Senior Machine Learning Engineer

About zaimlerAt zaimler, we recognize that AI agents struggle to make decisions based on fragmented data. Today’s enterprise data is scattered across numerous systems, lacking shared context and structure, which contributes to the challenges faced in enterprise AI. As we transition from copilots to fully autonomous agents, we're establishing a revolutionary …

Join Poshmark, Inc. as a Senior Machine Learning Engineer and help us shape the future of e-commerce through cutting-edge technology. In this role, you will leverage your expertise in machine learning to develop innovative models and algorithms that enhance user experiences and drive business growth.As part of our dynamic team, you will collaborate with data scientists, engineers, and product managers to implement machine learning solutions that solve real-world problems. Your contributions will directly impact our platform, making it smarter and more intuitive for our users.

Role overview The Senior Machine Learning Engineer at Rational Dynamics will work onsite in Berkeley, CA. The main focus is on developing and improving machine learning algorithms that power data-driven applications. This position involves hands-on work, from building models to optimizing and deploying them for greater performance and efficiency. What you will do Design, build, and fine-tune machine learning algorithms for practical, real-world scenarios Collaborate with colleagues from various disciplines to integrate models into products and workflows Deploy solutions that help drive better decision-making throughout the company

As a Machine Learning Engineer at Prosidian Consulting, you will play a pivotal role in designing and implementing innovative machine learning solutions that drive data-driven decisions. You will work closely with our data scientists and analysts to develop algorithms that enhance our clients' operational efficiencies and improve their business outcomes. Your expertise will help in transforming complex data sets into actionable insights that can be leveraged across various industries.

At OneStudyTeam, a subsidiary of Reify Health, we are dedicated to accelerating the pace of clinical trials and enhancing the approval rates of new therapies, ultimately aiming to uplift patient outcomes. Our innovative cloud-based platform, StudyTeam, digitizes research site workflows, enabling effective collaboration among sites, sponsors, and crucial stakeholders. Trusted by leading global biopharmaceutical companies, our platform is utilized at over 6,000 research sites across more than 100 countries. Join us in our mission to revolutionize clinical research and elevate patient care.One mission. One team. That’s OneStudyTeam.As a Senior Machine Learning Engineer, you will be instrumental in developing state-of-the-art AI products that significantly influence the delivery of new therapies to patients. We seek a seasoned ML engineer enthusiastic about transforming cutting-edge AI research into practical, scalable solutions. You possess a knack for resolving intricate challenges, maintain a sharp focus on detail, and strive for continuous process automation and enhancement. Your collaborative spirit shines through as you contribute both as an individual and as part of a team, demonstrating the resilience to face tough problems while remaining open to learning and adapting. Your self-motivation and discipline empower you to excel in a remote work environment, and your strong interpersonal skills foster a collegial atmosphere. As a key player in our rapidly expanding organization, you will harness AI to innovate clinical research and enhance patient care.

Join our innovative team at Weave as a Senior Machine Learning Engineer specializing in Generative AI. In this pivotal role, you will spearhead the development and implementation of cutting-edge machine learning algorithms that drive our AI initiatives. Collaborate with cross-functional teams to enhance our product offerings and deliver exceptional AI-driven solutions.

Waymo is looking for a Senior Machine Learning Engineer focused on Runtime and Serving to help advance autonomous vehicle technology in Mountain View, CA. Role overview This position centers on developing and improving machine learning systems that support safe and efficient vehicle operation. The work involves optimizing algorithms and increasing the performance of deployed models in real-world conditions. What you will do Lead the design and implementation of machine learning systems used in autonomous vehicles Work on runtime and serving infrastructure to ensure reliable and efficient model deployment Contribute expertise to optimize algorithms for safety and operational performance Impact Your contributions will directly affect how Waymo's vehicles interpret and respond to their environment, supporting safer and more reliable autonomous driving.

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.

Periodic Labs is an AI and physical sciences company based in Menlo Park. The team focuses on advancing scientific discovery by building advanced models that drive progress in materials, energy, and related fields. The company operates with a strong sense of ownership and a drive to push scientific boundaries, supported by leading investors and a rapidly growing organization. Role overview The Machine Learning Systems Engineer will own the systems layer that powers model training and inference. This work is closely tied to the reinforcement learning (RL) feedback loop at the heart of Periodic Labs' research process, where models propose experiments, experiments generate data, and that data improves future models. The role blends deep infrastructure work with research collaboration, focusing on both performance and integration with the scientific workflow. What you will do Develop scheduling solutions for GB series GPUs using platforms like Ray, Slurm, and Kubernetes. Aim to minimize latency and maximize resource utilization across different cluster setups. Create profiling tools, both online and offline, to identify and resolve bottlenecks in the training and inference stack. Implement direct S3 checkpoint streaming to remove I/O bottlenecks during large-scale training runs. Benchmark RL training configurations across model sizes, batch strategies, and hardware architectures to find optimal setups. Write and optimize communication and GPU kernels to increase hardware throughput. Design and implement zero-copy RDMA weight synchronization between training and inference systems, keeping the RL loop fast and efficient. Develop sandbox execution environments for rapid algorithm testing and iteration. Key focus areas Scheduling, kernels, RDMA, weight synchronization, and communication primitives Collaboration with researchers to co-design algorithms and infrastructure Accelerating the RL feedback loop that drives scientific discovery at Periodic Labs

Be Part of the Future of Autonomous RoboticsAt Bedrock Robotics, we are pioneering the transition of AI from theoretical frameworks to practical applications in the built environment. Our team is comprised of seasoned professionals who have been instrumental in the success of innovative companies such as Waymo, Segment, and Uber Freight. We are at the forefront of deploying autonomous technologies in heavy construction machinery, significantly enhancing the efficiency and safety of multi-billion dollar infrastructure projects across the nation.With backing from $350 million in funding, our mission is to address the urgent need for housing, data centers, and manufacturing facilities, while simultaneously responding to the construction industry's labor shortages.This position is where cutting-edge algorithms meet the practical world of construction. You will work alongside industry experts and top-tier engineers to tackle complex real-world challenges that cannot be simulated. If you are eager to leverage advanced technology for impactful problem-solving within a skilled team, we encourage you to apply.

About the RoleJoin bjakcareer as we create an innovative AI system that understands context throughout conversations, proactively plans actions, and effectively carries tasks forward over time.In this role, you will transform research directives into operational, production-ready machine learning systems. You will oversee the execution layer of our AI intelligence, including training pipelines, inference systems, evaluation tools, and deployment processes.What You'll DoDevelop and maintain comprehensive ML pipelines covering data management, training, evaluation, inference, and deployment.Optimize and fine-tune models utilizing cutting-edge methodologies like LoRA, QLoRA, SFT, DPO, and distillation.Design and manage scalable inference systems, ensuring a balance of latency, cost, and reliability.Create and oversee data systems that ensure high-quality synthetic and real-world training data.Implement evaluation pipelines that assess performance, robustness, safety, and bias, collaborating with research leaders.Manage production deployments, focusing on GPU optimization, memory efficiency, latency reduction, and scaling strategies.Work closely with application engineers to seamlessly integrate ML systems into backend, mobile, and desktop applications.Make practical trade-offs and deliver enhancements quickly, leveraging real-world usage data.Operate under real production constraints such as latency, cost, reliability, and safety.Tech StackPythonPyTorch / JAXGPU-based training and inference systemsIdeal ExperienceExperience in developing or deploying real-world ML systems that have been utilized by users, beyond mere demonstrations.Familiarity with large models and understanding their failure modes.Proficiency in writing robust, production-grade code with a focus on system accuracy and reliability.Demonstrated self-direction, pragmatism, and a strong sense of ownership over project outcomes.Excellent communication and collaboration skills, thriving in small, high-trust teams.

Join our innovative team at Nagarro as a Principal Engineer, specializing in Machine Learning. In this role, you will leverage your expertise to design and implement cutting-edge machine learning models that drive business solutions and enhance user experiences. You will collaborate with cross-functional teams to develop scalable and efficient algorithms, ensuring they meet the highest standards of performance and reliability.As a key member of our engineering department, your contributions will directly impact our product offerings and the success of our clients. We value creativity and encourage you to propose new ideas and advancements in machine learning technology.

Join Nagarro as a Staff Engineer specializing in Machine Learning, where you will play a crucial role in developing innovative AI solutions that drive business transformation. As part of our engineering team, you will collaborate with cross-functional groups to design, implement, and optimize machine learning models, contributing to cutting-edge technology and impactful projects.

OptiTrack builds motion capture systems used in animation, robotics, biomechanics, virtual production, and industrial environments. The team focuses on delivering accurate tracking solutions for a wide range of technical applications. Role overview The Machine Learning & Operations Engineer will help design, automate, and scale OptiTrack’s MLOps infrastructure. This remote position is open to candidates based in Miami, Florida, or anywhere in the United States. The role centers on supporting machine learning initiatives by working closely with research and engineering teams, automating workflows, and ensuring robust deployment of ML models. What you will do Create and maintain automated pipelines for machine learning training processes. Develop infrastructure for distributed experiments at scale. Build and improve CI/CD workflows tailored for ML systems. Manage data ingestion, preprocessing, validation, and handle model versioning. Implement tools for experiment tracking, hyperparameter tuning, and reproducibility. Optimize GPU and compute resources across both cloud and on-premises setups. Deploy, monitor, and maintain production machine learning models. Establish MLOps best practices, including model registry, artifact management, and observability. Enhance reliability, performance, and security of ML systems. Collaborate with machine learning researchers to prepare new algorithms for production deployment. Support additional DevOps tasks related to software development as needed. Location This is a fully remote role. Candidates may work from Miami, Florida, or anywhere in the United States.

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.

Join our innovative team at parspect as a Machine Learning Engineer, where you’ll be at the forefront of developing cutting-edge machine learning solutions. This is an exciting opportunity for an entry-level candidate eager to expand their skills in a dynamic and supportive environment.

Anduril Industries is a pioneering defense technology firm dedicated to enhancing military capabilities for the U.S. and its allies through innovative technology solutions. By integrating the best practices, expertise, and advanced technologies from the most forward-thinking companies in the 21st century, Anduril is revolutionizing the development, design, and delivery of military systems. Our cutting-edge systems are powered by Lattice OS, an AI-driven operating platform that transforms vast data streams into a real-time, 3D command and control environment. As we enter a new era of strategic competition, Anduril is committed to rapidly deploying breakthrough technologies in autonomy, AI, computer vision, sensor fusion, and networking to the military.We are looking for a Machine Learning Engineer to spearhead innovations in autonomous vehicle technology through deep learning and reinforcement learning techniques. In this role, you will create sophisticated algorithms and systems that facilitate safe, efficient, and intelligent autonomous operations. Currently, deploying large numbers of autonomous robots necessitates significant human oversight. At Anduril, we are harnessing AI to alleviate operator burdens and accelerate execution through real-time monitoring, user recommendations, and multi-modal interaction patterns. You will utilize both established and experimental methods to prototype and enhance the capabilities of autonomous systems.

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.

Be Part of the Future of Home RoboticsAt Sunday Robotics, we are pioneering the development of personal robots that alleviate the burden of repetitive household tasks. Our mission is to democratize access to advanced robotics, allowing families to reclaim precious time.After an intensive 18 months of assembling a talented team, securing funding, and validating our innovative technology, we are eager to welcome passionate individuals to join us as we embark on the next exciting chapter of our journey. If you are enthusiastic about contributing your skills to the cutting edge of robotics, we want to hear from you!The RoleAs a Machine Learning Infrastructure Engineer at Sunday Robotics, you will play a pivotal role in shaping the future of home robotics. You will develop end-to-end machine learning models for robotic manipulation, creating foundational systems that will expedite our efforts to introduce robots into everyday homes.This versatile position can be customized to align with your specific expertise, whether it be in data pipelines, training infrastructure, or inference. Your contributions will span the entire robot learning pipeline: from ingesting and processing multimodal data to scaling distributed training, optimizing real-time inference, and developing research tools.What You Will AccomplishEnhance the research codebase for optimal ergonomics and rapid iteration.Oversee model training infrastructure, including job scheduling, checkpointing, metrics, and logging.Facilitate distributed training across GPU clusters with minimal friction for researchers.Enable the training of larger models through techniques such as sharding and memory optimization.Profile and enhance GPU utilization, memory efficiency, and training throughput.Create low-latency inference pipelines for real-time robot control, employing techniques to optimize performance.Collaborate closely with researchers and roboticists to transform research requirements into robust software and infrastructure.Data Pipelines and Research ToolsArchitect high-throughput pipelines for the ingestion, validation, and transformation of multimodal robot data such as video and proprioception.Develop efficient storage systems and metadata indexing for seamless data retrieval.

Join the innovative team at goatgroup as a Senior Machine Learning Engineer, where you will play a pivotal role in developing cutting-edge machine learning models and solutions. In this fully remote position, you will collaborate with a dynamic group of professionals to tackle complex challenges and drive advancements in artificial intelligence.