Software Engineer - Machine Learning Tools

Join our dynamic team at LinkedIn as a Distinguished Software Engineer in Machine Learning. In this pivotal role, you will lead innovative projects that enhance our growth strategies through cutting-edge machine learning techniques. You will collaborate with cross-functional teams to implement advanced algorithms that drive our product offerings and influence key decisions.

Who We AreAt Ema, we are pioneering cutting-edge AI technologies designed to enhance the creativity and productivity of employees across enterprises. Our unique technology enables organizations to entrust Ema, the AI employee, with repetitive tasks, freeing up human talent for more strategic initiatives. Founded by a team of former executives from tech giants such as Google, Coinbase, and Okta, and backed by prestigious investors including Accel Partners and Naspers, we are on the forefront of the AI revolution.Our diverse team, composed of top engineers from leading tech firms like Microsoft Research and Facebook, brings a wealth of knowledge and experience, primarily from renowned institutions such as Stanford and MIT. Operating out of Silicon Valley and Bangalore, India, we embrace a hybrid work model, requiring employees to be in our Mountain View, CA office three days a week.Who You AreWe seek passionate and innovative Machine Learning Engineers who thrive on tackling complex challenges and enjoy working with vast datasets. You have a talent for translating theoretical concepts into practical, scalable solutions, and you are a collaborative team player who excels in autonomous settings. Your enthusiasm for employing machine learning techniques, particularly in Natural Language Processing and Information Retrieval, is matched only by your desire to contribute to a mission-driven, high-growth startup making a significant impact.Your ResponsibilitiesDesign, develop, and deploy machine learning models that drive our NLP, retrieval, ranking, reasoning, dialog, and code-generation systems.Implement state-of-the-art machine learning algorithms, including Transformer-based models and reinforcement learning, to enhance AI system performance.Analyze and process large, complex datasets (structured, semi-structured, and unstructured) to inform model development.Engage throughout the entire machine learning model lifecycle, from problem identification and data exploration to feature engineering and model evaluation.

Waymo is a pioneering company in the autonomous driving sector, dedicated to becoming the world’s most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has been committed to developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and prevent traffic-related fatalities. With over ten million rider-only trips and more than 100 million miles driven autonomously across various U.S. states, Waymo continues to push the boundaries of what is possible in vehicular automation. Our DUE Machine Learning team is tasked with constructing and managing scalable machine learning and data systems, simulation workflows, and insight tools, all aimed at optimizing the evaluation and onboarding processes for developers. This team integrates human expertise with cutting-edge machine learning models to produce training and evaluation data across a multitude of metrics, enhancing the performance of the Waymo Driver. We seek passionate researchers and software engineers excited about advancing machine learning methodologies for our autonomous vehicle evaluation systems, dedicated to enhancing our technology stack's efficacy.

About UsNuro is at the forefront of self-driving technology, dedicated to making autonomy available to everyone. Established in 2016, we are developing the world's most scalable driver by merging innovative AI with robust automotive hardware. Our flagship technology, the Nuro Driver™, is licensed to facilitate a variety of applications, from robotaxis to commercial fleets and personal vehicles. With years of successful self-driving deployments, Nuro is paving the way for automakers and mobility platforms to achieve commercial-scale autonomy, enabling a safer, more interconnected future.Role OverviewOur Sensor Data and Calibration team is expanding, and we are seeking a Senior Software Engineer with a strong background in robotics and machine learning. You will be responsible for designing both online and offline unstructured (targetless) sensor calibration algorithms. The ideal candidate will have extensive hands-on experience in the research, development, and application of machine learning methods utilizing various sensor data types (IMU, camera, lidar, radar, etc.). Familiarity with classical state estimation techniques, such as non-linear least-squares optimization and Lie algebra, is a plus.Key ResponsibilitiesDevelop cutting-edge state estimation and calibration algorithms leveraging both traditional robotics and modern machine learning techniques.Evaluate and characterize the accuracy and performance metrics of state estimation and calibration algorithms.Integrate calibration pipelines into the autonomy system while monitoring onboard performance and resource usage.Collaborate with cross-functional teams to enhance ML model training and overall performance assessment.Address critical inquiries regarding sensor data and overall autonomy effectiveness.

Who We Are Nuro is a pioneering self-driving technology company dedicated to making autonomy accessible to everyone. Established in 2016, Nuro is revolutionizing transportation with the most scalable autonomous driver, integrating advanced AI with automotive-grade hardware. Our flagship technology, the Nuro Driver™, is licensed to cater to various applications, including robotaxis, commercial fleets, and personal vehicles. With years of proven self-driving deployments, Nuro provides automakers and mobility platforms a clear pathway to commercial-scale autonomous vehicles, fostering a safer, more connected future. About the Role We are in search of a Senior/Staff Software Engineer to take on a pivotal technical leadership role in Nuro’s Machine Learning (ML) Data engine. You will be positioned at the crucial intersection of Autonomy, Machine Learning, and Infrastructure, serving as an architect for the systems that power our autonomy AI models. In this role, you’ll collaborate with the Autonomy team to implement the technical strategy to convert vast amounts of autonomy data into high-value training signals for decision-making. Your responsibilities will include designing and constructing data products for autonomy researchers, developing queries for rare 'needle-in-a-haystack' scenarios, and automating labeling and data ingestion workflows. You will work closely with Autonomy ML researchers to grasp their data needs, cooperate with infrastructure teams to establish the appropriate data interfaces and APIs, and develop robust tools for data selection, simulation, and introspection, all capable of handling data at scale. If you thrive on solving complex problems with practical solutions that impact the real world, we invite you to join us. About the Work Data Pipeline Architecture: Design and implement scalable data ingestion and processing pipelines that transform data streams into targeted training datasets. Lead efforts to enhance data quality, identify anomalies, and manage out-of-distribution examples to ensure effective model training and deployment. Cross-Functional Leadership: Collaborate with autonomy teams and data infrastructure teams to create effective ML data pipelines and products for ML engineers. ML Tooling & Introspection: Build infrastructure and visualization tools that enable ML researchers to easily introspect data, identify model failure modes, request new data samples, and comprehend shifts in data distribution. Labeling Operations Integration: Work closely with the data operations team to establish quality standards for labeling operations.

About NewsBreakEstablished in 2015, NewsBreak is a pioneering Content Intelligence platform redefining the content economy. With a robust user base of over 40 million monthly active users, our flagship platform delivers tailored local news and information, powered by cutting-edge AI, recommendation systems, and advanced adtech.Acknowledged by Fast Company as #32 among the Top Workplaces for Innovators, we proudly hold Great Place to Work® certification and foster a vibrant team of technologists, product innovators, and business leaders dedicated to addressing significant challenges at scale.Achieving unicorn status in 2021, we remain steadfast in our commitment to high growth, seeking the ideal team to realize our mission: to establish the foundational infrastructure for content intelligence.If you’re driven to dream big, innovate rapidly, and make a meaningful impact, we want to hear from you! For more details, visit www.newsbreak.com/aboutAbout the Role:We are seeking a Machine Learning Infrastructure Engineer to join us in building the pivotal infrastructure that trains, serves, and monitors the models behind our Ads and Recommendations products. You will be part of a small, high-responsibility team that implements platform enhancements end-to-end—collaborating with product and data teams to minimize latency and costs while expediting the transition from concept to safely launched model.Your role will encompass the entire ML lifecycle: enhancing training efficiency and reliability, optimizing model serving performance, and fortifying our feature/embedding platform to ensure models remain current and consistent across offline and online applications. We are looking for someone who takes genuine ownership, completes tasks, and elevates the standards for stability and developer experience.Why This Role:Scope & Impact: Join a small team with a significant influence—your contributions will directly impact production.Ownership: Manage everything from design to rollout and post-launch insights; enjoy real autonomy with support.Growth: Gain visibility across the stack and a clear pathway to lead projects and mentor others.Pragmatic Culture: We prioritize outcomes over jargon, valuing clear thinking and follow-through.

About Us Nuro is a pioneering self-driving technology company committed to making autonomy accessible for everyone. Established in 2016, we are developing the world’s most scalable autonomous vehicle, integrating advanced AI with automotive-grade hardware. Our flagship technology, the Nuro Driver™, is licensed to enable a variety of applications, including robotaxis, commercial fleets, and personal vehicles. With a proven track record in self-driving deployments, Nuro provides automakers and mobility platforms a clear pathway to large-scale autonomous vehicles, paving the way for a safer, more connected future. Position OverviewOur robotics division is expanding, and we are on the lookout for an experienced Software Engineer to join our Sensor Data and Calibration team. We seek a candidate with a strong background in robotics and machine learning to create synthetic sensor simulation models and algorithms. The ideal applicant will possess hands-on experience with research, development, and implementation of machine learning techniques (such as NeRF or Gaussian splatting) aimed at generating synthetic sensor data, including photorealistic images and realistic lidar and/or radar outputs. Your Responsibilities Research, develop, and implement cutting-edge synthetic sensor simulation methodologies. Evaluate and characterize the authenticity and utility of synthetic sensor data. Address critical inquiries regarding sensor data and the performance of autonomous systems. Collaborate with cross-functional teams to establish mapping needs and specifications. Candidate Profile One of the following qualifications: PhD in machine learning, computer science, electrical engineering, robotics, or a related discipline with at least 3 years of industry experience. Master's degree with a minimum of 4 years of industry experience. 5+ years of relevant industry experience. In-depth understanding of machine learning principles, with practical experience in training and evaluating modern ML models. Proficient in Python, with familiarity in deep learning frameworks like PyTorch, TensorFlow, or Jax. Desired Skills Comprehensive knowledge of 3D geometry and state estimation concepts. Strong programming skills in systems coding. Experience in simulating/modeling real sensors (camera, lidar, radar, IMU, etc.), including noise modeling. Familiarity with contemporary ML graphics techniques, such as NeRF, Gaussian Splatting, and/or generative models.

About the RoleJoin our dynamic team of experts where machine learning and systems engineering intersect to enhance the performance of autonomous systems. As a Senior Software Engineer specializing in Perception Machine Learning Data, you will play a crucial role in integrating machine learning advancements with autonomy infrastructure, ensuring that our models are trained using the most pertinent, diverse, and high-quality datasets. Your contributions will significantly influence how autonomous systems recognize uncommon scenarios, adapt to various geographical contexts, and operate safely at scale.Key Responsibilities Include:Utilizing Vision Language Models (VLMs) to compile diverse datasets that reflect real-world driving patterns across different regions.Creating high-fidelity synthetic data frameworks across multiple sensor modalities.Enhancing machine learning-powered validation processes for data quality and model preparedness.Your Impact:High-Output Generalist: Collaborate across various domains including autonomy, infrastructure, databases, simulation, and machine learning development, while expanding your expertise in Robotics and ML.Robotics Specialist: Develop cutting-edge solutions for data discovery, automated labeling, and synthetic data generation in close cooperation with the Infrastructure and Autonomy teams.About the WorkTackle the most demanding data challenges in autonomy by applying machine learning and rigorous systems engineering principles:Design hybrid systems that combine deep learning with traditional algorithms for scalable data curation and annotation.Create frameworks to evaluate the real-world authenticity of synthetic data and enhance the quality of synthetic data rendering.Develop tools to automatically identify data gaps that affect the performance of perception models.Collaborate with autonomy engineers to transform raw sensor data into prioritized training objectives, addressing critical gaps that hinder perception and autonomy performance.About YouBachelor’s degree in Computer Science, Robotics, Statistics, Physics, Mathematics, or a related quantitative field.Experience:4+ years of professional software engineering experience, proficient in Python and familiar with C/C++. Demonstrated ability to lead cross-functional technical projects from conception to execution.You have hands-on experience in implementing machine learning solutions and enjoy embedding them into practical systems. Your focus is on delivering impactful, integrated solutions rather than solely theoretical ML projects.Bonus PointsExperience working with synthetic or autonomous driving data.Background in building machine learning systems for robotic applications.

About Us Nuro is a pioneering self-driving technology firm focused on democratizing autonomy for everyone. Established in 2016, we are on a mission to create the world's most scalable autonomous driver. Our innovative approach blends advanced AI with automotive-grade hardware, allowing us to license our core technology, the Nuro Driver™, across diverse applications including robotaxis, commercial fleets, and personal vehicles. Our proven technology, tested through numerous self-driving deployments, provides automakers and mobility platforms with a clear path to commercial-scale autonomous vehicles, fostering a safer, more connected future. Position OverviewWe are excited to expand our robotics team and are seeking a talented Senior Software Engineer to join our Sensor Data and Calibration unit. The ideal candidate will possess a strong background in robotics and machine learning, with a focus on developing sophisticated synthetic sensor simulation models and algorithms. Experience in research, development, and application of machine learning techniques (such as NeRF or Gaussian splatting) for generating synthetic sensor data, including photorealistic images and realistic LiDAR or radar outputs, is essential. Key Responsibilities Research and create cutting-edge synthetic sensor simulation methodologies. Evaluate and characterize the realism and effectiveness of synthetic sensor data. Address essential inquiries regarding sensor data and autonomous performance. Collaborate with various teams across autonomy, infrastructure, and systems to define mapping requirements. Qualifications One of the following: PhD in machine learning, computer science, electrical engineering, robotics, or a related field, with 3+ years of industry experience. Master's degree with 4+ years of industry experience. 5+ years of industry experience. In-depth knowledge of machine learning fundamentals with practical experience in training and assessing contemporary ML models. Proficient in Python, with experience in deep learning frameworks such as PyTorch, TensorFlow, or JAX. Preferred Qualifications Strong grasp of 3D geometry and state estimation principles. Experience in systems-level coding. Familiarity with simulating and modeling real sensors (camera, LiDAR, radar, IMU, etc.), including noise modeling. Expertise in modern ML graphics techniques, such as NeRF, Gaussian Splatting, and/or generative models.

Waymo is a pioneering autonomous driving technology firm dedicated to becoming the world’s most reliable driver. Originating as the Google Self-Driving Car Project in 2009, Waymo has committed itself to developing the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access while aiming to save thousands of lives lost in traffic accidents. The Waymo Driver underpins Waymo’s fully autonomous ride-hailing services and can be adapted across various vehicle platforms and applications. With more than ten million rider-only trips completed, it has driven over 100 million miles on public roads and tens of billions of miles in simulations across 15+ U.S. states.In this hybrid role, you will work closely under the guidance of a Technical Lead in Planner Technology.Your Responsibilities:Analyze driving behavior issues from logs to identify underlying causes.Enhance the performance of cutting-edge machine learning models in the Planner.Build foundational frameworks to further the capabilities of the Waymo Driver.Broaden the influence of machine learning models while maintaining interpretability and behavioral assurances.Contribute to solving some of the most complex driving scenarios.

At Waymo, we are pioneering the future of autonomous driving technology with an unwavering commitment to becoming the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, our focus has always been on engineering the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and drastically reduce traffic-related fatalities. The Waymo Driver currently powers our fully autonomous ride-hail service, having completed over ten million rider-only trips and covering more than 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.This role in Software Engineering is crucial as we develop the intelligent systems that allow the Waymo Driver to navigate complex environments, make sound decisions, and ensure safe transportation for our users. We tackle intricate technical challenges in robotics, perception, decision-making, and deep learning, collaborating closely with hardware and systems engineers. If you are a dedicated software engineer or researcher with a passion for Level 4 autonomous driving, we are eager to meet you.In this hybrid role, you will report directly to a Technical Lead Manager.

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.

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the world's most trusted driver. Originating as the Google Self-Driving Car Project in 2009, Waymo has developed the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and save thousands of lives currently lost to traffic accidents. The Waymo Driver operates Waymo’s fully autonomous ride-hail service and is adaptable to various vehicle platforms and use cases. With over ten million rider-only trips, our technology has autonomously driven more than 100 million miles on public roads and processed tens of billions of miles in simulation across more than 15 U.S. states.The Waymo ML Frameworks & Efficiency team collaborates closely with Research and Production teams to design and implement models in Perception and Planning, which are essential components of our autonomous driving software. We provide our partners with the most effective frameworks for the entire model development lifecycle and innovative efficiency solutions for model execution, tailored to the unique challenges of machine learning in autonomous driving.We are seeking talented engineers with expertise in ML frameworks or ML systems to enhance computational efficiency in both cloud environments and vehicle systems. You will engage with the entire ML stack, from deep learning model architectures to accelerator runtimes, working alongside ML modeling teams to drive large-scale efficient model training and inference.

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.

Waymo is an innovative leader in autonomous driving technology, dedicated to becoming the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has made significant strides in developing the Waymo Driver—The World’s Most Experienced Driver™—aiming to enhance mobility access while preventing countless traffic-related fatalities. With over ten million rider-only trips and extensive autonomous driving experience across more than 100 million miles on public roads, Waymo continues to redefine transportation solutions in over 15 U.S. states.The Machine Learning Operations (ML Ops) team, a vital part of the Waymo ML Platform, is responsible for creating tools and infrastructure that facilitate the ML flywheel at Waymo. This team focuses on developing automation and orchestration solutions that streamline complex ML workflows and collaborates closely with the modeling team to enhance developer efficiency.We are seeking a skilled software engineer to join our team, responsible for building and maintaining critical data and ML pipelines that drive ML development at Waymo.In this hybrid role, you will report to a Technical Lead Manager, Staff Software Engineer.

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the world’s most trusted driver. Originating from the Google Self-Driving Car Project in 2009, Waymo has been relentlessly focused on creating the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and prevent traffic-related fatalities. The Waymo Driver is the driving force behind our fully autonomous ride-hail service, optimized for various vehicle platforms and applications. With over ten million rider-only trips and more than 100 million miles driven autonomously on public roads, alongside tens of billions of simulated miles across 15+ U.S. states, Waymo is redefining transportation.The ML Platform team at Waymo plays a critical role by offering a suite of tools that facilitate and automate the entire machine learning workflow lifecycle, including feature and experiment management, model development, optimization, and monitoring. Our initiatives have made machine learning more accessible across diverse teams at Waymo, including Perception, Planner, Research, and Simulation.We are seeking talented engineers with expertise in machine learning software or systems to enhance compute performance both in the cloud and on vehicles. You'll engage with the entire ML stack from a systems perspective, tackling challenges such as efficient deep learning models, model compression, and improving ML software (e.g., JAX, XLA, Triton, and CUDA). This hybrid position reports directly to the Senior Manager of Runtime and Optimization.

Join Our TeamAt Unity, we are creating an exceptional ad-tech ecosystem that connects billions of users with the games and experiences they cherish. The Advertiser Growth team plays a pivotal role in this mission, managing the online ads delivery stack, which includes auction, pacing, and bidding systems. As a Senior Machine Learning Engineer, you will significantly contribute to modernizing our core infrastructure and developing backend systems for next-generation AI agents that transform the campaign experience. This position provides an exciting opportunity to tackle complex system challenges at a massive scale while directly impacting Unity’s revenue growth.

Join Coupang as the Director of Machine Learning Engineering and lead transformative projects that will redefine customer experiences. You will spearhead our machine learning initiatives, collaborating with cross-functional teams to drive innovative solutions across our e-commerce platform.Responsibilities include:Developing and implementing cutting-edge machine learning algorithms.Leading a team of data scientists and engineers.Collaborating with stakeholders to identify opportunities for leveraging data to enhance customer satisfaction.To apply, please complete the Internal Transfer Request Form using your Coupang email address.

Aeva, Inc. is seeking a Machine Learning Engineer with a focus on Perception to join the team in Mountain View, CA. This role centers on developing algorithms that help autonomous systems interpret and respond to their environment. The work draws on both machine learning and computer vision to improve how autonomous vehicles perceive the world around them. Key responsibilities Design and build perception algorithms for autonomous platforms Use machine learning and computer vision on real-world datasets Support progress in autonomous vehicle technology through technical contributions Work closely with engineers and researchers to expand product capabilities Location This position is based in Mountain View, CA.

About EarnInEarnIn is a trailblazer in the field of earned wage access, dedicated to creating innovative solutions that provide real-time financial flexibility for individuals navigating the challenges of living paycheck to paycheck. Our community empowers members to access their earnings as they earn them, offering options to spend, save, and invest without mandatory fees, interest charges, or credit inquiries.With a highly experienced leadership team and backing from esteemed partners such as A16Z, Matrix Partners, DST, and Ribbit Capital, EarnIn is in a strong position with a thriving core business and significant growth potential. We are rapidly expanding and eager to onboard world-class talent to help us shape the future of our organization.POSITION SUMMARYWe are looking for a forward-thinking and experienced Director of Machine Learning to spearhead our machine learning initiatives across the organization. As a fintech leader, machine learning is central to our business strategy and enhances user experience. We rely on advanced, scalable ML systems to make impactful decisions and provide outstanding customer value. Our goal is to revolutionize success stories through the application of generative AI and cutting-edge machine learning algorithms, resulting in significant business and societal outcomes.The Director of ML will prioritize operational excellence by crafting and executing a strategy that transitions ML models from research to production, ensuring optimal performance, reliability, and maintainability. The ideal candidate will have a demonstrated history of deploying ML models at scale, particularly in dynamic startup settings. A strong coding background, familiarity with production-level ML engineering, and the ability to connect theoretical frameworks with practical execution are essential.The base salary range for this full-time role in Mountain View is $414,000 to $506,000, accompanied by equity and benefits. Salary ranges are determined by role, level, and location. This is a hybrid position, requiring in-office work two days a week.