Machine Learning Systems Intern at Meshy | Sunnyvale

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 Septe…

Who You AreWe are seeking talented Machine Learning Systems Engineers to contribute to the development of the world's largest end-to-end 3D native machine learning systems. You will collaborate on our comprehensive ML framework tailored for 3D applications, encompassing pretraining, fine-tuning, inference, and more. We value strong hands-on engineering skills, a passion for learning, and an ability to excel in a dynamic, high-responsibility environment.Who We AreAt Meshy, we envision a world where 3D creation is limitless and accessible to all. Our mission is clear: unleash creativity. We have developed a comprehensive pipeline for 3D content that spans text/image to 3D, texturing, texture editing, animation rigging, and beyond. Additionally, we foster a vibrant community for creators to share their work, draw inspiration from others, and utilize our platform as an asset marketplace for their games and prototypes. Recognized as the No.1 in popularity among 3D AI tools (according to the 2024 A16Z Games survey), Meshy delivers real value to enterprises such as Meta, Square Enix, and DeepMind, as well as millions of end-users. Our technology powers game and film production, 3D printing, industrial product design, user-generated content features, and even training simulations for robotics and physical AI.Your Next Challenge3D is the exciting new frontier of Generative AI, and your role at Meshy will present unique challenges in both training and inference. You will engage with the full stack of AI, from debugging and monitoring hardware platforms, building training frameworks, scaling high-throughput 3D data pipelines, collaborating with researchers on novel model architectures, to developing efficient inference engines for diffusion models and more. Here are some specific challenges on the training side:Collaborate closely with researchers to co-design the next frontier of 3D & Spatial AI.Develop and refine modern PyTorch solutions for maximum parallelism and efficiency, establishing a clean and intuitive training infrastructure for our foundational models.Identify bottlenecks and optimize for high throughput & efficient distributed model training across hundreds to thousands of GPUs.Implement and maintain 3D-specific custom operators in Triton or CUDA.Design and uphold novel data-loading frameworks and libraries.

Who You AreAs a driven and innovative researcher, you thrive in dynamic environments and possess a self-starter mentality. A true collaborator, you excel at executing tasks efficiently. With a profound understanding of transformer architectures, you are proficient in Python and tensor programming. Your vision for AI extends beyond traditional linear sequences, and you embrace the concept of 'the scaling law'. You are adept at converting abstract ideas into tangible research objectives and implementation strategies. When communicating complex technical concepts, you provide clarity and insight. You welcome new ideas and eagerly share your expertise with the team. Your contributions are aimed at delivering real-world advantages for our researchers, engineers, and millions of users, as you help propel our mission to enhance AI's capabilities in understanding and generating 3D environments.Who We AreAt Meshy, we envision a limitless and accessible landscape for 3D creation. Our mission is straightforward: to unleash creativity. We have developed a comprehensive pipeline for 3D content creation, spanning from text/image inputs to 3D modeling, texturing, texture editing, animation rigging, and more. Additionally, we foster a vibrant community for creators, facilitating the sharing of works, drawing inspiration, and utilizing our platform as an asset marketplace for games and prototypes. Recognized as the top choice among 3D generative AI tools (per the 2024 A16Z Games survey), we generate substantial value used by enterprises, including Meta, Square Enix, and DeepMind, as well as millions of users. Meshy is instrumental in game and film production, 3D printing, industrial design, and enhancing features such as user-generated content and training simulations for robotics and physical AI.Your Next ChallengeAs a pivotal member of our team of research scientists and machine learning engineers, you will spearhead the development of our core 3D-native generative foundational model. In this role, you will engage in foundational research to elevate 3D AI, apply insights from various ML domains, and advance the state of the art. You will also pursue long-term ambitious research objectives while establishing intermediate milestones.Key responsibilities include:Designing, training, and refining large-scale 3D generative models, encompassing pre-training, post-training, and emerging paradigms in diffusion, flow matching, and multi-modal learning.

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.

About the Role Meshy is looking for a Fullstack Engineer Intern in Sunnyvale. This internship offers practical experience building web applications and services alongside a collaborative team. Interns contribute to different stages of the development lifecycle, from planning to implementation. What You Will Do Develop and maintain web applications and backend services Work with team members across the development process Gain hands-on experience with modern technologies

Join our dynamic team as a Senior Machine Learning Engineer at Intuitive, where you will play a pivotal role in advancing our robotic surgery technologies. We are looking for a talented individual with a strong background in machine learning, artificial intelligence, and data analysis.

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...

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.

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.

About Applied IntuitionApplied Intuition, Inc. is revolutionizing the future of physical AI. Established in 2017 and currently valued at $15 billion, this Silicon Valley innovator is developing the essential digital framework to infuse intelligence into every moving machine globally. Our services cater to vital sectors such as automotive, defense, trucking, construction, mining, and agriculture, focusing on three main pillars: tools and infrastructure, operating systems, and autonomy. Renowned leaders, including 18 of the top 20 global automakers and the United States military along with its allies, rely on our solutions for advancing physical intelligence. Our headquarters is in Sunnyvale, California, with additional offices located 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.As an in-office company, we expect our employees to primarily work at the Applied Intuition office five days a week. However, we understand the need for flexibility and trust our employees to manage their schedules responsibly. This could involve occasional remote work, starting the day with morning meetings from home before coming to the office, or leaving earlier when necessary for family commitments.About the Role:We are actively seeking passionate Research Interns to become part of our Research Group at Applied Intuition. Our mission is to develop pioneering technology that empowers the next generation of physical AI, particularly in the most challenging domains that are transforming our daily lives: end-to-end autonomous driving and robotic generalists. Our team comprises distinguished experts from leading institutions and companies, acclaimed for their outstanding academic and industry contributions, including eight Best Paper awards at top conferences and journals such as CVPR and ICRA. For more information, visit appliedintuition.com/research.With access to industry-leading tools and infrastructure, our researchers can utilize millions of miles of data from extensive fleets and implement their developed methods across various autonomous and robotic systems, including self-driving cars and trucks, autonomous mining and construction machines, humanoid robots, and dexterous hands.

About the Institute of Foundation ModelsWe are an innovative research laboratory focused on the creation, comprehension, application, and risk management of foundation models. Our mission is to propel research forward, cultivate the next generation of AI innovators, and contribute significantly to a knowledge-driven economy.Joining our team presents a unique opportunity to engage in the core of advanced foundation model training, collaborating with leading researchers, data scientists, and engineers as we address the most pivotal and influential challenges in AI advancement. Your work will involve the creation of groundbreaking AI solutions with the potential to revolutionize entire industries. Employing strategic and innovative problem-solving skills will be crucial in establishing MBZUAI as a premier global center for high-performance computing in deep learning, fostering remarkable discoveries that inspire future AI trailblazers.

Cerebras Systems is at the forefront of AI technology, creating the world's largest AI chip that is 56 times the size of traditional GPUs. Our innovative wafer-scale architecture combines the compute power of dozens of GPUs into a single chip, simplifying the programming experience. This unique design enables us to achieve unparalleled training and inference speeds, allowing machine learning practitioners to run extensive ML applications seamlessly without the complexities of managing numerous GPUs or TPUs.Our clientele includes premier model laboratories, multinational corporations, and pioneering AI-driven startups. Notably, OpenAI has recently formed a multi-year collaboration with Cerebras, aiming to harness 750 megawatts of computational scale to revolutionize key workloads through ultra-high-speed inference.Thanks to our cutting-edge wafer-scale architecture, Cerebras Inference delivers the fastest Generative AI inference solution globally, achieving speeds over ten times faster than GPU-based hyperscale cloud inference services, thus transforming the user experience of AI applications and enabling real-time iterations and enhanced intelligence through additional agentic computation.Responsibilities:Lead the design and implementation of advanced system-level debugging, validation, and observability platforms.Develop automated systems for collecting and analyzing numerical data and execution anomalies.Create visualization and analysis tools to facilitate efficient root-cause investigations.Build frameworks for failure classification, regression detection, and anomaly monitoring.Enhance compilers, runtimes, and programming interfaces to support sophisticated profiling and instrumentation.Improve workflows related to system bring-up, low-level debugging, and validation.Collaborate cross-functionally with teams in compiler, hardware, firmware, runtime, and infrastructure domains.Establish best practices to ensure debuggability, reliability, and operational excellence.Lead impactful initiatives and support incident response while driving long-term corrective solutions.

Cerebras Systems revolutionizes the AI landscape with the creation of the world’s largest AI chip, a remarkable 56 times larger than conventional GPUs. Our innovative wafer-scale architecture delivers the computational power of numerous GPUs on a single chip, simplifying programming efforts for users. This unique approach enables Cerebras to achieve unparalleled training and inference speeds, empowering machine learning practitioners to seamlessly execute large-scale ML applications without the complexities of managing hundreds of GPUs or TPUs.Our clientele includes leading model laboratories, global enterprises, and pioneering AI-native startups. Notably, OpenAI recently announced a multi-year partnership with Cerebras to deploy 750 megawatts of scale, significantly enhancing key workloads with ultra-high-speed inference.Thanks to our groundbreaking wafer-scale architecture, Cerebras Inference provides the fastest Generative AI inference solution globally, exceeding the performance of GPU-based hyperscale cloud inference services by over ten times. This significant speed enhancement transforms the user experience of AI applications, facilitating real-time iterations and augmented intelligence through additional agentic computation.About The RoleWe are on the lookout for a highly skilled and experienced AI Infrastructure Operations Engineer to oversee and manage our state-of-the-art machine learning compute clusters. In this role, you will have the unique opportunity to work with the world’s largest computer chip, the Wafer-Scale Engine (WSE), and the systems that leverage its extraordinary power.You will play a pivotal role in ensuring the health, performance, and availability of our infrastructure, maximizing compute capacity, and supporting our expanding AI initiatives. This position requires an in-depth understanding of Linux-based systems, expertise in containerization technologies, and experience in monitoring and troubleshooting complex distributed systems. The ideal candidate is a proactive problem-solver with a strong background in large-scale compute infrastructure who is reliable and committed to customer success.

Join Our Team at MeshyBased in Silicon Valley, Meshy stands at the forefront of 3D generative AI, dedicated to Unleashing 3D Creativity by revolutionizing the content creation process. Our platform enables both professional artists and enthusiasts to effortlessly craft extraordinary 3D assets, transforming text and images into beautiful 3D models in mere minutes. What once required weeks and substantial financial investment can now be achieved in just two minutes for only $1.Our exceptional team comprises leading experts in computer graphics, AI, and art, including alumni from prestigious institutions such as MIT, Stanford, and Berkeley, along with seasoned professionals from Nvidia and Microsoft. Our global workforce spans North America, Asia, and Oceania, cultivating a diverse and innovative culture aimed at tackling global 3D challenges. Supported by top venture capital firms like Sequoia and GGV, Meshy has successfully raised $52 Million to fuel our growth.As the market leader recognized as the No.1 platform among 3D AI tools (2024 A16Z Games) and the top site in traffic analytics (SimilarWeb, with 3 Million monthly visits), Meshy boasts over 5 Million users and has facilitated the creation of 40 Million models.Our founder and CEO, Yuanming (Ethan) Hu, earned his Ph.D. in graphics and AI from MIT, where he developed the renowned Taichi GPU programming language (27K stars on GitHub, utilized by over 300 institutions). His influential work has garnered multiple accolades, including an honorable mention for the SIGGRAPH 2022 Outstanding Doctoral Dissertation Award and over 2,700 research citations.Position OverviewWe are excited to welcome our inaugural Senior Data Scientist to the US team. In this pivotal role, you will design, construct, and implement advanced analytical and machine learning solutions that will significantly influence our product direction, growth strategies, and monetization efforts.Key projects will include:Developing recommendation systemsConducting user segmentation and behavioral modelingPerforming churn analysis, including NLP-based parsing of text feedbackForecasting lifetime value (LTV) and revenue predictionsBusiness and growth forecastingThis position necessitates a robust technical foundation, keen business acumen, and the capability to translate analytical models into actionable insights.

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.

About Applied IntuitionApplied Intuition, Inc. is at the forefront of advancing physical AI technologies. Established in 2017 and currently valued at $15 billion, our Silicon Valley-based company is dedicated to creating the essential digital infrastructure that empowers intelligence across all moving machines globally. Our solutions serve critical sectors including automotive, defense, trucking, construction, mining, and agriculture, focusing on three main domains: tools and infrastructure, operating systems, and autonomy. Trusted by 18 of the top 20 global automakers, as well as the U.S. military and its allies, Applied Intuition is committed to delivering unparalleled physical intelligence solutions. Our headquarters is located in Sunnyvale, California, complemented by offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. For more information, visit applied.co.We prioritize in-office collaboration and expect our employees to work primarily from our Applied Intuition office five days a week. However, we value flexibility and trust our team members to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving early when necessary to accommodate personal commitments.About the RoleAs an Engineering Manager on our Machine Learning Platform team, you will lead an exceptional group of engineers dedicated to building the infrastructure that enables Physical AI at scale. Your team will oversee three pivotal areas: Training & Inference Orchestration, where we develop frameworks to efficiently schedule and execute extensive tasks across thousands of GPUs; GPU Cluster Architecture, where we design and expand what will become the industry's largest GPU cluster for Physical AI; and Performance Optimization, where we maximize hardware utilization, throughput, and cost efficiency for large-scale training and inference workloads. You will collaborate at the intersection of systems engineering and machine learning, working directly with stack development and research teams to eliminate bottlenecks and expedite the transition from experimentation to production.

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!

Join our ETA Team at DoorDash as a Machine Learning Engineer. In this dynamic role, you will harness the power of machine learning to drive innovation and optimize our delivery processes. You will collaborate with cross-functional teams to develop and deploy scalable machine learning models that enhance customer experience and operational efficiency.

Join our innovative team at intuitive as a Machine Learning Engineer, where you'll have the chance to work on cutting-edge AI technologies that are shaping the future. In this role, you will design, develop, and implement machine learning models that will drive impactful solutions across various sectors.As a critical member of our team, you will collaborate with data scientists and engineers to enhance our product offerings, ensuring they are not only effective but also scalable. This is an exceptional opportunity for those eager to leverage their skills in a thriving environment.

About the Institute of Foundation ModelsWe are a pioneering research laboratory focused on the development, understanding, application, and risk management of foundational models. Our mission is to propel research forward, cultivate the next generation of AI innovators, and make substantial contributions to a knowledge-driven economy.Join us and collaborate with top-tier researchers, data scientists, and engineers on the forefront of foundational model training. Engage in solving critical challenges that can redefine entire sectors through advanced AI solutions. Your strategic and innovative problem-solving skills will play a vital role in positioning MBZUAI as an international leader in high-performance computing for deep learning, facilitating discoveries that will inspire future AI trailblazers.The Role We are seeking a skilled distributed ML infrastructure engineer to enhance and expand our training systems. You will collaborate closely with distinguished researchers and engineers to:• Develop and scale distributed training frameworks (e.g., DeepSpeed, FSDP, FairScale, Horovod)• Implement distributed optimizers based on mathematical specifications• Create robust configuration and launching systems across multi-node, multi-GPU clusters• Manage experiment tracking, metrics logging, and job monitoring for enhanced external visibility• Enhance the reliability, maintainability, and performance of training systems• While much of your work will support large-scale pre-training, prior pre-training experience is not mandatory; strong infrastructure and systems expertise are our primary focus.Key Responsibilities • Distributed Framework Ownership – Extend or adapt training frameworks (e.g., DeepSpeed, FSDP) to accommodate new applications and architectures.• Optimizer Implementation – Convert mathematical optimizer specifications into distributed implementations.• Launch Config & Debugging – Develop and troubleshoot multi-node launch scripts with adaptable batch sizes and parallelism strategies.