Senior Machine Learning Software Engineer - Integration & Quality

Cerebras Systems is at the forefront of AI innovation, having developed the world's largest AI chip, which is 56 times greater in size than conventional GPUs. Our revolutionary wafer-scale architecture delivers the computational power of multiple GPUs on a single chip, simplifying programming to a single device experience. This unique approach enables Cerebr…

Join Wayve Technologies as a Principal Machine Learning Engineer, where you will lead innovative projects that push the boundaries of application software development. You will collaborate with cross-functional teams to design, implement, and optimize machine learning algorithms that enhance our software solutions.

About Applied IntuitionApplied Intuition, Inc. is at the forefront of advancing physical AI. Established in 2017 and currently valued at approximately $15 billion, this Silicon Valley-based company is dedicated to developing the digital infrastructure essential for instilling intelligence in every moving machine globally. We cater to various sectors, including automotive, defense, trucking, construction, mining, and agriculture, focusing on three main areas: tools and infrastructure, operating systems, and autonomy. Our solutions have earned the trust of 18 of the top 20 global automakers and the United States military and its allies. Headquartered in Sunnyvale, California, we have offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Discover more at applied.co.We prioritize in-office collaboration and expect employees to work from their Applied Intuition office five days a week. However, we also value flexibility and trust our employees to responsibly manage their schedules, which may include occasional remote work, starting the day with morning meetings from home, or leaving earlier to accommodate family obligations.About the RoleWe are seeking infrastructure engineers with a strong background in machine learning pipelines, as well as ML engineers who are eager to extend their skills beyond modeling. This position will involve engagement across the complete ML lifecycle, including dataset generation, training frameworks, compute, evaluation, and deployment, collaborating closely with modeling teams. If you thrive on tackling broad and ambiguous challenges and enjoy working across the entire ML stack, this team is the perfect fit for you. At Applied Intuition, we encourage all engineers to take ownership of technical and product decisions, actively engage with both internal and external users to gather feedback, and contribute to a thoughtful, dynamic team culture.At Applied Intuition, You Will:Design and implement distributed cloud GPU training strategies for deep learning model training and evaluation.Create comprehensive machine learning pipelines and integrate them into our core systems.

Join our innovative team at Intuitive Surgical, Inc., where we are redefining healthcare through advanced robotics and computer vision. As a Machine Learning Engineer, you will be at the forefront of developing cutting-edge algorithms that enhance robotic performance and improve patient outcomes. This role offers an exciting opportunity to work on transformative technology that makes a real impact in the medical field.

About the Institute of Foundation ModelsWe are a pioneering research laboratory focused on developing, understanding, utilizing, and managing foundation models. Our mission is to propel research, cultivate the next generation of AI innovators, and create transformative impacts within a knowledge-driven economy.Join our dynamic team and seize the opportunity to engage in groundbreaking foundation model training, collaborating with elite researchers, data scientists, and engineers to address the most pressing challenges in AI development. You will contribute to the creation of innovative AI solutions with the potential to revolutionize industries. Your strategic and creative problem-solving abilities will play a crucial role in establishing MBZUAI as a global center for high-performance computing in deep learning, fostering discoveries that will motivate future AI trailblazers.The RoleAs a Machine Learning Engineer at the Institute of Foundation Models, your main duty will be to design and implement cutting-edge machine learning models that tackle real-world issues, pushing the limits of artificial intelligence research. You will work collaboratively with diverse teams to deploy scalable solutions, furthering MBZUAI’s goal of driving significant AI advancements and solidifying the institution’s status as a leader in the international AI research community. Your expertise will be vital in enhancing the performance of large-scale machine learning models and aiding in the development of transformative AI tools that can reshape industries globally.

Join our team at DoorDash as a Principal Machine Learning Engineer specializing in Ads and Promotions Delivery. In this pivotal role, you will leverage cutting-edge machine learning techniques to optimize our advertising strategies and enhance customer engagement. Collaborate with cross-functional teams to design and implement scalable machine learning models that drive business growth.

42dot is seeking a Senior Machine Learning Platform Engineer to support its work in autonomous driving technology. This position is based in Sunnyvale, United States. Role overview This role focuses on developing machine learning platforms that support autonomous vehicle systems. The work involves designing and building scalable infrastructure to handle complex ML workloads, with a strong emphasis on performance and reliability. What you will do Lead the creation and enhancement of machine learning solutions for autonomous driving applications. Design, implement, and maintain ML platforms to ensure they meet high standards for scalability and reliability. Requirements Extensive experience in building and maintaining machine learning platforms. Background in supporting ML solutions for autonomous vehicle technology or similar fields. Strong skills in designing scalable and high-performance systems.

About the Internship Bosch Group is seeking an Automated Driving Machine Learning Intern in Sunnyvale, California. This role offers hands-on experience with real projects in automated driving and machine learning. Interns will apply academic skills to practical challenges in the field.

Cerebras Systems is at the forefront of AI technology, having developed the world's largest AI chip, which is 56 times larger than traditional GPUs. Our innovative wafer-scale architecture delivers the computational power equivalent to dozens of GPUs on a single chip while maintaining the programming simplicity of a single device. This unique approach enables Cerebras to provide unparalleled training and inference speeds, allowing machine learning practitioners to seamlessly run large-scale ML applications without the complexities of managing numerous GPUs or TPUs. Cerebras proudly serves a diverse clientele, including leading model labs, global enterprises, and pioneering AI-native startups. Notably, OpenAI has recently formed a multi-year partnership with Cerebras to harness 750 megawatts of scale, revolutionizing key workloads with ultra high-speed inference. Our groundbreaking wafer-scale architecture ensures that Cerebras Inference stands as the world's fastest solution for Generative AI inference, achieving speeds over ten times faster than GPU-based hyperscale cloud inference services. This remarkable increase in speed is transforming the user experience of AI applications, enabling real-time iterations and enhancing intelligence through additional agentic computation.About The RoleCerebras is expanding its Machine Learning team to spearhead a new initiative that aligns with our existing teams. We are seeking a Principal Investigator to collaborate with our ML leaders in shaping this new effort while building the team and enhancing our capabilities. This new team will work in concert with our current ML divisions: Field ML, which directly engages with customers, Applied ML, which develops new ML capabilities and applications, and Core ML, which adapts ML algorithms to leverage the unique features of Cerebras hardware. The new team may undertake similar or complementary responsibilities.The new team will focus on areas such as:Post-training and reinforcement learning: Enhancing model deployment quality through advanced training, tuning, and reinforcement learning techniques, concentrating on specific downstream tasks;Dataset curation and optimization: Implementing strategies to gather and select high-quality data, facilitating quicker and higher-quality model training and tuning;LLM Pretraining: Engaging in...

Wayve Technologies is searching for a Tech Lead, Machine Learning Engineer to join the autonomous vehicle product engineering group in Sunnyvale. This leadership role centers on guiding a team that develops sophisticated machine learning models for future mobility technologies. Role overview The Tech Lead will direct the design and deployment of machine learning algorithms tailored for autonomous vehicle systems. The position also includes mentoring junior engineers and collaborating with colleagues across multiple disciplines to ensure projects are delivered on time and meet quality standards. What you will do Lead the creation and implementation of machine learning solutions for autonomous vehicles Support and mentor junior engineers to strengthen their technical skills and project impact Coordinate with cross-functional teams to achieve project goals efficiently and with high quality Requirements Strong background in machine learning and artificial intelligence Proven experience leading or mentoring engineering teams Genuine interest in the intersection of AI and autonomous vehicle technology

About the Institute of Foundation ModelsWe are a pioneering research lab focused on the development, understanding, application, and risk management of foundation models. Our mission is to propel research forward, cultivate the next generation of AI innovators, and make significant contributions to a knowledge-driven economy.Join our dynamic team and engage in the heart of innovative foundation model training, collaborating with top-tier researchers, data scientists, and engineers. Tackle groundbreaking challenges in AI development and contribute to transformative AI solutions that have the potential to revolutionize industries. Your strategic and innovative problem-solving skills will be vital in establishing MBZUAI as a global center for high-performance computing in deep learning, enabling impactful discoveries that inspire the future of AI innovation.Role OverviewDevelop and Enhance Distributed Pre-Training Frameworks· Implement DeepSpeed / FSDP / Megatron-LM on multi-node GPU clusters.· Design robust launch scripts, resilient checkpoints, and job monitoring systems (e.g., NCCL/GLOO/GPU).Transform Mathematical Concepts into High-Performance Production Code· Prototype novel optimizers or attention mechanisms using PyTorch/NumPy/JAX or similar frameworks.· Convert prototypes into efficient CUDA/Triton kernels with custom gradients and performance tests.Enhance Training Efficiency and Stability· Lead efforts in mixed-precision training, integrating bf16, fp8, etc., into regular workflows while assessing accuracy versus speed improvements and analyzing numerical stability.· Utilize kernel fusion, communication tuning, and memory optimization to achieve state-of-the-art throughput.Accelerate Research Progress· Develop logging and metrics systems, along with experiment-tracking tools, to facilitate rapid iteration.· Design ablation studies and statistical tests that validate or challenge new concepts.· Guide interns and junior engineers through clear asynchronous design documentation and code reviews.You will collaborate closely with researchers, deliver production code, and shape the landscape of large language models.

At Cerebras Systems, we are at the forefront of AI technology, developing the world's largest AI chip that is 56 times larger than conventional GPUs. Our innovative wafer-scale architecture enables the computational power of dozens of GPUs on a single chip, simplifying programming to the ease of handling one device. This unique design allows us to achieve unparalleled training and inference speeds, empowering machine learning practitioners to seamlessly deploy large-scale ML applications without the complexity of managing numerous GPUs or TPUs.Our clientele includes leading model labs, global enterprises, and pioneering AI-native startups. Recently, OpenAI announced a multi-year partnership with Cerebras aimed at leveraging 750 megawatts of scale to revolutionize critical workloads through ultra-high-speed inference.Thanks to our groundbreaking wafer-scale architecture, Cerebras Inference delivers the fastest Generative AI inference solution globally, exceeding GPU-based hyperscale cloud inference services by over tenfold. This significant boost in speed is transforming the user experience of AI applications, facilitating real-time iteration and enhancing intelligence through added agentic computation.About The RoleAs an Applied Machine Learning Research Scientist at Cerebras, you will be instrumental in converting modern machine learning methodologies into scalable, high-performance systems. This position focuses on the intersection of modeling and systems, emphasizing the efficient execution of existing algorithms rather than merely publishing new ones. Your efforts will significantly influence the training, optimization, and deployment of large language models (LLMs) on one of the most sophisticated AI platforms in existence.You will collaborate closely with fellow researchers and senior engineers to enhance workflows for LLM pretraining, fine-tuning, and reinforcement learning-based post-training. Your responsibilities will encompass building training pipelines, debugging complex system behaviors, improving model quality, and refining data and evaluation strategies. Your contributions will have a direct and meaningful impact on advancing our capabilities in AI.

We are seeking a dynamic and experienced Manager for our AI and Machine Learning team at LinkedIn. In this role, you will lead a talented group of engineers and data scientists dedicated to developing cutting-edge solutions that enhance user experience and drive engagement across the platform. Your leadership will be crucial in shaping the direction of our AI initiatives, ensuring they align with our mission to connect the world's professionals.The ideal candidate will possess a strong background in machine learning algorithms, data analysis, and software development, as well as exceptional communication skills to effectively collaborate with cross-functional teams. If you are passionate about leveraging AI to create impactful solutions, we want to hear from you!

About Applied IntuitionApplied Intuition, Inc. is at the forefront of advancing physical AI technologies. Established in 2017 and currently valued at $15 billion, this Silicon Valley powerhouse is building the essential digital infrastructure to infuse intelligence into every moving machine on Earth. Serving a diverse range of industries including automotive, defense, trucking, construction, mining, and agriculture, Applied Intuition excels in three key domains: tools and infrastructure, operating systems, and autonomy. Eighteen of the world's top 20 automakers, along with the United States military and its partners, rely on our solutions to deliver physical intelligence. Our headquarters is located in Sunnyvale, California, with additional offices in Washington, D.C.; San Diego; Ft. Walton Beach, FL; Ann Arbor, MI; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Discover more at applied.co.As an in-office company, we expect our employees to primarily work from their Applied Intuition office five days a week. However, we value flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home, or leaving early for family commitments.Role and Team OverviewWe seek a dedicated Research Engineer (AI/RL Infrastructure) to join our Research Group at Applied Intuition. This position is perfect for engineers who design, build, and maintain large-scale machine learning systems and collaborate closely with researchers to innovate and enhance the foundational platform for next-generation physical AI systems.The Research Group's mission is to develop pioneering technologies that facilitate next-generation physical AI, focusing on two of the most challenging applications that are transforming our daily lives: end-to-end autonomous driving and robotic generalists. Our team comprises leading experts from prestigious institutions and organizations, recognized for their outstanding contributions in both academia and industry, including multiple Best Paper awards at top conferences and journals such as CVPR and ICRA. For further insights, visit appliedintuition.com/research.

Join Wayve Technologies as a Staff Machine Learning Performance Engineer, specializing in Training Efficiency. In this pivotal role, you will be responsible for enhancing the performance of our machine learning models and algorithms, ensuring they operate at peak efficiency. You will collaborate with cross-functional teams to develop innovative solutions that improve training processes, optimize model performance, and drive impactful results in autonomous vehicle technology.

Join us at Meshy as a Machine Learning Systems Intern, where your passion for AI, graphics, and innovative product development will thrive in a collaborative environment.What We're Looking For:Commit to a full-time internship for a minimum of 12 weeks.Aiming to transition to a full-time role at Meshy post-graduation (ideal candidates graduating between September 2026 and September 2027 are preferred).Open to candidates pursuing undergraduate, master's, or PhD degrees.A solid foundation in technical skills, coupled with a drive for innovation and a willingness to tackle challenges.Your RoleAs a key contributor to our team, you will assist in developing the most extensive end-to-end 3D native machine learning systems. This role encompasses the entire ML framework, from pretraining to fine-tuning and inference. We seek individuals with robust hands-on engineering capabilities, a thirst for knowledge, and the ability to excel in a dynamic, ownership-driven setting.About UsAt Meshy, we envision a world where 3D creation knows no limits. Our mission is to unleash creativity by offering a comprehensive 3D content pipeline, which includes transforming text and images into 3D models, texturing, editing, and animation rigging. We have cultivated a thriving community for creators, providing a platform to share work, draw inspiration, and utilize assets across projects. Recognized as the leader in 3D generative AI (top-ranked in the 2024 A16Z Games survey), our technology is embraced by industry giants like Meta, Square Enix, and Deepmind, impacting sectors like gaming, film, 3D printing, and robotics.Your Next Challenge3D is at the forefront of Generative AI, presenting unique challenges in training and inference. Your journey with Meshy will involve a full stack of AI responsibilities, including debugging and monitoring hardware platforms, creating training frameworks, scaling high-throughput 3D data pipelines, and collaborating on innovative model architectures with our research team.

About Applied IntuitionApplied Intuition, Inc. is at the forefront of advancing physical AI technologies. Established in 2017 and currently valued at $15 billion, this Silicon Valley powerhouse is dedicated to developing the essential digital infrastructure that will empower intelligent operations in every vehicle and machine worldwide. Our innovative solutions cater to the automotive, defense, trucking, construction, mining, and agriculture sectors, focusing on three pivotal areas: tools and infrastructure, operating systems, and autonomous capabilities. Our reputation is underscored by the trust placed in us by 18 of the top 20 global automakers and the United States military, among others. Our headquarters is in Sunnyvale, California, with additional offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Discover more at applied.co.We promote a collaborative in-office culture and expect our team members to primarily work from their Applied Intuition office five days a week. However, we also value flexibility, allowing our employees to manage their schedules responsibly, which may include occasional remote work, starting the day with morning meetings from home, or leaving early to meet family obligations.About the Role and TeamWe are seeking enthusiastic Research Scientists to join our dynamic Research Group at Applied Intuition. Our mission is to develop pioneering technologies that drive the evolution of physical AI, particularly in two transformative applications: end-to-end autonomous driving and general-purpose robotics. Our team comprises distinguished experts from leading institutions and companies, celebrated for their remarkable contributions to both academia and industry, including eight Best Paper awards at prestigious conferences such as CVPR and ICRA. Learn more about our research initiatives at appliedintuition.com/research.With access to industry-leading tools and infrastructure, our researchers can leverage millions of miles of data from extensive fleets and implement their innovative methods across diverse autonomous and robotic systems, including self-driving vehicles and autonomous machinery.

About the Institute of Foundation ModelsThe Institute of Foundation Models (IFM) specializes in designing and operating large-scale GPU supercomputing systems aimed at training cutting-edge foundation models. Our philosophy places emphasis on the interdependence of performance, fault tolerance, and scalability across various components, including model architecture, communication systems, runtime, and hardware topology.This position is pivotal to our mission — enhancing communication performance, distributed reliability, and cross-layer optimization for extensive training workloads.The MissionWe seek a highly skilled engineer to collaboratively design and optimize the communication stack for large-scale distributed training, with a focus on hybrid parallelism and Mixture-of-Experts (MoE) workloads. This is a systems-level engineering role centered on performance enhancement, distributed debugging, and communication-runtime co-design.· Design and optimize expert-parallel and hybrid-parallel communication patterns· Drive high-performance hierarchical collectives for MoE workloads· Co-design runtime orchestration with communication topology awareness· Mitigate tail latency and enhance determinism across thousands of GPUs· Architect fault-tolerant distributed execution that withstands real-world cluster failuresCore Technical Scope· Communication-compute overlap and topology-aware collective optimization· In-depth debugging of NCCL, RDMA, and custom communication layers· Implementing hybrid expert parallel strategies in modern large-scale MoE systems· Developing elastic and resilient distributed job orchestration concepts· Conducting congestion analysis and routing optimization across InfiniBand/RoCE fabrics· Executing microbenchmarking and performance modeling for communication-intensive workloadsExpected Technical Depth· Expertise in hybrid expert parallel communication strategies

About CeribellCeribell is a pioneering medical technology company dedicated to revolutionizing the diagnosis and management of patients suffering from severe neurological disorders. Our flagship product, the Ceribell System, is an innovative point-of-care electroencephalography (EEG) platform designed to meet the critical needs of patients in acute care settings. Our technology is currently utilized in numerous community hospitals, large academic institutions, and major integrated delivery networks across the nation. Our team shares a collective mission to enhance the critical care landscape through rapid seizure detection technology—join us in this transformative journey!Position Overview:We are seeking a skilled Data Scientist/Algorithm Engineer with a passion for biomedical applications, possessing a robust background in machine learning, pattern recognition, signal processing, and time-series analysis. The successful candidate will become a vital member of our data science team, tasked with the design and development of cutting-edge classification algorithms that will elevate EEG neurodiagnostics.Key Responsibilities:Utilize time-series analysis, statistical signal processing, and machine learning techniques to develop classification algorithms for various neurological conditions.Analyze datasets to identify trends and patterns, interpreting findings with a clear objective.Collaborate with clinical and business stakeholders to define project requirements and effectively communicate the results of the models and analytical solutions developed.Select and apply suitable evaluation metrics to assess algorithm and model performance, ensuring both technical accuracy and clinical significance.Document and validate models while performing statistical analyses to comply with regulatory standards for medical device algorithms.Mentor and guide junior data scientists and interns, fostering their professional development through technical direction and support.Independently manage multiple projects, prioritizing tasks effectively and aligning deliverables with key milestones to ensure timely, successful outcomes.Stay abreast of the latest advancements in machine learning and neurodiagnostics to maintain state-of-the-art algorithms.

Join Meshy as an AI Infrastructure EngineerLocated in the heart of Silicon Valley, Meshy is a pioneering force in the realm of 3D generative AI. Our mission is to Unleash 3D Creativity, revolutionizing the content creation process. We empower both professional artists and enthusiastic hobbyists to effortlessly craft extraordinary 3D assets, converting text and images into breathtaking 3D models in mere minutes. What used to require weeks of effort and thousands of dollars now takes just 2 minutes and costs only $1.Our elite team comprises leading experts in computer graphics, AI, and artistry, featuring alumni from prestigious institutions such as MIT, Stanford, and Berkeley, alongside seasoned professionals from Nvidia and Microsoft. With a diverse workforce spread across North America, Asia, and Oceania, we cultivate a culture of innovation aimed at solving global 3D challenges. We are backed by top-tier venture capital firms including Sequoia and GGV, having successfully raised $52 Million in funding.Meshy stands as the market leader, acclaimed as the No.1 in popularity among 3D AI tools (according to 2024 A16Z Games) and leading in web traffic (as per SimilarWeb, with 3 Million monthly visits). Our platform supports over 5 Million users and has facilitated the generation of 40 Million models.Our Founder and CEO, Yuanming (Ethan) Hu, earned his Ph.D. in graphics and AI from MIT, where he created the highly regarded Taichi GPU programming language (27K stars on GitHub, utilized by over 300 institutes). His influential work includes an honorable mention for the SIGGRAPH 2022 Outstanding Doctoral Dissertation Award and more than 2,700 research citations.Your RoleThis position merges platform engineering, site reliability, and applied ML systems. You will be responsible for ensuring the reliability, scalability, and operability of Meshy's AI model serving stack and core engineering infrastructure. The team manages a conventional production infrastructure (CI/CD, build systems, deployment, runtime environments) while developing a model-serving platform that links the models created by our Research Team to product-facing backend systems.This role is systems-heavy, focused on production, and dedicated to transforming experimental model artifacts into robust, observable, and cost-efficient services.Key ResponsibilitiesEnsure production reliability: manage availability, latency, error budgets, incident response, postmortems, and follow-ups.Develop and maintain observability frameworks: metrics, logs, traces, and alerting systems.