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Experience Level
Senior
Qualifications
• Proven experience in software engineering, particularly in machine learning infrastructure.• Proficiency in programming languages such as Python, Java, or C++.• Familiarity with ML frameworks and tools (e.g., TensorFlow, PyTorch).• Strong understanding of cloud platforms (AWS, Azure, or Google Cloud).• Excellent problem-solving skills and the ability to work in a team-oriented environment.• A Bachelor's or higher degree in Computer Science, Engineering, or related fields.
About the job
Join Decagon as a Senior Software Engineer specializing in Machine Learning Infrastructure. In this pivotal role, you will be responsible for designing and optimizing systems that support machine learning models and applications. Your expertise will help drive innovation and efficiency in our ML pipelines, ensuring that our algorithms are fast, scalable, and reliable.
You'll collaborate with cross-functional teams to implement cutting-edge solutions that enhance our product offerings. If you are passionate about advancing machine learning technologies and thrive in a dynamic environment, we want to hear from you!
About Decagon
Decagon is at the forefront of technology innovation, dedicated to using data and machine learning to make impactful decisions. Based in the heart of San Francisco, we foster a culture of creativity and collaboration, empowering our employees to push boundaries and achieve excellence.
Full-time|$137.1K/yr - $246.8K/yr|Hybrid|San Francisco, CA; Sunnyvale, CA
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…
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.
Full-time|$200K/yr - $275K/yr|On-site|San Francisco, CA
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.
About NudgeAt Nudge, our goal is to create innovative technologies that connect with the brain, enhancing individuals’ lives. We’re pioneering a non-invasive, ultrasound-based device designed to stimulate and image the brain with high precision and depth. This initiative involves developing state-of-the-art hardware, software, and research capabilities to deliver products that can positively impact millions — and eventually billions — of people.About the RoleAs a Machine Learning Software Engineer at Nudge, you will:Engineer imaging algorithms utilizing proprietary ultrasound transducers and advanced computing resources to visualize the brain and skull.Create sophisticated acoustic simulations to model sound scattering in the skull, enabling precise dose predictions.Develop real-time computer vision systems to monitor brain target movements and dynamically adjust parameters to ensure accurate targeting.Collaborate closely with mechanical, electrical, and ultrasound engineers, as well as transducer designers and neuroscientists.About YouWe are searching for engineers of all experience levels, with a preference for those boasting a minimum of three years in the industry. Regardless of your experience, you should possess:A solid understanding of engineering principles, physics, and signal processing.Proficiency in writing production-level code, preferably in Python.A degree in Computer Science or a related engineering field.No prior experience in ultrasound or neuroscience is required.Experience in delivering real-world products that provide tangible value; ideally, you have dealt with complex real-world sensors.A high level of integrity.
Full-time|$210K/yr - $260K/yr|Hybrid|San Francisco, CA, Washington, D.C., New York City, N.Y., Denver, CO
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.
Role Overview Voxel is hiring a Senior or Staff Software Engineer focused on Machine Learning Infrastructure in San Francisco, CA. This position centers on building and maintaining scalable infrastructure that supports the company’s machine learning products and services. What You Will Do Design, develop, and maintain machine learning infrastructure for production systems Work with teams across engineering, product, and data to streamline ML workflows Optimize systems for performance, reliability, and operational efficiency Collaboration This role involves frequent collaboration with colleagues from multiple disciplines to ensure machine learning solutions are robust and scalable.
Role overview Whatnot seeks a Software Engineer specializing in Machine Learning Infrastructure to develop and maintain the systems powering its machine learning applications. This position is based in San Francisco, CA and centers on building the technical backbone that supports machine learning efforts across the company. What you will do Develop and improve frameworks that enable machine learning throughout Whatnot’s platforms. Collaborate with teams from multiple disciplines to design infrastructure that can scale as needs grow. Support seamless integration of machine learning models into existing products.
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.
Full-time|$250K/yr - $250K/yr|Hybrid|San Francisco
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.
Join our innovative team at Twitch as a Software Engineer I specializing in Monetization Machine Learning. In this role, you will contribute to the development of cutting-edge algorithms and data-driven solutions that enhance user experience and maximize revenue generation. As part of our dynamic environment, you will have the opportunity to work on exciting projects that directly impact our platform and community.
Role overview MidiHealth is hiring a Staff Software Engineer - AI Engineer for a hybrid role in the San Francisco Bay Area. The position focuses on building and improving AI-powered solutions that contribute to better healthcare outcomes. What you will do Collaborate with cross-functional teams to design and implement AI-driven systems for healthcare. Develop scalable architectures and write efficient algorithms tailored to healthcare applications. Uphold strong software quality standards throughout the development lifecycle. Location This position is hybrid, with work based in the SF Bay Area.
About UsAt XOXO AI, we are at the forefront of innovation, crafting intelligent interfaces that seamlessly integrate into everyday life. As a dynamic research lab comprised of dedicated engineers, designers, and researchers, we tackle unique challenges that extend beyond the workplace.Having achieved significant breakthroughs in infrastructure, architecture, and model layers, we are looking for passionate builders to help us realize our vision through the development of robust interface and application layers.About the RoleWe seek a talented Data/Machine Learning Engineer to establish our data infrastructure and production-ready ML systems, ensuring our product is responsive, dependable, and intelligent. This full-cycle role involves designing high-throughput pipelines, defining resilient data models, and deploying low-latency feature and model serving that can withstand real-world demands.You will collaborate closely with our founders and the early engineering team to transition prototypes into production, transforming complex real-world signals into reliable datasets and real-time functionalities that enhance core product experiences.What You’ll DoDevelop and manage high-throughput batch and streaming pipelines for analytics, training, and product signals.Lead real-time feature pipelines and online feature serving for low-latency inference.Design and oversee dimensional data models, skillfully managing schema evolution to avoid disrupting downstream consumers.Optimize model serving infrastructure to meet stringent latency and reliability service level objectives (SLOs).Establish and enforce event schemas, telemetry standards, and data contracts across multiple teams.Collaborate with engineering, product, and research teams to translate ambiguous product requirements into measurable, sustainable systems.
Full-time|$275K/yr - $350K/yr|On-site|San Francisco, CA; Seattle, WA; New York, NY
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 Decagon as a Senior Software Engineer specializing in Machine Learning Infrastructure. In this pivotal role, you will be responsible for designing and optimizing systems that support machine learning models and applications. Your expertise will help drive innovation and efficiency in our ML pipelines, ensuring that our algorithms are fast, scalable, and reliable.You'll collaborate with cross-functional teams to implement cutting-edge solutions that enhance our product offerings. If you are passionate about advancing machine learning technologies and thrive in a dynamic environment, we want to hear from you!
Company Overview At Specter, we are pioneering a software-defined "control plane" designed to enhance the real-world perception of physical assets. Our mission begins with safeguarding American businesses by providing them with comprehensive insights into their physical environments.To achieve this, we are developing a robust hardware-software ecosystem leveraging multi-modal wireless mesh sensing technology. This innovation allows us to significantly reduce the cost and time involved in sensor deployment by a factor of ten. Ultimately, our platform aims to serve as the perception engine for businesses, facilitating real-time visibility and autonomous management of their operational perimeters.Our co-founders, Xerxes and Philip, are deeply committed to empowering our partners in the rapidly evolving landscape of physical AI and robotics. We are a dynamic, rapidly expanding team comprised of talent from Anduril, Tesla, Uber, and the U.S. Special Forces.Position Overview Specter is seeking a dedicated Machine Learning Infrastructure Engineer to construct and optimize the ML systems that drive real-time perception and inference capabilities across our edge-cloud platform. This position will involve overseeing the training, deployment, and enhancement of computer vision and sensor fusion models, aimed at enabling autonomous monitoring and decision-making for our clients' physical assets.Key Responsibilities Include:Design and implement scalable ML training pipelines for computer vision applications, including object detection, tracking, classification, and segmentation.Develop efficient model serving infrastructures to facilitate real-time inference on edge devices with limited computational and power resources.Optimize models for deployment on embedded hardware, employing techniques such as quantization, pruning, TensorRT, ONNX, and CoreML.Create continuous training and evaluation systems to enhance model performance through feedback loops derived from production data.Establish data pipelines for the ingestion, labeling, versioning, and management of extensive multi-modal sensor datasets, including video, radar, lidar, and thermal data.Implement model monitoring frameworks, A/B testing methodologies, and performance analytics for deployed perception systems.Collaborate with perception researchers to transition models from research environments to scalable production across thousands of edge nodes.Construct tools and infrastructure for distributed training, hyperparameter optimization, and experiment tracking.
Full-time|On-site|San Francisco Bay Area (San Mateo) or Boston (Somerville)
About the RoleIn this exciting position, you will address comprehensive challenges to enhance the performance of our AI models deployed on robotic systems. Your responsibilities will include adding new features to our video processing data pipeline, updating our machine learning data loaders, training models to validate your modifications, and testing these changes in real-world robotic applications. This role requires the integration of numerous distributed Python services to achieve specific data processing and application tasks, alongside managing substantial cloud infrastructure for efficient business logic processing at scale.Your responsibilities will include:Conceptualizing and implementing innovative solutions to enhance system robustness, scalability, and speed.Revamping existing systems and services to accommodate significant future growth.Developing business logic to ensure our robots access the necessary data and that customers receive appropriate access to our robotic solutions.You may excel in this role if you:Possess extensive experience in building complex distributed applications or data pipelines at scale.Have a background in processing petabytes of data, especially video data.Demonstrate expertise in Python, with foundational knowledge in distributed infrastructure and solid understanding of modern machine learning principles.Have a robust foundation in contemporary ML techniques with experience in large-scale ML training and production deployments.Have familiarity with distributed cloud infrastructure and a deep understanding of cloud networking, permissions, and container orchestration (Kubernetes).About GeneralistAt Generalist, our mission is to realize the potential of general-purpose robots. We envision a future where industries and homes thrive on the collaboration between humans and machines. Our robots are designed to enhance productivity and efficiency.We focus on developing embodied foundation models, starting with dexterity, which necessitates pushing the boundaries of data, models, and hardware to enable robots to intelligently interact with their environments.Our company is deeply rooted in large-scale AI and robotics, with a team drawn from leading organizations like OpenAI, Boston Dynamics, and Google DeepMind, all committed to delivering groundbreaking advancements in AI technology.
Full-time|$220K/yr - $247.5K/yr|On-site|San Francisco Bay Area
Discord is a vibrant platform utilized by over 200 million individuals each month for various activities, with one common passion uniting them: gaming. An astounding 90% of our users engage in gaming, collectively dedicating 1.5 billion hours to a diverse array of titles on Discord every month. We envision Discord as a pivotal player in the future of gaming, dedicated to enhancing communication and camaraderie among players before, during, and after their gaming sessions.We are in search of a Senior Machine Learning Engineer to become a key member of our Revenue ML team at Discord. This role is strategically positioned at the crossroads of our two primary revenue initiatives — our expanding first-party Shop and our newly introduced Game Commerce platform, which connects players to in-game items from renowned publishers such as Marvel Rivals, Fortnite, Valorant, and many others. You will be the pioneering ML expert for commerce discovery and personalization, constructing systems from scratch that will drive recommendations, social commerce features, and targeted marketing across both our first-party and third-party storefronts.This position is high-impact and offers significant leverage. Discord’s social ecosystem provides us with a distinct commercial advantage — robust social graphs, enthusiastic fan communities, and an inherent gaming context — and you will be the visionary who transforms this into ML-driven products that generate substantial GMV growth.Key Responsibilities:Develop and oversee the ML infrastructure for commerce discovery, including user, item, and interaction embeddings that facilitate personalized recommendations across various shop interfaces (homepage, cart, post-purchase, wishlist, etc.).Create and implement scalable real-time recommendation and ranking systems that efficiently manage a growing catalog of first-party and third-party items from diverse game publishers.Build ML-enhanced marketing targeting systems that accurately identify the ideal users for tailored campaigns — such as new buyer discounts, drop campaigns, weekly deals, and seasonal promotions — driving conversion rates without conditioning users to expect discounts.Utilize Discord's unique social graph to innovate social commerce ML applications: predicting gifting recipients, modeling group buying conversions, and generating friend-group recommendations that set Discord apart from traditional game storefronts.Lead the development of deep learning A/B testing infrastructure and model monitoring to convert experimentation insights into actionable product strategies.Collaborate closely with Shop, Game Commerce, Revenue Infra, ML Infra, and Data Engineering teams to outline ML requirements, identify integration points, and influence the commerce roadmap.
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.
Full-time|On-site|San Francisco, California, United States
Rockstar is on the hunt for a talented Backend Software Engineer to join a rapidly expanding startup that is pioneering the AI infrastructure for the next generation of smart products. This innovative company specializes in providing AI startups with the tools to design, fine-tune, evaluate, deploy, and maintain their specialized models across various domains like text, vision, and embeddings. Think of them as the 'AWS for AI models'—offering a comprehensive backend solution for fine-tuning, reinforcement learning, inference, and ongoing model maintenance. Their clientele includes Series A to C AI companies that are developing enterprise-grade products, with a simple promise: to enhance your AI systems.As a Backend Software Engineer focusing on ML Infrastructure, you will play a pivotal role in designing, building, and scaling the essential systems that facilitate extensive model training and deployment.Your responsibilities will include developing distributed training pipelines, establishing cloud-native infrastructure, and creating internal developer platforms that support fine-tuning, reinforcement learning, and inference at scale. This position uniquely combines backend engineering with machine learning systems, allowing you to work closely with ML engineers while taking ownership of production-grade infrastructure.This role is a fantastic opportunity for an early-career engineer eager to dive into real distributed systems, GPU workloads, and cutting-edge ML infrastructure—far removed from simple dashboards or CRUD applications.
