decisions.You will collaborate closely with engineering and product teams to transition AI capabilities from research into practical applications.

Join Our Team as a Machine Learning Infrastructure EngineerAt Fauna Robotics, we are on the forefront of revolutionizing robotics through cutting-edge machine learning technologies. As a Machine Learning Infrastructure Engineer, you will play a pivotal role in constructing and enhancing the machine learning systems that drive our innovative robotic solutions. Your expertise will be essential in designing, managing, and optimizing the infrastructure required for training, evaluating, and deploying ML models that facilitate robot locomotion, perception, manipulation, navigation, and interaction with humans.This position is an exciting opportunity to work at the convergence of machine learning and systems engineering, ensuring that our ML training and deployment systems are resilient, efficient, and scalable as we transition from prototypes to fully functional production systems.