Software Engineer Data Infrastructure Jobs

P-1299 Databricks is radically simplifying the entire data lifecycle, from ingestion to generative AI and everything in-between. We’re doing it cross-cloud with a unified platform, currently serving over 10k customers, processing exabytes of data/day on 15+ million VMs, and growing exponentially . To make it happen we’re building multi-cloud systems at every corner of the data ecosystem, from query engines, vector databases, training pipelines, and storage systems, down to the infrastructure that allows them to scale like auto-sharders, caches, and load balancers, just to name a few. We also build and support the tooling, languages, and stacks that bring it together. Basically, we do it all. The space we work in and the problems we solve are massive, complex, and very deep (our published work on Lakehouse , Delta lake , and Photon are a testament to that). We’re looking for practitioners who are eager to work with the best in industry to push the boundaries of what’s possible for our customers. If you’re truth seeking, data driven, and love to operate from first principles (head fake: our core values ), then Databricks is the place for you. As a part of the Database Engine team, there are opportunities to design and implement in many areas that leapfrog existing state-of-the-art systems: Query compilation & optimization Distributed query execution and scheduling Vectorized engine execution Data security Resource Management Transaction coordination Efficient storage structures (encoding, indexes) Automatic physical data optimization What we look for: PhD in databases or systems A passion for database systems, storage systems, distributed systems, language design, and/or performance optimization Motivated by delivering customer value and impact Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for

P-1299 Databricks is radically simplifying the entire data lifecycle, from ingestion to generative AI and everything in-between. We’re doing it cross-cloud with a unified platform, currently serving over 10k customers, processing exabytes of data/day on 15+ million VMs, and growing exponentially . To make it happen we’re building multi-cloud systems at every corner of the data ecosystem, from query engines, vector databases, training pipelines, and storage systems, down to the infrastructure that allows them to scale like auto-sharders, caches, and load balancers, just to name a few. We also build and support the tooling, languages, and stacks that bring it together. Basically, we do it all. The space we work in and the problems we solve are massive, complex, and very deep (our published work on Lakehouse , Delta lake , and Photon are a testament to that). We’re looking for practitioners who are eager to work with the best in industry to push the boundaries of what’s possible for our customers. If you’re truth seeking, data driven, and love to operate from first principles (head fake: our core values ), then Databricks is the place for you. As a part of the Database Engine team, there are opportunities to design and implement in many areas that leapfrog existing state-of-the-art systems: Query compilation & optimization Distributed query execution and scheduling Vectorized engine execution Data security Resource Management Transaction coordination Efficient storage structures (encoding, indexes) Automatic physical data optimization What we look for: PhD in databases or systems A passion for database systems, storage systems, distributed systems, language design, and/or performance optimization Motivated by delivering customer value and impact Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for

About the Role: As a Staff Software Engineer on the ML Infrastructure team, you will collaborate closely with the Machine Learning and Product teams to build world-class machine learning inference platforms. These platforms power essential services like personalized recommendations, search, and content understanding across Tubi. A core responsibility of this team is developing and maintaining low-latency ML model serving systems that support Deep Learning, LLM, and Search models. This involves building self-service infrastructure and critical components such as the inference engine, feature store, vector store, and experimentation engine. You will improve the way we deploy and operate our services and even contribute to open-source projects. This role grants the architectural freedom to explore new frameworks, lead critical cross-functional projects, and transform the capabilities of our ML and Product teams. Responsibilities: Design and build scalable, high throughput, and low latency distributed systems using Scala Build reusable components and services that serve various ML applications like Personalization, Search, Ads and Exploration Partner closely with ML engineers to understand their challenges and limitations and develop scalable solutions to address them. Proactively recommend solutions to keep our ML Inference stack state of the art. Take a data driven approach to identifying & optimizing latency, cost, and efficiency of our infra. Lead large scale cross functional refactorings if necessary Mentor other engineers on the team on system design, effective incident management, interviewing, leveraging LLMs for work, etc. Collaborate with ML, Product, and cross functional engineering teams to define the long term vision and architecture for ML Infrastructure at Tubi. Your Background: Experience designing and building scalable, distributed systems in any modern backend language (e.g., Scala, Java, Python, Go, C++); experience with Scala or JVM b

Software Engineer Argentina; Uruguay Software Engineer - Robotics & Autonomous Systems Scale's Robotics business unit is dedicated to solving the data bottleneck in Physical AI across Robotics, Autonomous Vehicles, and Computer Vision. In this role, you'll be a key contributor building production systems for robotics data collection, model training pipelines, and evaluation infrastructure. You'll have the opportunity to own critical parts of our robotics platform, work directly with cutting-edge robotics and AV customers, and shape the future of embodied AI systems. You Will: Own and architect large-scale data processing pipelines for robotics and autonomous vehicle datasets Build ML training and fine-tuning pipelines using Scale's robotics data Work across backend (Python, Node.js , C++), and frontend (React, TypeScript) stacks to build end-to-end solutions Develop tools and real-time systems for robotics data collection, teleoperation, model evaluation, data curation, and data annotation Interact directly with robotics and AV stakeholders to understand their technical needs and drive product development Design comprehensive monitoring and evaluation frameworks for robotics models and data quality Solving complex, late-stage industry challenges in concurrent and real-time robotic systems, with strict attention to timing constraints and data integrity. This often involves deep investigation, reviewing academic papers, and direct collaboration with robotics vendors Collaborate with ML engineers and researchers to bring robotics research into production Deliver features at high velocity while maintaining system reliability and performance Ideally, You Have: At least 6 years of high-proficiency software engineering experience, with a strong background in complex systems and the ability to independently research, analyze, and unblock hard technical problems. Strong programming skills in Python and TypeScript/Node.js for production systems Experience with React and m

The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the Role The Software Engineer, Operating Systems & Orchestration will focus on building systems to manage hardware, configurations, vendors, and the people interacting with our infrastructure. You will design and develop solutions that integrate individual nodes and servers into unified clusters, directly contributing to advancing AI research by streamlining the overall research user experience. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design and build systems to manage both cloud and bare-metal fleets at scale. Develop tools that integrate low-level hardware metrics with high-level job scheduling and cluster management algorithms. Leverage LLMs to coordinate vendor operations and optimize infrastructure workflows. Automate infrastructure processes, reducing repetitive toil and improving system reliability. Collaborate with hardware, infrastructure, and research teams to ensure seamless integration across the stack. Continuously improve tools, automation, processes, and documentation to enhance operational efficiency. You might thrive in this role if you: Have strong software engineering skills with experience in large-scale infrastructure environments. Possess broad knowledge of cluster-level systems (e.g., Kubernetes, CI/CD pipelines, Terraform, cloud providers). Have deep expertise in server-level systems (e.g., systems, containerization, Chef,

About Us Herald is transforming how commercial insurance gets sold. We combine modern API infrastructure with industry-specific AI that can read emails, extract data, generate quotes, and guide brokers through submission workflows end-to-end. The result: faster placement, cleaner operations, and meaningful revenue growth. The market is huge, the need is obvious, and the product we’re building doesn’t exist yet. If you want to help shape the operating system for modern insurance, we’d love to work with you. We’re a team of insurtech veterans with experience at At-Bay , Kin , and Insurify . We’ve raised our Series A funding from top-tier VCs ( Lightspeed , Brewer Lane, Afore , Underscore ) along with a panel of insurtech founders ( At-Bay , Marble ), insurance executives ( CRC ), and early employees of other successful API infrastructure companies ( Plaid , Alloy ). The role Herald is building Babbix, an AI-native platform that commercial insurance brokers use to create submissions and get quotes directly from their inbox. It orchestrates broker workflows end-to-end by combining classification pipelines, data extraction models, and a broker-facing web interface. Delivering high-quality product experiences and shipping new AI-driven capabilities are core to our success. As a Senior Software Engineer (Full Stack) on the Babbix product, you’ll drive major product initiatives from inception to delivery. You’ll work directly with brokers and internal stakeholders to shape ideas, turn them into designs, and build them into production-ready features. You’ll work across the stack, from frontend UI to backend APIs to model orchestration, to deliver effortless workflows and make our AI output transparent, accurate, and trustworthy Why This Role Matters Commercial insurance is one of the last major industries still powered by email. Every submission, quote, and policy must be manually processed by brokers, slowing them down and costing them deals. By bu

The Prediction & Behavior ML team is responsible for developing machine learning (ML) algorithms that learn and predict behaviors from data, applying them both on-vehicle to influence driving behavior and off-vehicle to provide ML capabilities to simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team collaborates closely with the Planner team to advance overall vehicle behavior. We also work closely with our Perception, Simulation, and Systems Engineering teams to accelerate our ability to validate our driving performance. As a Learned Trajectory Machine Learning Engineer you will be responsible for developing deep learned models that produce trajectories for our vehicles to drive. Given the tight integration of behavior prediction and motion planning, you will closely collaborate with the Planner and Perception teams in the advancement of our overall vehicle behavior. In this role, you will: You will develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for our autonomous vehicle. You will also work on techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort etc. You will leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field You will develop metrics and tools to analyze errors and understand improvements of our systems You will collaborate with engineers on Perception, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments Qualifications BS, MS, or PhD degree in computer science or related field Experience with training and deploying transformer-based model architectures and reinforcement learning Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines Fluency in C++

About the Team The Frontier Systems team at OpenAI builds, launches, and supports the largest supercomputers in the world that OpenAI uses for its most cutting edge model training. We take data center designs, turn them into real, working systems and build any software needed for running large-scale frontier model trainings. Our mission is to bring up, stabilize and keep these hyperscale supercomputers reliable and efficient during the training of the frontier models. About the Role As a Software Engineer on the Frontier Systems team focused on power management, you will work on critical infrastructure to support cutting-edge research. With large-scale supercomputers consuming substantial amounts of power, managing this efficiently is key to maximizing computational capacity. This role is critical to ensuring that our cutting-edge research supercomputing infrastructure runs smoothly, while maintaining reliability and grid-level power stability. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Develop and implement system-level and software-level solutions to optimize power usage in large-scale supercomputers, ensuring efficient and reliable operations. Build automation to monitor power consumption patterns during training workloads and design algorithms to stabilize these fluctuations, preventing issues with grid reliability. Work with researchers and engineers to design tools for real-time monitoring, detection, and remediation of power-related hardware and system faults. Collaborate cross-functionally to translate complex electrical system requirements into code, while driving continuous improvements in power man

Description: Graviton Research Capital LLP, Gurgaon is looking to hire Software Engineers for our Core Technology team which has some of the best programmers in India working on cutting edge technologies to build a super fast and robust trading infrastructure handling millions of dollars worth of trading transactions every day. As a Senior Software Engineer with Graviton your responsibilities will include: Designing and implementing a high-frequency automated trading system, that trades on multiple exchanges Building live reporting and administration tools for the trading system Performance optimization and improving the overall latency of systems, through algorithm research and using cutting edge tools and techniques End-to-end ownership of modules, including designing, development, deployment and support Growing the team through involvement in the regular hiring process and occasional campus recruitments Requirements : The ideal requirements for our candidates are: A degree in Computer Science 3-5 yrs Experience with C/C++ and object-oriented programming Experience in HFT industry Expertise in algorithms and data structures Excellent problem solving skills Strong communication skills A working knowledge of Linux systems Any of the following is a plus: A good understanding of TCP/IP and Ethernet Knowledge of any other programming language e.g. Java, Scala, Python, bash, Lisp, etc. Familiarity with parallel programming models and parallel algorithms Experience with big data environments e.g. Hadoop, Spark etc. Benefits: Our open and collaborative work culture gives you the freedom to innovate and experiment. Our cubicle free offices, non-hierarchical work culture and insistence to hire the very best creates a melting pot for great ideas and technological innovations. Everyone on the team is approachable, there is nothing better than working with friends! Our perks have you covered. Competitive compensation Annual international team outing Fully covered commuti

About the Role DoorDash is building the world's most reliable on-demand, logistics engine for delivery. We are continuing to grow rapidly and expanding our Engineering offices globally! We’re looking for Senior iOS Engineers who want to work on building an app that’s used by millions of people and critical to local entrepreneurs building their online presence. We’ve seen significant growth in our codebase and number of developers and we’d love for you to bring a piece of your culture and experiences into ours so that we can continue to improve our processes and architecture. Whether you’re an engineer interested in scaling our mobile infrastructure or building awesome product features, we’d love to talk to you! This role is hybrid with some in-office time expected and will report to an Engineering Manager. You're excited about this opportunity because you will… Work within our engineering teams to build exciting features Improve our code base through continuous refactoring Solve challenging real-time data transfer and synchronization problems Extend and implement our APIs Implement unit tests Keep up-to-date with the industry standards of iOS development We're excited about you because you have… 5+ years of industry experience B.S., M.S., or PhD. in Computer Science or equivalent Expert at Swift, and iOS SDK Familiarity with networking, storage, and Cocoapods Systems and OOP knowledge Experience building, launching, and iterating on mobile apps Compensation The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future. In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with

JOB TITLE: Senior Security Software Engineer (Backend Focus) CLASSIFICATION: Exempt Approved by: Jitendra Patil EXPERIENCE: 5–10 Years Approved Date: REPORTS TO: Shivendra Ashish Revised Dates: POSITIONS SUPERVISED: Core Responsibilities: Security Microservices: Architect and build centralized security services (e.g., Authentication/Authorization, Secrets Management, PKI) using high-performance languages. Secure Libraries: Develop standard SDKs/Libraries that abstract complex security logic (Encryption, Input Validation) for other engineering teams. Automated Remediation: Build bots or "Self-Healing" code that automatically detects and fixes infrastructure misconfigurations or code vulnerabilities. AI Security ( AISec ): Build guardrails and "Firewalls" for internal LLM applications to prevent data leakage and prompt injection. Must-Have Skills: Backend Engineering: Expert in Golang or Python. Ability to write production-grade, testable, and concurrent code. System Design: Strong understanding of distributed systems, microservices architecture, and API design. Application Security: Deep knowledge of OWASP standards, Cryptography fundamentals, and Auth protocols (OAuth2/SAML/OIDC). DevSecOps : Experience integrating security checks into CI/CD pipelines (Linters, SAST/DAST wrappers). Preferred / Nice to Have: Experience with Policy-as-Code frameworks (e.g., OPA). Knowledge of Service Mesh security patterns. Experience contributing to open-source security projects. Ability to embrace Clearwater's CLEAR core values (Commitment to Client Success, Lead with Accountability, Integrity & Collaboration, Excellence in All That We Do, Advance Colleague Success, Respect & Transparency) and culture. Disclaimer: The above statements are intended to describe the general natu

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 Streaming Platform team at Sentry is building the next generation of infrastructure that powers our ingestion pipelines and real-time data processing systems. Our platform ingests, processes, and distributes hundreds of thousands of events per second with low latency and high reliability. We are creating a system that makes it easy for Sentry engineers to deploy and run Streaming Applications at scale by simplifying the complexity of Kafka, scaling consumers automatically, and managing state so product teams can focus on building great experiences for developers. As part of this team, you will work on challenges at the intersection of distributed systems, real-time data processing, and developer experience. You will help us create a self-service streaming platform that improves stability, accelerates time to production, and reduces operational overhead. This role is based in Toronto, with three days per week in the office to work closely with engineering teams. In this role you will Design, build, and operate components of our Streaming Platform, including Kafka, the streaming runtime, high-level APIs, and developer-facing abstractions. Implement resilient, high-throughput stream processing systems that handle unbounded datasets with strong correctness guarantees (delivery, checkpointing, watermarking, and more). Build scalable automation and control plane for Kafka fleet management and improve efficiency. Partner with product engineers to ensure our abstractions enable fast, reliable, and consistent ingestion pipelines. Improve observability, monitoring, and failover for mission-critical real-time systems

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 Streaming Platform team at Sentry is building the next generation of infrastructure that powers our ingestion pipelines and real-time data processing systems. Our platform ingests, processes, and distributes hundreds of thousands of events per second with low latency and high reliability. We are creating a system that makes it easy for Sentry engineers to deploy and run Streaming Applications at scale by simplifying the complexity of Kafka, scaling consumers automatically, and managing state so product teams can focus on building great experiences for developers. As part of this team, you will work on challenges at the intersection of distributed systems, real-time data processing, and developer experience. You will help us create a self-service streaming platform that improves stability, accelerates time to production, and reduces operational overhead. This role is based in San Francisco, with three days per week in the office to work closely with engineering teams. In this role you will Design, build, and operate components of our Streaming Platform, including Kafka, the streaming runtime, high-level APIs, and developer-facing abstractions. Implement resilient, high-throughput stream processing systems that handle unbounded datasets with strong correctness guarantees (delivery, checkpointing, watermarking, and more). Build scalable automation and control plane for Kafka fleet management and improve efficiency. Partner with product engineers to ensure our abstractions enable fast, reliable, and consistent ingestion pipelines. Improve observability, monitoring, and failover for mission-critical real-time s

A Career with Point72's Technology Team As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications. As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business. WHAT YOU’LL DO Modernize the profit-and-loss reporting platform that helps finance, management, and investment teams understand firm performance with greater accuracy and speed Design scalable data pipelines and reconciliation workflows that improve the reliability, transparency, and timeliness of critical finance data Build analytical applications and reporting capabilities that turn complex valuation and performance data into clear, actionable insights Develop validation and adjustment tools that strengthen controls, reduce manual effort, and support accurate reporting across business processes Partner with controllers, valuation specialists, and Technology colleagues to translate business needs into robust, maintainable software Own features through design, development, testing, deployment, and ongoing support in a collaborative engineering environment Analyze data flows and calculation logic to anticipate reporting needs, identify gaps, and improve end-to-end process