Training Performance Engineer in United States

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking a Signal Integrity Engineer to join our growing team. The ideal candidate will have a wealth of exposure designing high speed interconnects, breakout design, material trade-offs and verification. A background in electrical engineering, electronics or relevant fields is required. Must love all things high speed! This role is hybrid, based out of Santa Clara, CA or Austin, TX or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You have a Bachelor’s degree in Electrical Engineering (or equivalent) and 5+ years working in high-speed digital design with a focus in high-speed PCB or package design at 10Gbps and above (e.g. 100GbE, GDDR6, PCIe Gen5+). You’re comfortable working with high-speed performance metrics such as ICR, ERL, COM, NEXT, and FEXT as well as knowledge of high-speed connector technologies, including NPO, CPO, and emerging standards. You are proficient with PCB ECAD tools (ideally Cadence Allegro). You communicate clearly (written and verbal), think critically, and love solving complex signal integrity problems. You’re enthusiastic about all things high speed and enjoy collaborating acro

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. As our TT-Distributed Software Engineer, you will develop and optimize distributed software systems that power the most efficient and highest-performing AI and HPC clusters. In this role, you'll work on distributed programming across multiple nodes, utilizing systems programming, inter-node communication, and Tenstorrent’s scalable architectures to advance the state-of-the-art distributed inference and training infrastructure. This role is hybrid, based out of Santa Clara, CA; Austin, TX; or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Strong C or C++ engineer with solid foundations in systems programming, operating systems, and distributed systems principles. Enthusiastic about distributed computing, including IPC, socket programming, and cluster resource coordination. Comfortable reasoning about scalability, fault tolerance, and performance across multi-node environments. Curious and first-principles thinker who challenges conventional approaches to distributed system design. Motivated to grow into a deep technical expert in large-scale distributed AI infrastructure. What We Need Architect, implement, and optim

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is building the world’s fastest, most efficient AI compute clusters. TT-Fabric is the high-performance nervous system of this platform: the low-level networking layer that lets thousands of RISC-V and AI processors snap together into a single, massively parallel distributed supercomputer. If you love squeezing nanoseconds out of hot paths, designing protocols that move data at absurd scale, and turning messy hardware constraints into elegant distributed systems, this is an opportunity to shape the fabric that future AI models will run on This role is hybrid based out of Santa Clara, CA; Austin, TX; or Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who We Are Strong systems engineer with deep C or C++ experience and comfort working in low-level or bare-metal environments. Passionate about hardware-software interaction, performance tuning, and eliminating inefficiencies at the protocol level. Curious about networking, synchronization, and communication across large clusters. Comfortable reasoning from first principles and challenging industry conventions. Motivated by building infrastructure that directly impacts large-scale

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking a senior High Speed Interconnect / Signal Integrity Engineer to design and validate high-bandwidth links for large-scale AI systems. You will define, model, and qualify interconnect solutions across copper and optical technologies for next-generation AI inference and training clusters. This role is on-site in Santa Clara, CA, Austin, TX, or Toronto, Canada. We welcome candidates at various experience levels. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting Who You Are An experienced electrical engineer with a Bachelor’s or Master’s in Electrical Engineering. 5+ years working on high-speed communications (100G–1.6T), including signal integrity, channels, and links. Comfortable building and owning link and channel budgets and making clear tradeoffs between reach, loss, BER, and margin. Hands-on with SI tools and lab equipment such as Keysight ADS, VNAs, TDRs, BERTs, and protocol analyzers. Familiar with cable specification and testing, as well as accelerated life testing, mating life, and failure analysis. Able to collaborate across hardware, systems, and manufacturing teams; manufacturing/DFM/DTM experience is a plus. What We Need Define and specify high-speed interconnect architectures

About the Team pAGI Infra team builds and operates the systems that make large-scale model training and evaluation reliable, efficient, and easy to run. Our work spans distributed training infrastructure, inference and grading platforms, compute scheduling, and research tooling. We partner closely with researchers and engineering teams to turn new research needs into dependable infrastructure, improve GPU efficiency, and shorten the path from an experiment to a validated model. About the Role We’re looking for an AI Systems Engineer to help scale the infrastructure behind our training and evaluation workflows. You’ll own projects from identifying bottlenecks and designing solutions through deployment and operation. The work combines distributed systems engineering, performance optimization, and close collaboration with researchers. You might build a shared grading service, improve resource allocation across workloads, or bring a new training stack into production — directly improving how quickly and reliably research moves forward. In this role, you will: Build and operate infrastructure for large-scale training and evaluation, improving reliability, throughput, and resource efficiency. Develop shared inference and grading platforms with automated capacity management, health monitoring, and visibility into performance. Improve compute scheduling and resource allocation to reduce idle GPU time and help workloads recover quickly from failures. Diagnose bottlenecks across training, inference, and orchestration, and work across teams to improve end-to-end performance. Build self-service tools, automated validation, and observability that help researchers launch experiments, diagnose issues, and compare results with less manual intervention. You might thrive in this role if you: Are excited about the potential of personal AGI and want to build the infrastructure that enables it. Have strong software engineering fundamentals and experience building or operating large-scal

As a Software Engineer - Frontend on a feature team, you'll be responsible for building an intuitive, responsive product. Your work will help thousands of customers to monitor the health and performance of their systems, no matter the scale. In this capacity, you’ll use tools like React and Typescript to help streamline the flow of data from platform to user, enable seamless pivots from one view to the next, and build a powerful yet easy-to-use platform. You will work on complex frontend challenges for thousands of customers with huge sets of data and work on exciting scalability and performance challenges. Our users are also developers so you will feel close to the product and have an impact on the development world. You will be part of a front-end community of 200+ passionate frontend engineers and you will be surrounded by experts. Join us to build the next generation of high-scale, data-powered features for our customers. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Work closely with backend engineers, product managers and designers to inform/refine/validate design concepts Break down complex features into distributable engineering tasks and rollout plans Design and deliver features that have direct impact on thousands of users Experiment with and advocate for new systems, design patterns, and tooling Participate in hackathons, sync with other Front end engineers at the monthly demos meeting and yearly Front End summit Use and contribute to a best-in-class in-house design system Own meaningful parts of our service, improve performance and address scalability limits Work in a fast-paced, high-growth environment that values diversity of talent, excellence of product, and exciting engineering challen

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Research Engineer to help OpenAI models solve chip-design problems through reinforcement learning, tool use, and evaluation. You’ll own experiments from the initial idea through implementation and analysis. That means building environments and evaluations, running training, investigating failures, and using the results to decide what to try next. You’ll also build the software needed to make those experiments reliable and reproducible. We value strong coding fundamentals, careful experimental judgment, and the ability to make progress independently. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build RL environments and evaluations for tasks such as RTL generation, design verification, and physical design optimization. Develop and test approaches that help models use chip-design tools and improve power, performance, and area while preserving correctness. Design experiments, establish baselines, and measure whether improvements hold up on new tasks and designs. Investigate failures across model behavior, rewards, evaluation tools, and experiment infrastructure. Improve iteration speed through better tooling, faster evaluations, and proxy rewards that reflect the outcomes we care about. Turn successful experiments into reusable research code and training workflows, working closely with researchers and engineers. You might thrive in this ro

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Fraud Data team at Plaid builds the machine learning systems that power Plaid’s fraud detection products, leveraging insights from across Plaid’s network to help identify and stop fraud before it happens. Our team works across the full data science and machine learning lifecycle—from discovering new signals and experimenting with models to deploying and optimizing them in production. We continuously learn from real-world model performance and customer feedback to improve our systems and develop new ways to protect customers and consumers from evolving fraud threats. As a Senior Machine Learning Engineer on Plaid's Fraud Data team, you will develop models that improve fraud detection for our customers. You will identify predictive patterns in Plaid's network data and lead projects from initial experiments through model deployment and ongoing improvement. Investigate fraud patterns and model errors to identify new signals, improve detection, and expand coverage across customers and use cases. Develop training datasets and predictive features, addressing challenges such as incomplete labels, class imbalance, data leakage, and changing fraud behavior. Design, train, and tune model

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Software Engineer to build the research infrastructure and tooling that help OpenAI models design silicon. You’ll turn chip-design workflows into reliable environments for reinforcement learning and evaluation, and make it easier for researchers to run experiments and iterate on new ideas. You’ll move between software engineering, tool integration, and open research problems. We value strong coding fundamentals, clear technical judgment, and independent execution. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build and maintain infrastructure for reinforcement learning environments, evaluations, and long-running experiments. Integrate electronic design automation (EDA) tools into workflows for RTL generation, verification, and physical design optimization. Improve experiment reliability, reproducibility, observability, and performance; debug failures across tools, services, and infrastructure. Develop tooling and model harnesses that let researchers test ideas quickly and measure correctness and power, performance, and area (PPA). Collaborate with researchers and engineers to turn successful experiments into reusable systems and training workflows. Own ambiguous projects end to end, communicate progress, and use results to guide the next iteration. You might thrive in this role if you: Have strong software engineering fundamentals, with

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Driver, Marketplace, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing petabyte-scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. The Fulfillment group, within the Marketplace at Lyft, is responsible for determining what inventory can be reliably offered for a given rider session and fulfilling rider requests. The group comprises several sub-teams that generate feasible offers for riders, match rider requests with drivers, and maintain a distributed state machine to track rides and drivers from request through completion. We are seeking a Machine Learning Engineer to join the Fulfillment team and lead the design, development, and deployment of state-of-the-art machine learning systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging machine learning and data science. Responsibilities: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform Evaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement

The Team As Datadog’s in-house product experts, the Technical Escalation Engineering (TEE) team plays a critical role in driving our global success. We enable our customers, from the world’s most innovative startups to the largest enterprises. Through deep technical expertise, relentless problem-solving, and exceptional customer engagement, we educate, guide, and troubleshoot, delivering high-impact solutions that shape the customer experience. Whether through hands-on technical call, in-depth fact findings meeting, or complex investigations, we set the gold standard for technical excellence and customer advocacy. As part of our TEE team, you’ll tackle the most challenging technical problems, collaborate directly with Engineering and Product to refine and evolve our platform, and mentor teams worldwide, elevating the technical bar at every level. Role Summary As part of the Technical Escalation Engineering (TEE) team, you’ll operate at the heart of Datadog’s ecosystem, working at the intersection of Technical Solutions, Engineering, Product, and our Customers. Every challenge you take on will directly impact the performance, scalability, and success of both our clients and our platform. You’ll be in an environment that moves fast, challenges you daily, and rewards curiosity, ownership, and technical excellence. This is your chance to shape the future of observability and security, driving innovation, mentoring teams, and influencing product direction while witnessing your expertise make an immediate and lasting impact. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Develop deep technical expertise and continuously learn as the product evolves. Investigate complex escalations, lead high-stakes technical calls, and drive solutions for

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About The Role The Security Team is responsible for securing all things Sentry: our customers, our code, and everything in between. We are a small but growing team with broad scope, high trust, and the autonomy to tackle hard security problems with creativity and an engineering mindset. We work at a company with a strong developer culture, building a product that millions of developers genuinely love and rely on. That context shapes everything about how we operate. We take a pragmatic approach to preventing and responding to security risks. In this role not only will you build and contribute to systems which detect malicious activity, you will have the unique opportunity to implement new controls to prevent future incidents. You will work across detection and response and corporate security domains. You'll contribute to practices that keep Sentry secure as we grow: alert triage for corporate and production, detection engineering, deploying preventative controls, identity and access management, investigations and incident response, and more. You'll partner with teams across the company to prevent and respond to security incidents. You will work as a technical collaborator who prioritizes preventative controls, defense in depth, and high signal alerting practices. As Sentry expands our agentic product capabilities and development practices, you'll also find yourself at the frontier of a new set of security approaches and challenges. In this role, you will Maintain, improve, and own detection engineering systems. We own and operate our own detection stack and are building agentic triage with thoughtful security response and orc

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About The Role The Security Team is responsible for securing all things Sentry: our customers, our code, and everything in between. We are a small but growing team with broad scope, high trust, and the autonomy to tackle hard security problems with creativity and an engineering mindset. We work at a company with a strong developer culture, building a product that millions of developers genuinely love and rely on. That context shapes everything about how we operate. As a Security Engineer on this team, you'll work across application and platform security domains. You'll contribute to the practices that keep Sentry secure as we grow: security reviews, threat modeling, vulnerability management, and embedding secure coding practices into an engineering organization that cares about doing things right. You'll partner closely with product and engineering teams to influence how features are designed and built from the start. You will work as a technical collaborator who helps make the secure path the obvious one. As Sentry expands our agentic product capabilities and development practices, you'll also find yourself at the frontier of a new set of security challenges. In this role, you will Support and help mature Sentry's security review program. From secure code review, to architecture review, and threat modeling. You'll help build the processes, tooling, and culture which make security a natural part of how we ship and operate. Contribute to mature vulnerability management practices. Intake, triage, prioritization, remediation tracking, and support of our bug bounty and responsible disclosure program. Advocate for secure-by-desig

About the Team OpenAI, in partnership with our capital and technology partners, is building a global network of advanced datacenters to support the most demanding AI workloads. The Infrastructure Quality team ensures that all datacenter systems are manufactured, delivered, and commissioned to the highest standards of quality, reliability, and performance. We work closely with manufacturing partners, general contractors, engineering teams, and operations staff to ensure that every component is delivered ready for installation, startup, and long-term service. Our work spans from vendor qualification through commissioning, ensuring operational readiness across our global portfolio. About the Role We are seeking an experienced Manufacturing Quality Engineer (MQE) to establish, implement, and manage a manufacturing-focused quality program for datacenter infrastructure. This role will be responsible for vendor oversight, quality assurance, process improvement, and issue resolution for all critical systems. You will lead vendor audits, monitor performance metrics, and coordinate corrective actions to ensure predictable delivery schedules, reduced risks, and operational reliability. By partnering with vendors, construction teams, and internal stakeholders, you will help ensure OpenAI’s datacenters are delivered on time and built to the highest operational standards. Travel Domestic and international travel as needed (estimated 40–60%) to manufacturing sites, datacenter locations, and partner facilities. Key Responsibilities Vendor Oversight & Performance Management Conduct manufacturing evaluation, audits, and improve vendor performance across production, inspection, testing, and delivery phases. Develop and track quality metrics to assess manufacturing performance and identify trends. Partner with vendors to refine processes, training, and quality controls to mitigate risks before shipment. Program Development & Execution Develop and maintain a datacenter-focused m

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a Sr. Studio Software Engineer for Roblox Studio Platform, you will be a key contributor to the evolution of Roblox Studio, the primary IDE for making massive multiplayer online games on the Roblox platform. Studio provides the mission-critical tools for 3D modeling, animation, and the complete SDLC for millions of developers. We are looking for engineers who thrive on an adventure into the unknown and have experience across various systems, Operating Systems, Game Engines, and Application Frameworks. You’ll tackle projects involving: Core User Features: Architecting application frameworks, windowing systems, and code generation. “AI Native” Features: Pioneering scalable systems that extend to complex, agentic use cases. Foundational Architecture: Driving OS integration, extensibility, and customizability at the deepest levels. Central Backend Systems: Engineering the infrastructure to power a consistent, high-performance UX. Design Evolution: Collaborating with UX designers to translate Studio into a modern, consistent design language. You Will: Design and execute the technical direction to drive the future extensibility and adaptability of the application. Own and deliver complex techn