Machine Learning Engineer

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.

About Atomic SemiAtomic Semi is revolutionizing the semiconductor industry by creating a compact, high-speed semiconductor fabrication facility. Leveraging existing technology and innovative simplifications, we are committed to developing our own tools to enable rapid iteration and continuous improvement.We are assembling a select group of talented, hands-on engineers across various disciplines—mechanical, electrical, hardware, computer, and process engineering. Our mission is to maintain ownership of the entire technological stack, from atomic structures to architectural design. Our optimistic team is dedicated to pushing the boundaries of technology.We believe that smaller, faster, and self-created solutions are superior. Our lab is equipped with advanced 3D printers, diverse microscopes, e-beam writers, and general fabrication tools. If we identify any gaps, we will create the necessary innovations ourselves.Founded by Sam Zeloof and Jim Keller, Atomic Semi combines Sam's garage chip-making expertise with Jim's 40 years of leadership in the semiconductor industry.About the RoleAs a Data & Machine Learning Engineer, you will develop systems that utilize fabrication data to enhance, monitor, and optimize our manufacturing processes. This role primarily involves converting raw data into actionable insights that drive improvements in yield, reliability, and throughput.

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.

Join Matter Intelligence as a Data and Machine Learning Infrastructure Engineer, where you will play a pivotal role in shaping the future of data-driven decision-making. You will be part of a dynamic team focused on building and optimizing infrastructure that supports innovative machine learning applications. Your expertise will help us enhance our data pipelines and ensure seamless integration of machine learning models into production.

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 Hilbert, a pioneering data science-driven growth engine that empowers B2C teams with predictive insights into user behaviors, revenue drivers, and sustainable growth strategies. Our innovative approach compresses lengthy decision-making processes into mere minutes.Trusted by Fortune 10 enterprises and beloved brands like FreshDirect, Blank Street, and Levain Bakery, Hilbert is the backbone of their growth strategies. We are also collaborating with leading AI companies to push the boundaries of what’s possible.We are seeking a talented Data Scientist who possesses a deep understanding of B2C business challenges, develops actionable models using real-world data, and delivers impactful analyses that facilitate significant growth outcomes — all with the initiative and urgency typical of a founder.This is not a role where you simply receive tasks; you will take ownership of problems from start to finish — from problem framing and modeling to measuring impact — for enterprise clients where the stakes are high and feedback is rapid. If you understand the nuances of churn analysis for different sectors, can create effective recommendation systems from sparse data, and can clearly communicate your causal analysis to clients, we want to meet you.ROLE OVERVIEWYou will closely collaborate with the founding team, engineering, product, and go-to-market teams to enhance the data science systems integral to Hilbert. Daily responsibilities include building models, conducting experiments, analyzing data, and producing analyses that influence key decisions. Our focus is B2C, and the challenges we tackle — such as demand forecasting, customer lifecycle management, personalization, and activation — require an individual who can translate business contexts into effective modeling choices. You will thrive in a high-autonomy, high-ambiguity environment where data is often messy, incomplete, or scarce.Key Responsibilities:Develop ML models that enhance core product features: recommendation systems, search relevance, customer segmentation, demand forecasting, and activation optimization.Contribute to configurable, multi-tenant model architectures that adapt to various customer contexts and business needs, avoiding the need for custom solutions for each case.Build effective models using available data — leveraging limited, noisy, or sparse datasets while determining the appropriate level of complexity.Design and implement rigorous A/B tests and recognize when causal inference methods are necessary.

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.

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 Strava, a leader in the sports technology sector, as a Machine Learning Engineer. In this exciting role, you will apply your expertise in machine learning and data science to develop innovative solutions that enhance the experience of millions of athletes worldwide. Collaborate with cross-functional teams to create algorithms that analyze vast datasets and provide actionable insights to our users.

About Stand Insurance Stand Insurance is rethinking how property risks are understood and managed. By combining advanced physics with artificial intelligence, the team models catastrophic risks at the asset level and automates underwriting and risk mitigation before losses happen. Instead of simply delivering insurance, Stand builds a scalable risk engine that aims to deliver real-world impact and stay in markets where others exit. Traditional property insurance often relies on outdated data and manual workflows, accepting damage as a given. Stand takes a different path: simulating real-world catastrophes for individual properties, turning those simulations into actionable steps, and automating operations around those insights. The result is a platform that can underwrite risks others avoid, while reducing operational friction. Role Overview: Machine Learning Engineer – Data Pipeline This role centers on building and maintaining the tools behind Stand’s data annotation pipeline. Areas of focus include computer vision, human-in-the-loop management, quality assurance, and economic optimization. The main goal: increase automation and lower cost-per-policy, while keeping quality high. Early on, work will involve hands-on management of the pipeline, quality checks, and close coordination with the annotation team. As experience grows, the focus will shift to developing advanced data science and machine learning systems, especially around quality instrumentation, automated QA, predictive labeling, and computer vision models. Over time, the role will evolve into shaping a systems-driven, automation-focused framework for the entire annotation lifecycle. Key Responsibilities Pipeline Operations and Reliability Monitor and maintain the daily health of the annotation pipeline Set up escalation protocols and frameworks for categorizing failures Lead the transition from manual to automated operations Quality Instrumentation Design validation systems that align with downstream model metrics Develop anomaly detection models for annotation workflows Automate tasks to cut down on manual QA effort Vendor and Annotator Performance Define and track performance metrics for vendors and annotators Location San Francisco

Join Hilberts as a Machine Learning Engineer / Data Scientist in our San Francisco office, where you will leverage cutting-edge technology to drive enterprise-level solutions. You will work collaboratively with cross-functional teams to design, develop, and implement machine learning models that enhance our data-driven decision-making processes.

About NationGraphAt NationGraph, we are revolutionizing the accessibility and usability of public sector data for businesses targeting municipalities, state agencies, educational institutions, and specialized districts. Our advanced data intelligence engine extracts actionable insights from millions of public sector sources, empowering organizations to make informed decisions. Established in 2024, our mission is to democratize information, ensuring that public data is genuinely accessible to everyone. Discover more at nationgraph.comOur TeamComprises seasoned entrepreneurs who have successfully built, scaled, and exited multiple companies.Developed robust software infrastructure capable of processing billions in transactions.Supported by top-tier venture capitalists and seasoned operating partners with a track record of investing in and nurturing iconic brands.Role OverviewDesign and implement end-to-end machine learning pipelines.Extract and mine data from various online sources through large-scale web crawling and scraping techniques to enhance our models and insights.Convert unstructured text data into structured knowledge using natural language processing (NLP), entity recognition, and bespoke models.Develop and refine text classification models to systematically organize intricate datasets.Enhance retrieval-augmented generation (RAG) systems utilized in our product offerings.Drive our data strategy by identifying and integrating new data sources.Tackle open-ended technical challenges, fostering a culture of learning and collaboration within the team.Primarily utilize Python and SQL for development.QualificationsA strong quantitative background in fields such as computer science, physics, mathematics, or engineering.Solid foundation in mathematics and statistics.A PhD in a quantitative discipline.Expertise in Python programming.Proactive ownership mentality with the ability to address complex technical challenges to create commercial value.A genuine enthusiasm for continuous learning, growth, and uncovering insights from complex datasets.Strong problem-solving, communication, and collaboration abilities in a dynamic work environment.

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!

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.

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).

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.

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.

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.

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.