Performance And Systems Engineer Jobs

Join the MongoDB Networking & Observability team and help build the core of a distributed database! Our team focuses on creating and enhancing components which facilitate communication between distributed processes and make these processes, and their communication, easily observable. Networking Observability’s responsibilities include improving MongoDB networking, improving the efficiency of resource utilization, and building low-overhead observability features. Our team includes engineers located in New York City and fully remote engineers. We operate close to the bottom of the stack, and have a lot of influence over the availability, performance, and robustness of our open source database. Recently, we’ve improved connection handling, explored new networking architectures, and integrated OpenTelemetry to make issues easier to diagnose and connect MongoDB to modern observability tools. We are planning to further improve our networking’s stack performance, availability and scalability as well as further enhance our observability stack using open observability frameworks. Are you excited to help the MongoDB engineering team build a better database? We are! Join us today, and we can build a faster, more reliable, exceptionally observable, database system together. This role will be based remotely in Canada. Candidate Profile 3+ years of experience building distributed systems Passionate about delivering and deploying a product with cross-team stakeholders Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Hands-on experience with building production-level code. Experience in C++ is required Interest in furthering their knowledge of networking, observability and how computer architecture and internals impact the availability of SaaS Solid verbal and written communication skills and highly motivated to collaborate with colleagues Position Expectations Understand and improve the current funct

Join the MongoDB Networking & Observability team and help build the core of a distributed database! Our team focuses on creating and enhancing components which facilitate communication between distributed processes and make these processes, and their communication, easily observable. Networking Observability’s responsibilities include improving MongoDB networking, improving the efficiency of resource utilization, and building low-overhead observability features. Our team includes engineers located in New York City and fully remote engineers. We operate close to the bottom of the stack, and have a lot of influence over the availability, performance, and robustness of our open source database. Recently, we’ve improved connection handling, explored new networking architectures, and integrated OpenTelemetry to make issues easier to diagnose and connect MongoDB to modern observability tools. We are planning to further improve our networking’s stack performance, availability and scalability as well as further enhance our observability stack using open observability frameworks. Are you excited to help the MongoDB engineering team build a better database? We are! Join us today, and we can build a faster, more reliable, exceptionally observable, database system together. This role can be based out of our New York City office or remotely within the United States and Canada. Candidate Profile 3+ years of experience building distributed systems Passionate about delivering and deploying a product with cross-team stakeholders Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Hands-on experience with building production-level code. Experience in C++ is required Interest in furthering their knowledge of networking, observability and how computer architecture and internals impact the availability of SaaS Solid verbal and written communication skills and highly motivated to collaborate with colleagues Po

P-1428 At Databricks, we run the world's largest AI platform. We believe the next breakthroughs will come from models trained on domain-specific enterprise data, not from bigger general-purpose models alone. That's why we built AI Runtime , a serverless product that makes GPU training of any size feel simple, so companies can train their own models the way frontier labs do. Customers across industries already use it to train models on governed data, from automotive AI at Rivian to Merck's TEDDY foundation models for single-cell biology and drug discovery, all the way to agents like KARL from Databricks AI Research. It takes a lot of engineering to make that work, and we've written about it on our blog: how we keep GPUs reliable , make training fault-tolerant , and speed up fine-tuning with fused kernels and smart sequence packing. As a Senior Software Engineer, you'll work on the systems behind all of this, solving hard technical problems and helping shape how AI Runtime evolves. The impact you will have: Build core parts of AI Runtime and contribute to Databricks' technical direction in AI training infrastructure. Develop reliability and observability features for a fleet that keeps growing in scale and complexity. Improve AI Runtime's developer experience, so the largest training jobs feel as simple as a first experiment. Help prepare AI Runtime for new GPU generations and workload types. Take on hard multi-node training problems, from orchestration and GPU scheduling to data loading and checkpointing. Make training faster and cheaper by raising GPU efficiency across model architectures and hardware generations. Work with research, product, and customers on what we build next and own features from design through production. Champion engineering excellence, raise the bar, and help the engineers around you grow. What we look for: 5+ years in large-scale distributed systems, with experience in GPU training, high-performance computing, or ML systems. Experience traini

About Us: Future is building a personalized guidance system for lifelong health. We help people understand what to do next for their body, goals, and stage of life — then support them in turning those decisions into sustained behavior change. By combining AI, human expertise, personal health data, and accountability, Future helps members improve performance today while building the resilience, capacity, and healthspan they need for decades to come. About the Role We're looking for an Applied AI Engineer to help us build and ship AI-powered features that directly improve our product experience and business outcomes. This is a hands-on, product-focused role where you'll take ideas from concept to production — designing intelligent systems, validating them with real users, and turning them into reliable, scalable services. You'll work at the intersection of AI, product, and engineering — partnering closely with cross-functional teams to identify high-impact opportunities, prototype quickly, and iterate based on data. This isn't a research-only role. You'll own the full lifecycle: experimentation, evaluation, deployment, monitoring, and continuous improvement. The ideal candidate is excited about applying LLMs and modern ML tooling to real-world problems. You think in terms of systems, tradeoffs, and outcomes — not just models. You care about performance, quality, latency, and cost in production. Most importantly, you're motivated by shipping impactful AI experiences that customers actually use. What You'll Do Build and ship AI agents that serve real users: tool-calling LLM systems with structured output, parallel API orchestration, and streaming responses. Design evaluation harnesses and quality scoring — we use Langfuse, rubrics to measure safety, effectiveness, and personalization. Own the full loop: prototype a new agent capability, validate it with evals, deploy it to staging and production, monitor traces, and iterate. Improve reliability, latency, and cost throug

NVIDIA is hiring senior engineers to develop its AI platform and more specifically its performance optimizations in deep learning frameworks using JAX, a tool that can differentiate between Python control code and NumPy code. Our goal is to deliver a polished, fast, modular and coordinated platform to handle data, training and analysis for a wide range of deep learning solutions using JAX. To achieve this and provide an excellent user experience, you have strong programming skills and excellent system design skills. You should have excellent communication and planning skills for this role. Come join us to build the next generation of tooling that will advance the numerical computing and machine learning research around the world! What you will be doing: Play meaningful role in NVIDIA's effort in contributing to JAX. Design and implement JAX core components and drive peak performance on NVIDIA products. Work with AI applied researchers and leaders to build future-proof models Build tools that will increase the efficiency of teams developing AI-based systems. Work to bridge the gap between the latest in numerical computing, simulation and deep learning research and their applications in real world products. What we need to see: BS in Computer Science or Computer Engineering or related field (or equivalent experience). 6+ years relevant experience. C/C++ and Python programming. Experience with machine learning frameworks and their internals (e.g. PyTorch, TensorFlow, scikit-learn, etc.). Proven ability developing customer-facing solutions, balancing feature requests and bugs. Proven technical foundation in CPU and GPU architectures, numeric libraries, modular software design. Highly motivated with excellent ver

The NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We are building the next-generation data and storage infrastructure to solve some of the hardest problems in AI: storage, access, ingestion, governance, observability, and data management for exabyte-scale, high-performance GPU-based training and inference jobs. Our work gives NVIDIA teams the foundational capabilities they need to build, train, deploy, and operate AI products at scale without reinventing critical data infrastructure for every workload. What you will be doing: Build storage technologies, client libraries, and filesystem frameworks that help AI workloads access data across object stores, file systems, and hybrid cloud infrastructure. Develop high-performance storage paths for training and inference workflows, including data loading, checkpointing, caching, POSIX-style access, and object-store integration. Build observability systems that diagnose storage bottlenecks, attribute GPU idle time to I/O behavior, and expose actionable telemetry through production monitoring stacks. Improve performance, scalability, and reliability of storage systems serving massive datasets, deep directory trees, and high-concurrency AI workloads. Work closely with internal AI teams, platform teams, SRE, and operations to validate storage behavior against real workloads and production environments. Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, performance, and verification. What we need to see: BS in Computer Science, Information Sys

At Carbon, our mission goes beyond 3D printing. We are enabling creators everywhere to make what the world needs, right now. Our company is built on the idea that diverse fields of study must come together to solve intractable problems. We have grand ambitions to create technology that will influence industry around the world. You will be joining a diverse team with a vibrant culture, where team success is as important as celebrating individual contributions. Help us change the world and we will help you change yours. As a Senior Staff Mechanical Engineer, you will be a primary architect of Carbon’s hardware future. You won't just design parts; you will define the technical roadmap and foundational architectures for our next generation of additive manufacturing solutions. As a senior leader within a high-velocity hardware team, you will navigate extreme ambiguity to deliver elegant, high-reliability systems. You are expected to be a technical cornerstone, elevating the engineering bar across the organization and mentoring the next generation of staff-level talent Note: This role is remote; working from a home office in North Carolina. You will… Drive Hardware Architecture: Own the high-level mechanical architecture for new 3D printing platforms, ensuring modularity, serviceability, and industry-leading precision. Lead Cross-Functional Technical Delivery: Act as the technical bridge between Systems, Electrical, Software, and Materials Science to de-risk 0-to-1 products. Establish Engineering Standards: Define company-wide frameworks for validation, reliability testing, and DFM to ensure hardware excellence at global scale. Influence the Roadmap: Partner with Leadership and Product Management to translate product needs into a multi-year technical execution strategy. Navigate Technical Debt: Proactively identify and resolve architectural gaps in our technology to improve long-term product performance. Act as a Technical Gatekeeper: Serve as an

About the Role The Infrastructure team builds and operates the foundational systems behind Perplexity’s products. At Perplexity, infrastructure sits on the critical path of every answer, supporting real-time search, retrieval, model serving, and agent workloads where latency, reliability, and rapid iteration directly shape the user experience. This role is for strong infrastructure engineers whose experience spans multiple domains and who are energized by cross-cutting problems that do not fit neatly within a single platform team. You do not need to be a specialist in every area. Scope ranges from owning major production systems to setting technical direction across teams, leading complex infrastructure programs, and shaping infrastructure strategy across the organization. If a specialized Cloud Infrastructure, Storage Platform, Backend Platform, Data Platform, Connector Platform, or AI Acceleration role clearly matches your expertise and interests, apply directly to it. If your experience spans several infrastructure domains or you are most energized by cross-cutting systems problems, apply here. Submit one application, and we will consider you across the Infrastructure organization. Key Responsibilities Own cross-cutting infrastructure problems that span compute, storage, networking, data, deployment, and reliability, including eliminating bottlenecks across retrieval and serving paths, building shared abstractions across deployment environments, and resolving failure modes that cross platform boundaries. Design, build, and operate distributed infrastructure supporting Perplexity’s consumer, AI, and enterprise workloads, owning systems from architecture through production operation. Identify gaps between existing platforms and build shared abstractions, automation, and tooling that make infrastructure easier and safer to use. Improve system performance, availability, scalability, and cost-efficiency across online request traffic and background workloads. Debug com

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 SoC Design Verification Engineer to validate the System Management Controller (SMC) and enable seamless multi-chip integration. In this role, you will design and execute tests, build infrastructure, and debug issues across chiplet-based SoCs. You’ll have the opportunity to work with remote mentorship while contributing to the foundation of scalable multi-die systems. This role is hybrid, based out of Toronto, Ontario, Boston, MA or Santa Clara, CA. 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 Proficient in SystemVerilog, SV-UVM, Python, and C/C++ with strong verification skills. Experienced in writing test plans, building infrastructure, and debugging hardware/software flows. Comfortable working with remote mentorship and distributed teams. Familiar with AI-assisted tools like Copilot, Cursor, and Claude to accelerate verification. What We Need Develop and maintain SMC tests and supporting DV infrastructure. Write, execute, and track test plans for chiplet and multi-chip SoC designs. Use C/C++ to develop tests compiled, loaded, and executed directly on the DUT. Triage, analyze, and debug issues in clos

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. At Tenstorrent, we are building open, scalable compute for real AI workloads. As Director, Customer Hardware Engineering, you own the technical relationship with strategic customers and FAEs, turning their silicon needs into precise requirements for our hardware and software teams. You connect customer architectures to Tenstorrent platforms so their models run efficiently on our silicon. This role is hybrid, based out of Toronto, Austin, TX or Belgrade, Serbia. 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 Experienced leader of customer-facing technical teams and Field Application Engineering organizations. Strong background across RTL, verification, and physical design for custom silicon programs. Systems thinker who understands how RTL choices affect software, performance, and customer solutions. Clear communicator who aligns customers, FAEs, and internal teams around shared technical goals. What We Need Own technical customer relationships and convert high-level asks into concrete engineering specifications. Coordinate with hardware and software leads on customer-specific NEO silicon configurations. Oversee RTL changes and NEO cus

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 SoC Design Verification Engineer to lead pre-silicon verification of the Beowulf SoC, with focus on the Compute Subsystem (CSS), DDR memory subsystem, and Fabric NoC. This role will drive coverage, coherency, memory traffic, connectivity, error handling, and bring-up features critical to silicon success. This role is hybrid, based out of Boston, MA; Toronto, ON; or Santa Clara, CA. 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 Deeply curious about SoC architecture, compute systems, DDR behavior, and Fabric NoC/interconnect verification. Expert in UVM, SystemVerilog, coverage-driven verification, assertions, and subsystem-level debug. Experienced in verifying compute subsystems, DDR controllers and PHY-facing logic, NoC/interconnect protocols, coherency, ordering, and data movement. Comfortable with reset, power management, error handling, performance, and high-concurrency system scenarios. Proactive, detail-oriented, and effective in cross-functional technical discussions. Familiar with Python, C/C++, Tcl, CocoTB, or similar verification automation tools. What We Need Develop and own scalable verification environmen

We are seeking software engineers to work on next-generation graphics and computing products. Our charter is to build the most stressful set of applications a GPU or high performance computing server would see in its life cycle. The best candidates will have strong C++ programming skills, detailed knowledge of graphics concepts and algorithms, a proven foundation of systems software with emphasis on OS fundamentals, and a deep understanding of current generation hardware architecture at systems level. Excellent interpersonal skills and a dedication to meticulous engineering practices are a requirement. As a system software engineer, you will extensively use your knowledge of operating systems, algorithms, and computer architecture to provide robust and efficient solutions to validate and test next generation processors. Join us! What you'll be doing: Working closely with architecture, hardware and driver teams through the product development lifecycle of computing and graphics processors, as well as compute products. Responsible for crafting software tools and infrastructure required for new chip development, validation, and productization. You will assess new hardware features and architect manufacturing diagnostic tests using pre-beta CUDA and OpenGL extensions. This job will require an understanding of our hardware and software architectures. What we need to see: BS or MS degree in one of the areas of Electrical Engineering, Computer Engineering, Computer Science or equivalent experience Strong C/C++ or Python programming skills Familiarity with computer architecture, and ability to work close to the hardware 5+ years of relevant experience Background with PCIe, NVLink or server product technologies like InfiniBand, Ethernet is a plus Previous experience of working on a large system software code

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

Where Performance Meets Purpose Join a team that values excellence and innovation, at a company known for its iconic golf brands. At Acushnet Company, your background and experience contribute to creating the best products for dedicated golfers worldwide. Here, your performance has purpose. What You Will Be Doing The Senior Industrial Engineer plays a vital role in advancing manufacturing and distribution excellence by driving efficiency, innovation, and continuous improvement across operations. This position applies industrial engineering principles to optimize production processes, facility layouts, material handling systems, and labor utilization while supporting East Coast manufacturing and distribution teams. The role leads projects involving equipment installation, relocation, and workflow redesign; develops labor and capacity models for global golf ball manufacturing; and identifies opportunities for cost reduction, productivity gains, and operational improvements. Through data-driven analysis, reporting, and cross-functional collaboration, the Senior Industrial Engineer helps ensure safe, efficient, and scalable operations that support long-term business growth. What You Bring Bachelor’s degree in Industrial Engineering or a related Engineering discipline required Minimum of 5 years of Industrial Engineering experience Proficient in the use of computers and engineering software Ability to sit, stand, walk, crawl, and climb for extended periods as needed Proficiency with AutoCAD and Microsoft Office applications Experience with facility layout design and optimization Strong knowledge of capacity planning and capacity analysis Experience with Lean manufacturing, process simp

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the Role Anyscale is seeking a Staff Software Engineer to lead the technical vision for our Infrastructure team. As a Staff Engineer, you will be responsible for the architectural evolution of our control plane and data plane, ensuring that our "infinite laptop" vision scales to meet the most demanding distributed AI workloads in the world. You will act as a force multiplier, setting the standards for Kubernetes-based cloud-native infrastructure while mentoring engineers and driving cross-functional alignment across the Ray open-source community and our proprietary product teams. Key Responsibilities Architectural Leadership: Define and drive the multi-year technical roadmap for services that orchestrate Ray clusters across diverse cloud and on-premises environments. Systemic Optimization: Lead the design and optimization of high-performance control plane components specifically tailored for large-scale, heterogeneous AI/ML workloads. Platform Reliability: Establish the organization-wide standards for the reliability, scalability, and observability of Anyscale-managed infrastructure. Strategic Integration: Direct the long-term strategy for accelerator integration (GPUs, TPUs) and container management to ens