Staff Machine Learning Engineer - Conversion Visibility

Waymo is at the forefront of autonomous driving technology, driven by the mission to become the world’s most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has dedicated itself to developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access while preventing traffic-related fatalities. Our Waymo Driver is the backbone of our fully autonomous ride-hail service and is adaptable across a variety of vehicle platforms and applications. To date, we have successfully completed over ten million rider-only trips, supported by our extensive experience of driving autonomously for more than 100 million miles on public roads and tens of billions of miles in simulation across over 15 U.S. states.The Driver Understanding and Evaluation team at Waymo focuses on deeply understanding the Waymo Driver’s behavior. With an impressive rate of over 1 million driverless miles per week, it is essential for Waymo to analyze and evaluate the behavior of its vehicles—both in real-world scenarios and simulations—using automated algorithms. Our learned metrics team plays a crucial role in leveraging machine learning to scale our operations to meet Waymo's ambitious goals. We work collaboratively across teams to integrate machine learning into production systems and establish the reward function for Waymo. Our team designs and manages large-scale machine learning systems, data infrastructures, simulation workflows, and analytical tools. By combining expert human insights with advanced machine learning models, we provide critical training and evaluation data for the Waymo Driver. We are on the lookout for passionate researchers and software engineers dedicated to creating robust machine learning systems for our autonomous vehicles, with a relentless pursuit of enhancing the performance of our technology stack.

We are looking for a talented individual who is local to any of our offices (Silver Spring, NYC, SF, Miami, Denver) and is eager to work at least 1-2 times per week from one of these locations.ABOUT ROCKET MONEY At Rocket Money, our mission is to empower individuals to take control of their financial lives. We provide our members with unparalleled insights into their finances and a suite of services that save them both time and money, enabling them to achieve their financial goals.ABOUT THE TEAM As Machine Learning Engineers at Rocket Money, we play a vital role in enhancing customer engagement with our diverse range of financial products. Our responsibilities include transaction enrichment, personalization, and creating cross-functional tools that bolster various AI initiatives. Collaborating closely with product teams, we develop features that aid customers in understanding, tracking, and improving their personal finances. We value team players who excel in cross-team collaboration, can align strategy with ML and AI-driven user experiences, deliver scalable and high-quality user experiences, and are mindful of the impact our products have on end users. At the Staff level, you will be expected to cultivate broad expertise in our products and the ML solutions that enhance them, while driving technical advancements within the team.ABOUT THE ROLE As a Staff Machine Learning Engineer, you will spearhead our ML and AI product development efforts, utilizing your expertise to design, implement, and maintain sophisticated ML systems that elevate our product experiences. Your responsibilities will include:Leading the architecture and development of advanced AI and ML features across Rocket Money's product suite, proactively identifying and addressing technical challenges.Designing and maintaining robust evaluation frameworks to ensure continual improvement of ML/AI systems and facilitating similar initiatives among others.Creating innovative product experiences that leverage our unique dataset and scalability, guiding others in delivering impactful results through effective technical leadership and collaboration with product teams.Overseeing the end-to-end development and implementation of ML and AI product features in partnership with cross-functional product teams, emphasizing thorough technical critique and clear communication of business impacts.Providing technical mentorship to foster an environment of high-impact contributions from all team members.

Join us in creating the most dependable on-demand logistics engine for last-mile retail delivery! We are on the lookout for a seasoned machine learning engineer to aid in the development of cutting-edge growth and personalization models that will elevate DoorDash's expanding retail and grocery services.About the RoleWe are seeking a dedicated Applied Machine Learning expert to become part of our innovative team. As a Staff Machine Learning Engineer, you will conceptualize, design, implement, and validate algorithmic enhancements that enrich the growth and personalization experiences central to our rapidly evolving grocery and retail delivery business. Leveraging our advanced data and machine learning infrastructure, you will implement novel ML solutions to enhance the consumer search experience, making it more relevant, seamless, and enjoyable across grocery, convenience, and various retail sectors. A strong command of production-level machine learning and proven experience in addressing end-user challenges while collaborating effectively with multidisciplinary teams is essential.This position will report to the engineering manager on our Personalization team and is expected to be hybrid, combining both in-office and remote work (#LI-Hybrid).

Join Decagon as a Staff Software Engineer specializing in Machine Learning Infrastructure. In this role, you will play a crucial part in enhancing and optimizing our machine learning systems. You will collaborate with a talented team of engineers to build scalable and efficient infrastructure that supports our AI-driven initiatives.As a key contributor, you will leverage your expertise in software engineering and machine learning to solve complex challenges and drive innovation. Your work will impact various projects and help shape the future of our technology.

About FaireAt Faire, we are revolutionizing the wholesale marketplace with an unwavering commitment to local communities. Our platform empowers independent retailers globally, enabling them to thrive against larger competitors like Walmart and Amazon. By leveraging cutting-edge technology, data insights, and machine learning, we connect these vibrant entrepreneurs with the best products from around the world. We believe that with the right tools, small businesses can elevate their potential and compete on a grand scale.By nurturing independent businesses, Faire is making a significant positive impact on local economies worldwide. We are in search of intelligent, resourceful, and passionate individuals to join our mission of championing local commerce. If you resonate with our community-driven values, we'd love to welcome you to our team.About this roleAs a Staff Machine Learning Platform Engineer, you will play a pivotal role in shaping, enhancing, and managing a scalable machine learning platform designed to expedite model training, deployment, and governance. You will serve as the vital technical link between our data science and production engineering teams. Joining a small but integral team, you will amplify Faire’s capabilities to support tens of thousands of local businesses in an increasingly competitive retail landscape.

Join Hive as a Senior Machine Learning Engineer and help shape the future of AI! We are seeking passionate individuals who excel at developing and deploying cutting-edge deep learning models. In this role, you will work with large-scale datasets to create innovative machine learning solutions, collaborating closely with a talented team of engineers to push the boundaries of artificial intelligence. Ideal candidates will have a proven track record of building and scaling machine learning projects from conception to production, along with a strong commitment to continuous learning and personal ownership in their work.

Airbnb began in 2007 with two hosts and three guests in San Francisco. Since then, the platform has grown to over 5 million hosts and more than 2 billion guests worldwide. Airbnb connects people with unique places to stay and experiences, building authentic community connections across nearly every country. The team: Growth Platform Engineering The Growth Platform team focuses on driving sustainable, long-term growth for Airbnb. The team’s mission centers on building an agentic system and supporting capabilities to help all Airbnb offerings grow, both now and in the future. Efforts include delivering personalized and relevant content and product experiences to users, both on and off the Airbnb platform. The team is working toward a future where AI identifies opportunities, creates campaigns, personalizes experiences, and optimizes outcomes with minimal human input. This journey moves through a maturity curve: AI-assisted, agentic, and ultimately autonomous systems, always with human oversight to ensure brand safety, quality, and compliance. Growth Platform Engineering is tightly integrated with the Airbnb product, enhancing the customer journey and enabling new ways for users to engage. The platform supports a range of digital marketing channels, landing pages, email, push notifications, SMS, and digital advertising, as well as the machine learning and data infrastructure that powers these efforts. What you will do Develop AI-driven solutions to shape the future of Airbnb’s agentic growth platform, using the latest AI methodologies. Lead and mentor engineers through brainstorming, design, and implementation of AI products and features, from initial concept to deployment. Work at the intersection of technical depth, architectural innovation, and mentorship as a Senior Staff Engineer. Collaborate with cross-functional teams to build scalable systems that operate globally. Help evolve the foundational elements of Airbnb’s AI-powered growth systems.

About Us:At Ambience Healthcare, we aspire to redefine healthcare technology. We are creating an AI intelligence platform that brings humanity back to healthcare while delivering significant ROI for health systems nationwide.Our cutting-edge technology enables healthcare providers to concentrate on exceptional patient care by alleviating the administrative tasks that detract from their critical responsibilities. Ambience provides real-time, coding-aware documentation and clinical workflow support across various healthcare settings, including ambulatory, emergency, and inpatient environments, partnering with top health systems across North America.We are relentless in our pursuit of excellence, exhibiting extreme ownership as we develop optimal solutions for our health system partners. We value transparency, positivity, and profound insight — holding each other to high standards because the challenges we tackle are of utmost importance.Ambience has been recognized as the leading company for improving clinician experience in the KLAS Research Emerging Solutions Top 20 Report, named one of the Next Big Things in Tech by Fast Company, and selected as one of the best AI companies in healthcare by Inc. Additionally, we were honored as a LinkedIn Top Startup in 2024 and 2025. Our esteemed investors include Oak HC/FT, Andreessen Horowitz (a16z), OpenAI Startup Fund, and Kleiner Perkins — and we’re just getting started.The Role:As a Staff Machine Learning Engineer on the Frontier AI team at Ambience, you will tackle the most challenging model quality issues across our clinical AI products, including foundational coding models, adaptive scribing, voice agents, long-context chart understanding, and clinical reasoning. This role focuses on research direction, designing learning loops, and driving comprehensive improvements in model quality over time.Ambience delivers advanced clinical AI solutions in real-world healthcare environments. The models that fuel our products operate under unique constraints, including proprietary ontologies, complex electronic health record (EHR) data, stringent compliance requirements, and clinician workflows where both latency and accuracy are critical. You will leverage your deep research instincts and engineering rigor to push the boundaries of what is possible.Our engineering roles are hybrid, requiring in-office attendance at our San Francisco location three days a week.

About Scale AI At Scale AI, we are dedicated to propelling the advancement of AI applications. Over the past eight years, we have established ourselves as the premier AI data foundry, supporting groundbreaking innovations in fields such as generative AI, defense technologies, and autonomous vehicles. Following our recent Series F funding round, we are intensifying our efforts to harness frontier data, paving the way toward achieving Artificial General Intelligence (AGI). Our work with enterprise clients and governments has enhanced our model evaluation capabilities, allowing us to expand our offerings for both public and private evaluations. About the ACE Team The Agent Capabilities & Environments (ACE) team, a vital part of Scale’s Research organization, unites customer-focused Researchers and Applied AI Engineers. Our primary mission is to conduct research on agent environments and reinforcement learning reward signals, benchmark autonomous agent performance in real-world contexts, and develop robust data programs aimed at enhancing the capabilities of Large Language Models (LLMs). We are committed to creating foundational tools and frameworks for evaluating models as agents, focusing on autonomous agents that interact dynamically with a wide range of external environments, including code repositories and GUI interfaces. About This Role This position sits at the cutting edge of AI research and its practical applications, concentrating on the data types necessary for the development of state-of-the-art agents, including browser and software engineering agents. The ideal candidate will investigate the data landscape required to propel intelligent and adaptable AI agents, steering the data strategy at Scale to foster innovation. This role demands not only expertise in LLM agents and planning algorithms but also creative problem-solving skills to tackle novel challenges pertaining to data, interaction, and evaluation. You will contribute to influential research publications on agents, collaborate with customer researchers, and partner with the engineering team to transform these advancements into scalable real-world solutions.

JOIN THE REVOLUTION AT MITHRLImagine a world where groundbreaking medicines reach those in need within months, not years, and where scientific innovations occur at lightning speed.Mithrl is pioneering the world's first commercially available AI Co-Scientist, a transformative discovery engine that swiftly converts complex biological data into actionable insights. By posing questions in natural language, scientists receive rapid, meaningful analyses, innovative targets, hypotheses, and ready-to-file reports.OUR IMPACT IS EVIDENT:Achieved 12X year-over-year revenue growthTrusted by top biotech firms and major pharmaceutical companies across three continentsCatalyzing substantial advancements from target identification to patient outcomes.ROLE OVERVIEWWe are seeking a talented Machine Learning Engineer to focus on Analysis and Simulation to construct the foundational analytical and reasoning framework for the Mithrl AI Co-Scientist. Your contributions will shape how our AI interprets biological datasets, formulates scientific conclusions, and integrates simulation tools for drug discovery.You will create reusable analysis modules that will be applied across all datasets and design complex workflows that merge statistical analysis, biological reasoning, and computational modeling. Additionally, you will explore and optimize simulation tools for small molecule discovery, including ADMET predictions, docking scores, Boltzmann generators, and various computational chemistry engines.This position is critical in enhancing the intelligence of the AI Co-Scientist. If you possess a solid foundation in machine learning, computational biology, and scientific analysis workflows, and are eager to influence how AI interprets biological systems, we invite you to apply.RESPONSIBILITIESDevelop AI-powered analysis agents capable of performing complex biological reasoning across diverse datasets.Create a standardized analysis suite for each dataset, encompassing modules for differential expression, pathway analysis, feature importance, clustering, scoring, enrichment, and mechanism-of-action interpretation.Engineer multi-step workflows integrating machine learning models, statistical logic, and biological expertise to yield high-confidence insights.Design and implement intelligent reasoning strategies that enable Mithrl to execute numerous analyses per dataset.

Join Orchard as a Machine Learning Engineer and play a pivotal role in transforming data into actionable insights. In this dynamic position, you will leverage your expertise in machine learning algorithms and data analysis to develop innovative solutions that enhance our products and services.We are looking for a proactive team player who thrives in a fast-paced environment and possesses strong problem-solving skills. You will collaborate with cross-functional teams, engage with large datasets, and contribute to the design and implementation of machine learning models.

The Bot CompanyJoin us in creating a revolutionary robot designed to enhance everyday living.Based in San Francisco, our dynamic team consists of talented engineers, designers, and operators hailing from industry leaders like Tesla, Cruise, OpenAI, Google, and Pixar. We've successfully delivered exceptional products and experiences to hundreds of millions of users.Our deliberately streamlined team structure fosters prompt decision-making, eliminating bureaucracy and hierarchy. Each team member is an individual contributor empowered with significant scope, radical ownership, and direct accountability, working collaboratively across the stack in a fast-paced environment focused on rapid iteration and execution.What We Value in CandidatesAt The Bot Company, we seek individuals who exhibit remarkable sharpness and can thrive in high-pressure situations. Throughout the selection process, we expect candidates to showcase:Exceptional mental acuity: You think quickly, absorb information rapidly, and navigate unfamiliar domains with ease.Engineering curiosity: You possess an innate desire to understand system functionalities, extending beyond your primary expertise.High performance mindset: You excel in ambiguous environments and maintain high productivity under challenging conditions.Machine Learning Engineer: World ModelsWe are developing neural simulators capable of comprehending the fundamental

As a Technical Staff Member specializing in Machine Learning, you will:Engage in the complete development lifecycle of innovative large-scale deep learning models.Curate datasets, architect solutions, implement algorithms, and train and assess models to enhance our offerings.Work collaboratively with engineers and researchers to convert groundbreaking research into real-world applications.Join us at a pivotal time, take on diverse roles, and contribute to building transformative products from the ground up!

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the most trusted driver globally. Originating from the Google Self-Driving Car Project in 2009, our primary goal has been to develop the Waymo Driver—The World’s Most Experienced Driver™. Our innovations aim to enhance mobility access while saving countless lives lost to traffic accidents. The Waymo Driver powers our fully autonomous ride-hail services and is adaptable across various vehicle platforms and product applications. Having completed over ten million rider-only trips, our technology has autonomously navigated over 100 million miles on public roads and executed tens of billions of miles in simulations across more than 15 U.S. states.Your Role:Lead the technical strategy for the Simulator’s issue response lifecycle, encompassing automated detection, root cause analysis, and the deployment of both temporary and permanent software solutions to prevent future regressions.Direct complex, cross-functional projects to enhance automated issue detection by integrating new data sources and signals, thus reducing the time from an in-field event to mitigation deployment.Work closely with Data Science, Systems Engineering, and operations teams to improve technical processes and tools, accelerating the deployment and validation of solutions for identified issues.Mentor mid-level and junior engineers on sophisticated technical challenges, best practices in system architecture, and high-quality software development, serving as a technical force multiplier.

Join Patreon as a Staff Machine Learning Engineer specializing in Taxonomy. In this pivotal role, you will leverage your advanced knowledge in machine learning and data science to enhance our taxonomy systems, providing value to creators and patrons alike. You will work collaboratively with cross-functional teams to design and implement innovative solutions that drive our mission forward.

Supported by top-tier Silicon Valley investors, Peregrine Technologies empowers public safety organizations, local and state governments, federal agencies, and private entities to tackle societal challenges with unmatched speed and precision. Our AI-driven platform transforms fragmented and isolated data into actionable operational intelligence, enabling immediate access to critical information that enhances decision-making processes. Currently, Peregrine serves hundreds of clients across more than 30 states and two countries, positively impacting over 125 million individuals as we extend our influence into the enterprise sector and beyond.TeamWe believe that empathy is key in engineering. Understanding how users engage with our product is vital to our success. Our engineers collaborate closely with on-site teams to grasp the diverse use cases that Peregrine addresses.We prioritize both ownership and teamwork, encouraging you to take accountability for significant features while working alongside fellow engineers to bring them to fruition. We value humility and empathy as essential traits in developing effective solutions, engaging directly with our deployment teams and users to iteratively resolve their challenges. Creativity and perseverance are critical to realizing our vision.RoleAs a crucial member of our engineering team, you'll play a pivotal role in delivering exceptional value to our customers. This team focuses on creating robust, user-friendly experiences powered by generative AI. You will pioneer innovative interactions for users within our platform, shaping impactful AI-driven features that assist clients in solving real-world problems swiftly and efficiently.Your responsibilities will encompass addressing a variety of complex challenges, including scaling our platform to manage terabytes of data from multiple sources, providing real-time user notifications and queries, and optimizing search algorithms for rapid result delivery.Our technology stack is continually evolving, anchored by a backend built with Python, Django, Celery, Airflow, and Kafka; a frontend utilizing React, Redux, and Mapbox; data storage solutions including PostgreSQL and Elasticsearch; machine learning models hosted in Bedrock and SageMaker; along with AWS, Pulumi, Terraform, and Kubernetes forming our infrastructure.About YouEnthusiasm and ambition to take ownership of major projects and contribute to the team's success.

Join Handshake as a Machine Learning Engineer I, where you will have the opportunity to work on cutting-edge machine learning projects that drive our innovative solutions. Collaborate with a talented team to develop algorithms and models that enhance our product offerings and improve user experiences.

Join Our Innovative Team at HiveHive is at the forefront of cloud-based AI solutions, revolutionizing how organizations understand, search for, and generate content. Trusted by many of the world's largest and most groundbreaking companies, we empower developers with premier pre-trained AI models that handle billions of API requests monthly. Our turnkey software applications leverage proprietary AI models and datasets, driving transformative advancements in content moderation, brand protection, sponsorship measurement, and context-based ad targeting.With over $120M in funding from prominent investors like General Catalyst, 8VC, Glynn Capital, Bain & Company, and Visa Ventures, Hive is rapidly expanding. Our dynamic team of over 250 employees operates from our San Francisco, Seattle, and Delhi offices. If you are passionate about shaping the future of AI, we invite you to explore opportunities with us!About the Machine Learning Engineer RoleAs we strive to achieve our ambitious vision, we seek exceptional machine learning engineers to join our team. We are looking for enthusiastic developers who are eager to remain at the cutting edge of deep learning technology, designing and deploying state-of-the-art neural network models into production. Our ideal candidates thrive in working with large-scale datasets and demonstrate a keen interest in mastering new technologies across the machine learning spectrum. We value individuals who are proactive and take ownership of their projects, contributing innovative ideas and practical implementations. Experience in building machine learning applications from the ground up and designing scalable, maintainable data pipelines is essential.

Join our dynamic Personalization team at Boomtrain as a Machine Learning Engineer. We are in search of a skilled engineer who will play a pivotal role in developing and enhancing our recommendation systems that cater to a variety of customers.In this role, you will collaborate with a talented team dedicated to designing and implementing innovative models and systems that deliver personalized recommendations. You will have the opportunity to work on complex engineering challenges and contribute to generating hundreds of millions of recommendations daily.This position offers a unique chance to engage in end-to-end project work and make a significant impact on our personalization initiatives.Key Responsibilities:Research and propose advanced recommendation and optimization models to enhance our personalization systems.Develop and maintain offline model generation pipelines.Design and maintain online recommendation serving systems.