Machine Learning Infrastructure Engineer Jobs

About the Team DoorDash’s ML Serving Platform delivers tens of millions of predictions per second , powering search, recommendations, advertising, delivery estimates, and logistics across DoorDash, Wolt, and Deliveroo. Our customers are modelers and engineering teams across our internal business verticals. We build self-serve infrastructure that empowers them to bring new models into production, adopt open source software and models, and expand what they can accomplish with machine learning at scale. We work at the intersection of a rapidly evolving open source ecosystem and demanding production workloads. With active customer demand and growing modeling ambitions, we’re advancing the infrastructure behind today’s predictions while building the capabilities that enable the next generation of ML innovation. About the Role You’ll help build the next generation of our ML serving platform, connecting request routing and online feature retrieval with model inference on CPU and GPU infrastructure. You’ll tackle challenging infrastructure problems involving latency, reliability, resource efficiency, and scale, and make those capabilities accessible through self-serve tools and workflows. Working alongside experienced platform engineers, you’ll own defined projects from technical design and implementation through testing, rollout, and production support. You’ll partner directly with internal teams to understand emerging modeling requirements, remove adoption barriers, and turn advances in open source technology into measurable production improvements. You’re excited about this opportunity because you will… Empower modelers through self-serve infrastructure. Build tools, APIs, and workflows that help internal teams deploy, configure, validate, and operate models independently, accelerating ML adoption across business verticals. Bring open source innovation into production. Evaluate and integrate evolving inference frameworks and enable open source models, translating promisi

Build something people love Wealthsimple is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. Wealthsimple currently serves more than 4 million Canadians and holds over $155 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada. We're proud of what we've built — and we're just getting started. Read our Culture Manual and learn more about how we work . ML Platform & Infrastructure Team The Machine Learning Infrastructure & Platform team builds the foundational architecture powering AI and GenAI initiatives across Wealthsimple. We sit at the intersection of production MLOps and cutting-edge GenAI enablement. As our AI footprint expands rapidly, our priority is evolving our robust MLOps foundations into a scalable, high-performance LLM serving and routing platform. We build self-serve systems that allow Data Scientists and Engineers to host open-source LLMs reliably, optimize inference latencies, manage GPU infrastructure, and benchmark model performance safely in production. The Role We are looking for an experienced MLOps or ML Platform Engineer who is excited to pivot their deep background in model orchestration, serving, and platform tooling toward solving the unique challenges of LLM inference and infrastructure . In this role, you will bridge the gap between traditional MLOps (model lifecycles, pipeline orchestration, serving infrastructure) and modern GenAI stack requirements (vLLM, GPU cluster management, intelligent model routing, and automated Evals). You will take end-to-end ownership of setting the technical direction for operating enterprise-grade LLM systems company-wide. In this role, you will have the opportunity to: Turn MLOps expertise to GenAI: Transition traditiona

Scale AI’s Public Sector business is growing quickly as government agencies adopt AI to support critical national security, defense, and public sector missions. We’re looking for a hands-on Engineering Manager to lead a team of software engineers building core products and infrastructure for these customers. This role is ideal for someone who thrives in technical environments, enjoys managing teams while staying close to the code, and wants to work on meaningful problems that impact real world operations across the U.S. government. You’ll play a critical role in delivering backend systems, distributed platforms, and ML tooling used by our public sector partners—all while helping your team grow and execute. You’ll split your time between technical planning and execution (50%) and people management and team development (50%) , leading a team of 6-8 engineers. You’ll work cross-functionally with product, security, and customer-facing teams to ensure our engineering efforts meet complex federal compliance, security, and performance needs. Must be able to commute to office three times per week You will: Recruit a high-performing engineering team. Drive engineering productivity. Provide guidance, mentorship, and technical leadership to a team of engineers working on Generative AI projects. Collaborating with cross-functional teams to define, design, and execute strategic roadmap. Navigate and deliver outcomes while navigating through complex public sector compliance requirements and frameworks. Design and implement scalable backend systems for Federal customers, leveraging Scale's modern and cloud-native AI infrastructure Develop distributed systems, data-intensive applications, and machine learning infrastructure to enable real impact for mission owners Build robust and reliable backend systems that can serve as standalone products, empowering customers to accelerate their own AI ambitions Participate actively in customer engagements, working closely with sta

Zoox is looking for an AWS Cloud Security Engineer to lead the design and implementation of secure, scalable, and software-defined infrastructure in our AWS cloud environment. This role is responsible for establishing best-in-class security practices across AWS, driving automation-first infrastructure security, and partnering with engineering and platform teams to embed security into every layer of our technology stack. You’ll act as a security champion, ensuring that infrastructure designs meet the highest standards of confidentiality, integrity, and availability — while maintaining operational efficiency and scalability through Infrastructure as Code (IaC). In this role, you will: Define and own the multi-year security architecture and roadmap for Zoox's robots and fleet, spanning embedded/firmware, in-vehicle networks, cloud, and supporting infrastructure. Partner with hardware, firmware, autonomy, and infrastructure engineering teams to embed security requirements into system design from the ground up, rather than bolting them on after the fact. Lead threat modeling and architecture reviews for new vehicle platforms and major feature launches, identifying and prioritizing systemic risk across the fleet. Set technical standards and guardrails - secure boot, key management, network segmentation, update/OTA security, and more - and drive their adoption across engineering teams. Represent Product Security in cross-functional and leadership discussions, translating technical risk into business and safety impact for the organization. Qualifications 10+ years of experience in security engineering, including significant time in an architect, staff, or technical lead capacity. Deep expertise in embedded/IoT security, including secure boot, TPM/TEE, cryptographic key management, and hardened firmware/OS design. Demonstrated experience architecting security for complex, physical/cyber-physical sys

About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role We are looking for a Member of Technical Staff, Infrastructure Compute to lead and manage large-scale GPU computing clusters powering our AI training and deployment workloads. You'll work at the intersection of systems engineering and machine learning infrastructure, owning the reliability, scalability, and efficiency of the compute platform that our research and engineering teams depend on. This is a high-impact, highly technical role suited for someone who thrives in complex distributed systems environments and cares deeply about infrastructure as a product. Responsibilities Design, implement, and maintain Infrastructure as Code (IaC) best practices to enable repeatable, auditable, and scalable cluster provisioning. Enhance and harden CI/CD deployment pipelines to ensure robust, secure, and low-latency model service delivery across production environments. Own and evolve stable training infrastructure operating at the scale of 10,000+ GPUs, including job scheduling, fault tolerance, and network fabric optimization. Partner closely with ML researchers and engineers to understand compute bottlenecks and translate them into infrastructure improvements. Monitor system health, define SLOs, and lead incident response for critical training and

P-1360 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As a software engineer with a backend focus, you will work with your team to build infrastructure for the Databricks platform at scale. The impact you'll have: Our backend teams cover a diverse range of domains, from core compute fabric resource management to service platforms and machine learning infrastructure. For example, you might work on challenges such as: Supporting Databricks' growth by building foundational infrastructure platforms that enable seamless operation across numerous geographic regions and cloud providers. Implementing cloud-agnostic infrastructure abstractions to help Databricks engineers more efficiently manage and operate their services. Develop tools and processes that drive engineering efficiency at Databricks. We enhance the developer experience for Databricks engineers across various areas, including programming languages, linters, static analysis, IDEs, remote development environments, automated release pipelines, and test automation frameworks. Our current focus is on optimizing the Rust development experience across the organization. What we look for: 2+ years of professional software development experience, or alternatively a PhD degree. Bachelor’s degree or higher in Computer Science, related field, or equivalent experience. Proficiency in one or more backend languages such as Java, Scal

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Workforce Identity Cloud Okta Workforce Identity Cloud (WIC) provides easy, secure access for your workforce so you can focus on other strategic priorities, such as reducing costs and doing more for your customers. If you like to be challenged and have a passion for solving large-scale automation, global traffic routing, and resilient cloud infrastructure problems, we would love to hear from you. The ideal candidate is someone who exemplifies the ethics of, “If you have to do something more than once, automate it” and who can rapidly self-educate on new network topologies, multi-cloud ecosystems, and agentic engineering models. Position Overview: The Staff Software Engineer - Infrastructure will play a foundational role in architecting, evolving, and securing Okta's global core network fabric and multi-cloud platform layers. This position focuses on building highly resilient, edge management in AWS and GCP cloud, executing enterprise-wide cloud migrations (AWS to GCP), enforcing absolute Zero-Trust primitives (mTLS / TLS 1.3), and integrating cutting-edge AI automation layers (Agentic SRE) into our day-to-day operations. As a Staff Engineer on this team, you will act as a key technical anchor in India, working closely with global counterparts to maintain Okta's high-availability SLAs while protecting the platform against active global DDoS attacks. Key Responsibilities: Global Ingress & Routerless Evolution (CFSaaS): Design and engineer Next-Gen traffic

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 We're looking for a Staff Data Engineer to own the architecture and technical vision of our data platform. This is a high-leverage, high-autonomy role where you'll set the technical bar for the team, drive cross-functional alignment on data infrastructure strategy, and solve our hardest engineering problems. You'll operate across AWS serverless technologies, Snowflake, dbt, and Terraform, but your impact goes well beyond any single tool: you'll shape how we think about reliability, scalability, cost, and developer experience at the platform level. This role is for someone who doesn't just build great systems, but makes the engineers around them better. The Role: Own the technical architecture of ClickUp's data platform, making design decisions that balance scalability, cost, reliability, and velocity. Define and drive the technical roadmap for data infrastructure in partnership with leadership. Design systems at scale : build frameworks, abstractions, and patterns that other engineers use daily. Lead complex, cross-team technical initiatives spanning data engineering, analytics engineering, data science, and data analytics. Drive cost optimization across cloud infrastructure and compute, turning efficiency into a competitive advantage. Build and evolve our data pipelines using AWS serverless (Lambda, Fargate, Step Functions, Kinesis, S3, DynamoDB, Aurora), Snowflake, and dbt. Establish and champion engineering standards : observability, testing, CI/CD, code review, and documentation practices. Design and maintain infrastructure for AI/ML workloads , including LLM frameworks, feature pipelines, training

Who We Are Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale, empowering a safer, richer, and more connected future. About the Role The Mapping team in Nuro takes a machine learning-first path to unblock geographic capability with lower costs. This team plays a crucial role in the advancement of autonomous driving systems by creating and improving different components in the full lifecycle of ML models for multiple teams in this organization. We are searching for an engineer with experience building reliable and scalable machine learning infrastructure and a strong desire to contribute to the future of robot navigation for logistics and transportation. About the Work Mainly focus on building and improving HD map generation and release pipelines. Develop scalable workflows to manage first party and third party map data. Develop and manage APIs for internal users to access data. Improve and refactor existing workflows and toolings to boost efficiency. Engage with other mapping teams to help identify issues and establish long-term relationships that include knowledge sharing. About You BS in Computer Science, Robotics or another quantitative area. You have experience in one or more of the following areas: large-scale distributed systems; data storage and processing systems; advanced algorithms using C++ and Python; multithreading; and software performance tuning and optimization. Ability to efficiently develop, debug, and support new technologies in a changing environment. Str

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Okta authenticates, authorizes, and provisions millions of users a day. Internally, TDI Infrastructure Engineering runs the platforms that our own engineering and business teams build on — hosted on AWS, increasingly Kubernetes-native, and expanding fast to support AI-driven internal workflows. We're looking for a Staff SRE to help us evolve Site Reliability Engineering from a traditional operations model into a true Platform as a Service (PaaS) organization. As a Staff Site Reliability Engineer on our Dublin/EMEA team, you will be the senior-most technical voice on the ground — setting architectural direction for our Kubernetes platform, driving the hardest reliability and scaling problems to resolution, and partnering with Staff/Principal engineers on our US and India teams to keep our global platform strategy coherent. You'll report to the Senior Manager, Site Reliability Engineering, and work alongside a Senior SRE and the rest of the Dublin team. What you'll be doing Owning the architecture and evolution of our Kubernetes platform for the Dublin/EMEA team — cluster strategy, multi-tenancy, networking, and security posture — in close coordination with counterparts in the US and India Leading the technical design and rollout of self-service platform capabilities, golden paths, and self-healing patterns that let internal teams ship and operate workflows without deep platform expertise Driving the platform's readiness to host AI-driven internal workflows r

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Okta authenticates, authorizes, and provisions millions of users a day. Internally, TDI Infrastructure Engineering runs the platforms that our own engineering and business teams build on — hosted on AWS, increasingly Kubernetes-native, and expanding fast to support AI-driven internal workflows. We're looking for a Senior SRE to help us evolve Site Reliability Engineering from a traditional operations model into a true Platform as a Service (PaaS) organization. As a Senior Site Reliability Engineer on our Dublin/EMEA team, you will build and operate the Kubernetes-based platform that hosts internal workflows across the business, with a growing focus on hosting AI-driven workflows reliably in production. You'll report to the Senior Manager, Site Reliability Engineering, and work closely with a Staff SRE and the rest of the Dublin team, as well as SRE peers in the US and India. What you'll be doing Building, operating, and improving our Kubernetes platform — cluster management, networking, security posture, and day-2 operations Developing self-service capabilities, golden paths, and automation that let internal teams onboard and operate workflows with less platform expertise required Supporting the platform's readiness to host AI-driven internal workflows reliably at scale Troubleshooting and resolving production issues, including participating in a follow-the-sun on-call rotation shared with SRE peers in the US and India, and driving postmortems for in

P-1344 As a software engineer with a backend focus, you will work with your team to build infrastructure for the Databricks platform at scale. The impact you'll have: Our backend teams cover a diverse range of domains, from core compute fabric resource management to service platforms and machine learning infrastructure. For example, you might work on challenges such as: Supporting Databricks' growth by building foundational infrastructure platforms that enable seamless operation across numerous geographic regions and cloud providers. Implementing cloud-agnostic infrastructure abstractions to help Databricks engineers more efficiently manage and operate their services. Develop tools and processes that drive engineering efficiency at Databricks. We enhance the developer experience for Databricks engineers across various areas, including programming languages, linters, static analysis, IDEs, remote development environments, automated release pipelines, and test automation frameworks. Our current focus is on optimizing the Rust development experience across the organization. What we look for: 8+ years of professional software development experience. Bachelor’s degree or higher in Computer Science, a related field, or equivalent experience. Proficiency in one or more backend languages such as Java, Scala, or Go. Hands-on experience in developing and operating large-scale, critical distributed backend systems. Demonstrated leadership throughout all project phases, from inception and design to implementation and operations, with a strong ability to drive architectural decisions and guide teams through complex challenges. Experience mentoring engineers, influencing best practices, and fostering a collaborative engineering environment. Self-driven and passionate with a strong focus on delivering impact through team collaboration. Strong written and verbal communication skills to drive alignment across teams, and contribute to both technical documentation and strategic decisi

P-150 At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform). Below are some example teams you can join: Data Science and Machine Learning Infrastructure: Build services and infrastructure at the intersection of machine learning and distributed systems. Our te

P-150 At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark™, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform). Below are some example teams you can join: Data Science and Machine Learning Infrastructure: Build services and infrastructure at the intersection of machine learning and distributed systems. Our

P-78 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As a software engineer with a backend focus, you will work with your team to build infrastructure and products for the Databricks platform at scale. The impact you'll have: Our backend teams span many domains, from our core compute fabric resource management infrastructure, to service platforms, to machine learning infrastructure. For instance, you might work on challenges such as: Resource management infrastructure powering the big data and machine learning workloads on the Databricks platform in a scalable, secure, and cloud-agnostic way Develop reliable, scalable services and client libraries that work with massive amounts of data on the cloud, across geographic regions and Cloud providers Build tools to allow Databricks engineers to operate their services across different clouds and environments Build services, products and infrastructure at the intersection of machine learning and distributed systems. What we look for: BS (or higher) in Computer Science, or a related field 5+ years of production level experience in one of: Java, Scala, C++, or similar language. Experience developing large-scale distributed systems. Experience working on a SaaS platform or with Service-Oriented Architectures. Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes. Experience with security and systems that handle sen