Performance And Systems Engineer Jobs

Join the Atlas Search Query team to design and develop the next generation of Search query architecture, optimization, and execution. Atlas Search is a growing cloud service that allows users to execute complex search and vector search queries using the MongoDB Query Language. Our users can focus on relevance and data retrieval instead of the machinery needed to search data at scale. Our team is building a cloud-based distributed system responsible for the core components of search including data ingestion, performance, query language, query execution, for both relevance-based search and vector search. Our product is being adopted quickly and there are many interesting projects. This is a technical role where you will be responsible for the success of complex Search Query feature development. We are looking to speak to candidates who are based in San Francisco, CA for our hybrid working model. What You’ll Do Lead complex projects across the MongoDB ecosystem, for instance, development of a new Search aggregation framework within the MongoDB aggregation framework. Set project level strategy, architect features, and lead projects to successful execution Identify, design, and implement features enhancing our query language, performance, and operability Perform code reviews with peers and make recommendations on how to improve our software development processes Influence and grow team members through active mentoring and leading by example What We Look For 5+ years experience in data management/search systems, ideally with a strong query processing and optimization background Experienced in the development and maintenance of stateful distributed systems Eager to shape the technological direction of a complex system and have the ability to lead initiatives through collaboration with others Experienced in debugging and profiling multithreaded applications written in Java and Rust Bonus: experience with designing high-volume query engines, such as a datab

About the Role: Tubi is seeking a highly skilled and experienced QA Automation Engineer to lead quality assurance initiatives for our cutting-edge streaming and AI-driven product features. This pivotal role involves ensuring exceptional end-to-end user experiences, robust streaming playback, and the accuracy and integrity of our AI/ML features across web, mobile, and OTT platforms. We're looking for a candidate with a strong background in streaming QA and deep technical knowledge of media workflows. You'll be instrumental in collaborating with engineering, product, and data science teams to define comprehensive QA strategies that guarantee both functional excellence and data-level quality This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: Design and lead test strategies for streaming workflows, playback systems, and AI-powered features. Test across platforms (web, mobile, and connected TV) to ensure functional parity and playback stability. Validate streaming performance—including ABR logic, encoding pipelines, and DRM integrations—under diverse real-world conditions. Debug with precision using tools like Charles Proxy, Chrome DevTools, ADB, and Xcode. Collaborate with data and ML teams to validate AI model updates, recommendations, and personalization accuracy. Leverage AI-assisted QA tools to enhance regression coverage, UI validation, and anomaly detection. Contribute to automation and CI/CD frameworks, driving faster, more reliable releases. Oversee QA deliverables for multiple concurrent releases and ensure seamless sign-off for production launches. Monitor live environments for playback or recommendation anomalies post-release and escalate issues promptly. Continuously improve QA processes, metrics, and reporting for streaming and AI validation. Your Background: Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent hands-on experi

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Pure Storage is seeking a full-time Principal Hardware Engineer working as part of our Hardware Development Team. In this position, you'll be working to define the technical direction of our next-generation hardware platforms. You’ll work closely with Architects, Engineering, Operations, OEM/JDM Partners and Support & Escalation Teams. You'll be responsible for the future of Pure’s high performance storage systems, acting as the primary subject matter expert for system hardware across executive, product, and client interactions.. WHAT YOU'LL DO Define system-level hardware architecture for FlashBlade, including compute, memory, interconnect, storage, power, and thermal design. Translate product requirements and customer needs into clear technical specifications and design trade-offs. Evaluate and select key components, technologies, and vendors, and lead make-vs-buy decisions. Drive architecture reviews and design reviews, and ensure designs meet performance, reliability, and compliance targets. Partner with firmware and software teams to define hardware/software interfaces and optimize the full stack Track emerging technologies and industry standards, and shape the long-term hardware roadmap. Work with manufacturing and supply chain on DFM/DFT, yield, cost reduction, and component risk. Strong understanding of X86 architecture and proven design track record Solid understanding of Major Bus

MongoDB Technical Services Engineers use their exceptional problem solving and customer service skills, along with their deep technical experience, to advise customers and to solve their complex MongoDB problems. Technical Service Engineers are experts in the entire MongoDB ecosystem - database server, drivers, cloud and infrastructure. This also includes services such as Atlas (database as a service), or Cloud Manager (which helps customers with automation, backup and monitoring of their MongoDB systems). Our engineers combine their MongoDB expertise with passion, initiative, teamwork and a great sense of humor to help our customers to be successful with MongoDB. We are looking to speak to candidates who are interested in working out of our Dublin office under our in-office working model Monday to Friday for the first 3-6 months depending on ramping speed. Once considered ramped, they will transition to a permanent (Tuesday to Saturday) 9am-6pm work week (with 3 in-office days) to provide weekend coverage alongside other peers. Saturdays and Sundays are considered fully online workdays and not an on-call shift. Due to the 24/7 nature of our support organization, certain events throughout the year will require volunteering for coverage outside one’s normal work days or work hours (i.e. regional offsites, regional holidays, etc). These are typically announced weeks in advance with a sign-up system that considers equitability. Cool things you’ll do You'll be working alongside our largest customers, solving their complex challenges - resolving questions on architecture, performance, recovery, security, and everything in between. You'll be an expert resource on best practices in running MongoDB at scale, whatever that scale may be. You'll be an advocate for customers' needs - interfacing with our product management and development teams on their behalf. And you'll contribute to internal projects, including software development of support tools for performance, ben

P-1385 We are hiring a Senior Staff Software Engineer for Databricks' Engineering team reporting to an Engineering Leader. You will be part of the Databricks engineering organization, working with teams that develop Databricks products and features for thousands of enterprises worldwide. Key Characteristics As an executive engineering individual contributor at Databricks, you will have full ownership of the product or infrastructure direction in a major area, driving it from initial development to scalable solutions with clear business impact. You will serve as a force multiplier by elevating stability, reliability, and organizational processes, while bringing deep expertise in large-scale distributed systems. You will mentor senior engineers, contribute to recruiting, and lead high-impact company projects, often tackling complex problems beyond their comfort zone. Job Description 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. Our engineering teams build highly technical products that fulfill real, important needs in the world. 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. The Impact You Will Have Solve real business needs at large scale by applying your software engineering. Deliver a highly scalable, available, and fault-tolerant engine processing hundreds of TB of data daily across thousands of customers Low level systems debugging, performance measurement & optimizat

This role in the Offline Driving Intelligence team is responsible for developing/learning behavior models for road users such as cars, bicycles, and pedestrians. These agents populate Zoox's simulations and must be indistinguishable from real road users, yet fully controllable: promptable into the rare, adversarial, safety-critical behaviors we need to test against. This means the team’s models directly impact how fast Zoox can train, validate and ship its driving stack. Our team collaborates closely with Planner, Simulation and Validation teams to develop and validate our driving performance. As an ML Agents Machine Learning Engineer, you will work on the bleeding edge of the industry, developing novel machine learning pipelines and models to predict the behavior of other agents in the world and planning the best course of action for the ego vehicle. In this role, you will... Develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for human-like driving agents. Work on novel techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort and realism. Build generative behavior models (e.g. autoregressive, diffusion) that are conditionable on scenario intent — "cut off the ego vehicle," "jaywalk here" — for targeted stress-testing. Leverage our compute, infrastructure and large corpus of data to push boundaries of the field. Develop metrics and tools to analyze errors and understand improvements of our systems. Collaborate with engineers on Perception, Planning, Simulation, and Validation to solve the overall Autonomous Driving problem. Qualifications PhD degree in computer science or related field and 4+ years of relevant professional experience or master's degree and 7+ years of relevant professional experience

About the Team The Software Engineering Firmware team builds reliable, high-performance systems on custom hardware. We work closely with hardware engineers to design, optimize, and ship software that bridges cutting-edge devices and real-world constraints like memory, power, and latency. Our work spans early prototyping through product launch, ensuring that our embedded platforms are robust, efficient, and production-ready. About the Role As a Firmware Engineer , you will design, implement, and debug software for embedded devices. You’ll own low-level bring-up, write production C/C++ code, and partner closely with hardware teams to deliver reliable, high-performance systems. We’re looking for engineers with deep embedded expertise, strong debugging skills, and a passion for building systems that perform under real-world conditions. This role is based in San Francisco, CA . We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, implement, and debug software for embedded devices. Contribute to defining software requirements, interfaces, and test plans. Bring up and debug new boards. Analyze performance, memory, and power profiles and implement optimizations. Investigate field issues, perform root-cause analysis, and deliver robust fixes. Foster good software engineering practices. You might thrive in this role if you: Have deep experience shipping embedded systems (around 10+ years). Are proficient in C and C++. Are familiar with embedded toolchains, operating systems, and debugging tools. Have experience with both rapid prototyping and scalable product development. (Nice to have) Have experience with Zephyr RTOS. (Nice to have) Have worked with networking/wireless stacks (BLE, Wi-Fi). (Nice to have) Have experience with Linux kernel development. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefit

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. Auth0 provides an unparalleled authentication experience for hundreds of millions of users worldwide. Our commitment to reliability is a key foundation of our product and our dedication to exceeding customer availability expectations is a core engineering focus. As a Senior Site Reliability Engineer, you'll join our SRE team based in Europe to ensure our production systems are not only operational but also resilient, scalable, and ready for exponential growth. This isn't just about keeping the lights on; it's about directly contributing to the platform's core resiliency and robustness. You'll be a hands-on builder, crafting solutions that make our system more reliable by design. What you’ll do: Design and build custom software in Go to enhance the platform's reliability, resiliency, and redundancy. Partner with engineering teams to embed reliability principles, improving the availability, performance, and observability of our services. Use your deep understanding of infrastructure and observability principles to identify opportunities for improvement within the product and implement solutions. Contribute to our follow-the-sun on-call rotation, providing rapid, effective response to critical incidents and using your expertise to troubleshoot, mitigate or accurately escalate production issues. Because our team is globally distributed, your on-call shifts will only occur during your standard local working hours. Develop and refine our SRE tooling and proc

The goal of a Machine Learning Engineer at Scale is to leverage techniques in the fields of generative AI, computer vision, reinforcement learning, and agentic AI to improve Scale's products and customer experience in production environments. Our machine learning engineers take advantage of robust internal infrastructure and unique access to massive datasets to deliver improvements to our customers. Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge . Our work spans multiple modalities, with a strong focus on both large language models and computer vision. On the LLM side, we are developing agentic systems that help solve complex operational and planning challenges for government partners. This includes building agent frameworks that integrate with custom retrieval pipelines and production APIs, as well as evaluation tools to benchmark and refine agent behavior. We're also advancing research in areas like reinforcement learning for agentic LLMs, with successful deployment into real-world operational environments. On the computer vision front, we're training advanced models to increase labeling throughput and automate perception tasks. Our efforts include building large-scale fine-tuning pipelines, training models across multiple modalities, and developing generalizable vision foundation models to support a wide range of defense applications. You will: Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines Work with massive datasets to develop bo

P-1416 Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse ( CIDR 2021 paper ), open platforms that unify data warehousing and advanced analytics. This new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. To achieve this vision, Databricks is building the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance. Yet we will retain the expressiveness and robustness of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science. You will be part of this multi-year journey. As part of this team, you will design these next-generation systems that leapfrog state-of-the-art within the following areas: Query compilation and optimization Distributed query execution and scheduling Vectorized execution engine Data security Resource management Transaction coordination Efficient storage structures (encodings, indexes) Automatic physical data optimization The responsibilities you will have: Drive requirements clarity and design decisions for ambiguous problems Produce technical design documents and project plans Develop new features Mentor more junior engineers Test and rollout to production, monitoring. What we look for: A passion for database systems, storage systems, distributed systems, language design, or performance optimization Are comfortable working towards a multi-year vision with incremental deliverables Be customer-oriented and focused on having an impact 7+ years of experience working in a related system Optional: PhD in databases or distributed systems About Dat

P-1415 Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse ( CIDR 2021 paper ), open platforms that unify data warehousing and advanced analytics. This new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. To achieve this vision, Databricks is building the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance. Yet we will retain the expressiveness and robustness of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science. You will be part of this multi-year journey. As part of this team, you will design these next-generation systems that leapfrog state-of-the-art within the following areas: Query compilation and optimization Distributed query execution and scheduling Vectorized execution engine Data security Resource management Transaction coordination Efficient storage structures (encodings, indexes) Automatic physical data optimization The responsibilities you will have: Drive requirements clarity and design decisions for ambiguous problems Produce technical design documents and project plans Develop new features Mentor more junior engineers Test and rollout to production, monitoring. What we look for: A passion for database systems, storage systems, distributed systems, language design, or performance optimization Are comfortable working towards a multi-year vision with incremental deliverables Be customer-oriented and focused on having an impact 5+ years of experience working in a related system Optional: PhD in databases or distributed systems About Dat

(P-1174) We are hiring a Senior Staff Software Engineer for Databricks' Engineering team reporting to an Engineering Leader. You will be part of the Databricks engineering organization, working with teams that develop Databricks products and features for thousands of enterprises worldwide. Key Characteristics As an executive engineering individual contributor at Databricks, you will have full ownership of the product or infrastructure direction in a major area, driving it from initial development to scalable solutions with clear business impact. You will serve as a force multiplier by elevating stability, reliability, and organizational processes, while bringing deep expertise in large-scale distributed systems. You will mentor senior engineers, contribute to recruiting, and lead high-impact company projects, often tackling complex problems beyond their comfort zone. Job Description 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. Our engineering teams build highly technical products that fulfill real, important needs in the world. 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. The Impact you will have: Solve real business needs at large scale by applying your software engineering. Deliver a highly scalable, available, and fault-tolerant engine processing hundreds of TB of data daily across thousands of customers Low level systems debugging, performance measurement &

(P-1174) We are hiring a Senior Staff Software Engineer for Databricks' Engineering team reporting to an Engineering Leader. You will be part of the Databricks engineering organization, working with teams that develop Databricks products and features for thousands of enterprises worldwide. Key Characteristics As an executive engineering individual contributor at Databricks, you will have full ownership of the product or infrastructure direction in a major area, driving it from initial development to scalable solutions with clear business impact. You will serve as a force multiplier by elevating stability, reliability, and organizational processes, while bringing deep expertise in large-scale distributed systems. You will mentor senior engineers, contribute to recruiting, and lead high-impact company projects, often tackling complex problems beyond their comfort zone. Job Description 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. Our engineering teams build highly technical products that fulfill real, important needs in the world. 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. The Impact you will have: Solve real business needs at large scale by applying your software engineering. Deliver a highly scalable, available, and fault-tolerant engine processing hundreds of TB of data daily across thousands of customers Low level systems debugging, performance measurement &

(P-1174) We are hiring a Senior Staff Software Engineer for Databricks' Engineering team reporting to an Engineering Leader. You will be part of the Databricks engineering organization, working with teams that develop Databricks products and features for thousands of enterprises worldwide. Key Characteristics As an executive engineering individual contributor at Databricks, you will have full ownership of the product or infrastructure direction in a major area, driving it from initial development to scalable solutions with clear business impact. You will serve as a force multiplier by elevating stability, reliability, and organizational processes, while bringing deep expertise in large-scale distributed systems. You will mentor senior engineers, contribute to recruiting, and lead high-impact company projects, often tackling complex problems beyond their comfort zone. Job Description 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. Our engineering teams build highly technical products that fulfill real, important needs in the world. 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. The Impact you will have: Solve real business needs at large scale by applying your software engineering. Deliver a highly scalable, available, and fault-tolerant engine processing hundreds of TB of data daily across thousands of customers Low level systems debugging, performance measurement &

Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse ( CIDR 2021 paper ), open platforms that unify data warehousing and advanced analytics. The new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support. A critical part of realizing this vision is the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance, yet retain the expressiveness and of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science. As part of this team, you will be working in one or more of the following areas to design and implement these next gen systems that leapfrog state-of-the-art: Query compilation and optimization Distributed query execution and scheduling Vectorized execution engine Data security Resource management Transaction coordination Efficient storage structures (encodings, indexes) Automatic physical data optimization What we look for: A passion for database systems, storage systems, distributed systems, language design, or performance optimization Experience working towards a multi-year vision with incremental deliverables Motivated by delivering customer value and impact 5+ years of experience working in a related system (preferred) Optional: PhD in databases or distributed systems 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 non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based