Machine Learning Engineer - Perception

Role Overview Unity Technologies is advancing mobile gaming with AI-driven features. The Principal Machine Learning Engineer will focus on deploying advanced AI models, such as transformers and diffusion networks, directly onto mobile devices. This position shapes how Unity brings state-of-the-art multi-modal models from research into real-world mobile applications. What You Will Do Technical Leadership: Set the vision for deploying multi-modal AI models on iOS and Android, drawing on deep experience with transformers, diffusion models, and generative architectures. Make key decisions on model optimization strategies, including compression, quantization, and knowledge distillation to address mobile device constraints. Assess and select inference runtimes (such as CoreML, ONNX Runtime Mobile, TFLite) to improve team capabilities and deployment outcomes. Oversee the entire optimization pipeline, from model export through hardware-specific kernel tuning across different processing units. Architecture & Research Translation: Work closely with research scientists to convert innovative model architectures into operational, mobile-optimized systems. Design scalable systems capable of processing varied inputs, images, text, metadata, while ensuring real-time output performance. Develop new approaches for dynamic resolution and token reduction tailored for mobile environments. Monitor and incorporate advancements in efficient AI technologies to keep Unity’s mobile AI stack current. Team Leadership & Mentorship: Guide and mentor machine learning engineers, establishing best practices for on-device performance evaluation. Collaborate with cross-functional teams to ensure AI capabilities align with product roadmaps and device requirements. Promote a culture centered on performance measurement, defining and tracking key metrics for efficiency and accuracy. Location Mountain View, CA, USA

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.

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the world's most trusted driver. Established in 2009 as the Google Self-Driving Car Project, Waymo has developed the Waymo Driver—The World’s Most Experienced Driver™—aimed at enhancing mobility access and saving countless lives from traffic-related accidents. Our technology empowers a fully autonomous ride-hail service and is adaptable across various vehicle platforms and product applications. With over ten million rider-only trips facilitated by the Waymo Driver and more than 100 million miles driven autonomously on public roads, we are paving the way for safer transportation.The Perception team is responsible for developing systems that interpret the spatial-temporal representations and semantic meanings of the environment surrounding our autonomous vehicles. Our collaborative efforts with downstream teams focus on optimizing and integrating these systems within the Waymo Driver. We engage in innovative research to tackle real-world challenges and work closely with research teams at Alphabet. Our engineers have access to extensive driving data from diverse sensors, allowing us to (1) create efficient learning methods from vast real-world datasets, (2) build and train models at scale, (3) analyze real-world behaviors, and (4) optimize models for both onboard and offboard hardware.In this hybrid role, you will report to a Technical Lead Manager.

Join Waymo as a Tech Lead Manager for Machine Learning Optimization, where you will spearhead innovative projects to enhance our self-driving technology. In this role, you will lead a team of talented engineers and data scientists, guiding the development of advanced algorithms and optimization techniques that drive performance and reliability. You will collaborate with cross-functional teams to ensure the successful integration of ML models into our systems, pushing the boundaries of autonomous vehicle technology.

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.

The Role Join Moveworks as a Senior Machine Learning Engineer II, where you will play a pivotal role in enhancing our Natural Language Understanding (NLU) and Agentic AI capabilities. Your expertise in software engineering and machine learning will help create seamless user experiences and optimize our generative and conversational AI platform. As part of the NLU team, you will leverage cutting-edge tools in Natural Language Processing (NLP) and Natural Language Generation (NLG), including advanced Large Language Models (LLMs), multimodal foundation models, and hybrid vector databases. You'll have all the necessary infrastructure at your fingertips to fine-tune, evaluate, and deploy your models into production. Our data-centric approach is supported by a world-class annotation team that ensures the creation of high-quality, privacy-conscious datasets for model training and evaluation. Your mission will extend beyond mere model training; you will strive for exceptional AI performance across all metrics, including accuracy, latency, reliability, and the overall functionality of user-facing systems. Our ideal candidates are driven not only by the desire to develop high-performing models but also by the ambition to design and enhance comprehensive AI systems and their components. We are focused on accelerating our operations, tackling complex engineering challenges, and maximizing the value we deliver to our customers. Your contributions will be crucial in achieving our objectives of resolving enterprise issues and establishing the most dependable AI co-pilot ever seen, in collaboration with various teams at Moveworks.

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 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.

About NewsBreakFounded in 2015, NewsBreak is a pioneering Content Intelligence platform that is redefining the content economy. With a vibrant community of over 40 million monthly active users, our flagship platform offers deeply personalized local news and information, driven by cutting-edge AI technologies, sophisticated recommendation systems, and innovative adtech solutions.Recognized by Fast Company as #32 on the Top Workplaces for Innovators, we take pride in being Great Place to Work® certified. Our dynamic team of technologists, product innovators, and business leaders is dedicated to tackling significant challenges at scale.Having reached unicorn status in 2021, we are steadfast in our commitment to maintaining a high-growth trajectory through the right talent to help us realize our mission: building the infrastructure layer for content intelligence.If you’re motivated to think big, innovate rapidly, and make a meaningful impact, we’d love to connect with you! For more information, visit www.newsbreak.com/aboutAbout the RoleWe are on the lookout for a Staff Machine Learning Engineer to spearhead technical leadership for our recommendation systems and AI initiatives.In this pivotal position, you will set the technical direction for large-scale personalization systems, lead intricate projects across various teams, and champion the integration of AI / LLM technologies in our product capabilities and engineering workflows.This opportunity is perfect for engineers who relish system-level thinking, enjoy mentoring others, and excel at transforming complex, ambiguous challenges into scalable solutions.What You’ll Work OnTechnical Leadership & ArchitectureLead the design of next-generation recommendation system architectures at scale.Drive best practices for model lifecycle management, experimentation, and system reliability.Collaborate with product, infrastructure, and data teams to ensure alignment of technical strategy with business objectives.Advanced Recommendation & AI SystemsOversee complex initiatives encompassing retrieval, ranking, re-ranking, and multi-objective optimization.

About the RoleMoveworks is seeking experienced Senior and Staff Engineers to enhance our Generative AI Search Platform. Join our dedicated team as we innovate on search-based question answering systems by integrating traditional machine learning methods with the latest advancements in generative AI technologies. Our goal is to construct conversational search systems that deliver immediate responses to enterprise user inquiries.As part of the Search Platform team, you will lead efforts to refine our search capabilities, collaborating closely with ranking, product, design, infrastructure, and data science teams. Together, we aim to elevate our agentic search products to new heights of performance and enterprise readiness.At Moveworks, we value a fast-paced, problem-solving culture that prioritizes providing exceptional value to our customers. Your role will involve working with diverse teams to identify, define, and implement elegant solutions that meet user needs.Design robust abstractions to empower ranking and product teams to effectively contribute to the codebase.Develop algorithmic frameworks for various conversational search applications, including multi-turn, multi-hop question answering systems.Lead the evolution of our search platform by integrating new LLM-enabled generative AI features, ensuring scalability, quality, security, and privacy.Create systematic evaluation metrics and methodologies for our search models, utilizing LLMs to solve unique enterprise challenges.As a technical leader, foster a high-performing, inclusive team environment while mentoring engineers at various levels.Contribute to our hiring processes and help grow our engineering team.

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.

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.

Join Moveworks as a Principal Machine Learning Engineer, where you will play a pivotal role in enhancing our GAI search relevance and ranking systems. In this dynamic position, you will lead a talented team of engineers and data scientists to develop cutting-edge machine learning algorithms that improve user interactions and search outcomes. Your expertise will drive innovation and reinforce our commitment to delivering exceptional solutions.

Waymo is pioneering the future of autonomous driving technology with a commitment to becoming the most trusted driver worldwide. Since its inception as the Google Self-Driving Car Project in 2009, Waymo has dedicated itself to developing the Waymo Driver—The World’s Most Experienced Driver™—with the goal of enhancing mobility access and saving countless lives currently lost to traffic accidents. The Waymo Driver not only powers our fully autonomous ride-hail service but is also adaptable across various vehicle platforms and applications. Having completed over ten million rider-only trips and autonomously navigated more than 100 million miles on public roads, our technology has undergone extensive testing, including tens of billions of miles in simulations across more than 15 U.S. states.The Simulator Team at Waymo specializes in creating cutting-edge simulations of realistic environments designed for the rigorous testing and training of the Waymo Driver. Our diverse and collaborative team comprises software engineers, machine learning (ML) engineers, and data scientists, all united in our mission to develop industry-leading simulation solutions utilizing advanced ML algorithms to measure and enhance the Waymo Driver's performance. By leveraging machine learning, we meticulously model real-world scenarios, including realistic agents such as vehicles, pedestrians, cyclists, motorcyclists, roads, traffic control systems, and varying weather conditions.To enhance the fidelity and steerability of our simulations, we integrate the latest ML technologies, including large foundation models trained on our exclusive datasets and advanced diffusion techniques. Our investment in robust infrastructure facilitates the swift setup and deployment of multiple scenarios for comprehensive testing of our autonomous driving systems.In this hybrid role, you will report to a Senior Engineering Manager.

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the most trusted driver in the world. 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™—to enhance mobility and save lives lost in traffic accidents. Our technology powers a fully autonomous ride-hailing service and is adaptable across various vehicle platforms and applications. With over ten million rider-only trips and 100 million miles driven autonomously on public roads, our experience is unmatched.As part of the DUE ML Core team, you will play a pivotal role in building and managing scalable machine learning and data systems, refining simulation workflows, and enhancing developer onboarding experiences. This position combines expert human insight with cutting-edge machine learning models to produce training and evaluation data for a multitude of metrics and components integral to the Waymo Driver. We seek passionate researchers and software engineers eager to advance machine learning methodologies for our autonomous vehicle evaluation systems and continuously improve the performance of our technological framework.

Waymo, a leader in autonomous driving technology, is dedicated to becoming the world's most trusted driver. Originating from the Google Self-Driving Car Project in 2009, our focus has been on creating the Waymo Driver—The World’s Most Experienced Driver™—to enhance mobility access and prevent traffic-related fatalities. With our Waymo Driver, we have powered a fully autonomous ride-hail service, achieving over ten million rider-only trips and accumulating experience from over 100 million miles driven on public roads and tens of billions of miles in simulation across more than 15 U.S. states.The Waymo AI Foundations team is on a mission to create machine learning solutions that address critical challenges in autonomous driving, aiming to operate Waymo vehicles safely across numerous cities and under various driving conditions. We actively engage in collaborative efforts with other research teams within Alphabet, focusing on areas such as reinforcement learning, learning from demonstrations, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.This role follows a hybrid work schedule and you will report to a Senior Staff Software Engineer.

Are you driven by a passion for solving complex AI challenges and eager to play a pivotal role in revolutionizing enterprise automation? Join Kognitos as we shape the future of software development!Your Contributions Will Include:Optimizing Resource Utilization: Create cutting-edge strategies to enhance resource efficiency in training and fine-tuning machine learning models, ensuring optimal performance without compromising on resource usage.Developing Intelligent Workflows: Innovate workflows that empower AI to reason, plan, and execute tasks consistently, reducing errors and unexpected outcomes.Integrating Multimodal Language Models: Engage in multimodal projects that blend text, images, and various data formats to develop robust, enterprise-ready automation solutions.Enterprise-Scale AI Solutions: Deliver AI systems that address enterprise needs, targeting a reduction of operational costs by 30% through widespread adoption.Key Responsibilities:Design and implement machine learning models with a focus on intelligent workflows and reliable task execution.Refine AI systems for multimodal applications, effectively tackling real-world challenges faced by enterprises.Pioneer new fine-tuning methodologies to enhance resource utilization and model efficacy.Ensure alignment of AI systems with regulatory standards while delivering consistent business outcomes.Collaborate with diverse teams, including product management, engineering, and business stakeholders, to drive impactful solutions.Stay abreast of the latest advancements in AI research, integrating cutting-edge developments into Kognitos’ platform.Qualifications:A Bachelor's, Master's, or Ph.D. in Computer Science, Machine Learning, or a related discipline.Demonstrated experience in developing and deploying machine learning models in production settings.Expertise in fine-tuning techniques for large-scale models and resource optimization.Strong intuition and experience with Large Language Models (LLMs).Familiarity with multimodal language models and their applications in enterprise environments.

Moveworks seeks a Senior Machine Learning Engineer to advance the GAI search relevance system. This position is based in Mountain View and centers on improving how users find information on the platform. Key Responsibilities Partner with fellow engineers to design and implement solutions that raise the quality of search results. Work on projects aimed at making the user experience smoother and supporting operational goals. Collaboration and Influence This role involves working alongside engineers who prioritize careful problem-solving and practical improvements. The work directly shapes how users engage with Moveworks’ technology.

Join Our TeamAre you passionate about pioneering projects that harness advanced AI technology to unlock significant benefits from meetings and conversations? Become a vital member of our core AI team at Otter.ai, where you will collaborate with seasoned scientists and engineers dedicated to machine learning. As a Senior Machine Learning Engineer, your expertise in software engineering will be crucial in scaling and refining our machine learning systems. You will play a key role in transforming innovative research into production-ready features that enhance Otter’s summarization and conversational intelligence products.Your ContributionsDesign, construct, and advance extensive SID / ASR / NLP / LLM systems that drive essential product experiences, including summarization, chat, and speech comprehension for millions of interactions.Lead the creation and execution of training, fine-tuning, post-training, and inference methodologies for large language and speech models utilizing PyTorch and/or JAX while balancing quality, latency, cost, and dependability.Innovate and enhance model architectures, loss functions, decoding techniques, and training methodologies for speech and language models, guided by research insights and production restrictions.Oversee the entire ML system lifecycle, from initial research prototyping to production deployment, continuous monitoring, iteration, and long-term maintenance.Collaborate closely with product and infrastructure teams to translate groundbreaking research into scalable, production-grade systems that yield measurable user and business outcomes.Champion system-level enhancements in model performance, robustness, observability, and operational excellence using real-world conversational data.Establish technical direction and best practices for ML infrastructure, data pipelines, evaluation frameworks, and deployment workflows within a cloud environment.Diagnose and resolve complex issues related to model behavior, data quality, scalability, and system interactions, often preemptively before they affect users.Mentor and uplift fellow engineers, contributing to team standards, evaluating designs, and fostering a culture of sound technical decision-making and execution.