Senior Staff Systems Engineer Jobs

Senior: PLN 260,400 - 352,200 Staff PLN 350,700 - 474,400 Subject to alignment to the responsibilities and duties of the role - we currently have multiple positions available at both Senior and Staff level. About the job Build the quality foundations for Kubernetes systems that power next-generation AI compute. As a Staff QA Engineer, you will validate the workload management stack for new AI accelerator hardware. You will help ensure our Kubernetes integrations are robust, scalable and ready for production. Your work will shape how accelerators are scheduled, orchestrated and used across distributed environments. You will test the systems that make complex AI compute infrastructure reliable for real users. You will design automated test suites, build system and integration tests, and improve CI/CD quality practices. You will also debug issues across Kubernetes, infrastructure and applications. This role is for someone who wants to raise engineering quality across a deeply technical platform. The team and culture You will join the Workload Management team, working closely with software engineers and infrastructure specialists. The work is hands-on, systems-focused and driven by clear technical ownership. Quality is built early here, not checked at the end. You will influence test strategy, validation plans and automation practices across the development lifecycle. The team moves through open technical discussion and evidence-based decisions. You will mentor others, speak up on risk and help turn complex systems into dependable products. What we’re looking for Strong Python programming experience, with a focus on automation and test engineering Hands-on experience with Robot Framework or similar automation frameworks Experience testing cloud-native, containerised or distributed systems Strong Linux understanding and confidence debugging across multiple system layers Experience with CI/CD systems such as GitLab CI or GitHub Actions Ability to define quality standards,

Senior: PLN 260,400 - 352,200 Staff: PLN 350,700 - 474,400 Subject to alignment to the responsibilities and duties of the role - we currently have multiple positions available at both Senior and Staff level. Location: Gdańsk. This role is not available as fully remote. About the job Build the AI compute libraries that turn next-generation hardware into real performance. As a Staff Software Engineer, you will design and optimise high-performance compute kernels for AI workloads. You will work across linear algebra, tensor operations, numerical correctness and low-level performance. Your work will help customers get more from advanced AI hardware. That means shaping the libraries behind faster, more reliable AI systems at scale. You will write C++ and Python, profile on Linux and make hard trade-offs across memory, threading and numerical behaviour. You will also guide technical direction, review designs and help engineers make better decisions. This role suits someone who wants deep technical ownership without moving away from hands-on engineering. The team and culture You will join the ML Kernels & Runtime team, which builds the compute libraries that expose hardware performance to customers. The work is technical, detailed and close to the machine. Engineers own problems from design through validation, benchmarking and production quality. Decisions are made through evidence, clear technical reasoning and open debate. You will move quickly, speak up when something can be better and help others raise the quality of their work. Leadership here means taking responsibility for outcomes, not waiting for permission. What we’re looking for Excellent C++ and Python skills, with experience building performance-sensitive software Strong understanding of processor architectures, Linux profiling and low-level optimisation Proven technical leadership, including guiding engineering direction, reviewing designs and mentoring others Ability to balance hands-on implem

Machine Learning Engineer – Biometrics (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestra

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. As a Staff Software Engineer on the Order Platform team, you'll shape the systems that power every Affirm purchase after checkout — orders, captures, refunds, and settlement — and drive the technical strategy that lets our merchants and consumers transact reliably at scale. Your work raises the bar for reliability and simplicity across our engineering systems, keeping the platform highly available while defining the capabilities that unlock future product needs. We're a small, senior team doing high-leverage work within Financial Platforms. Today we're consolidating the internal platform behind Affirm's post-checkout APIs — drawing clean domain boundaries, migrating existing merchants, and enabling future product launches. You'll set technical direction, mentor a strong group of engineers, and own decisions that matter for years. What You'll Do · You will be responsible for setting technical strategy for your team on a year-long time scale, and help your team tie it together with critical, business-impacting projects. · You will collaborate across teams in the product development lifecycle by collaborating with product management, design & analytics to ensure technical sustainability, risks and trade-offs are well understood and managed. · You will act as a force-multiplier for your team through your definition and advocacy of technical solutions and operational processes. · You take ownership of your team’s operations and availability by ensuring you have the right monitoring, triage rotations, playbooks, polcities, testing and alerting in place to support “keep the lights on” & on-call efforts. · You will foster a culture of quality and ownership on your team by setting code review and design standards for your team, and advocating for them beyond your team through your writing an

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Operations Central Team (OCT) Diffusion/Implant Manufacturing Alignment Senior Engineer/Staff Engineer will drive tool and process optimization, global manufacturing alignment, and preventive maintenance standardization across the Micron network. This role will collaborate with equipment and process engineering teams to improve tool utilization, develop safe shutdown and recovery procedures, deploy equipment and process BKMs, and sustain global standards through systems such as SEAL. The position requires strong technical experience in the Diffusion or Implant area, problem-solving capability, effective cross-functional communication, and the ability to support AI-assisted data analysis and workflow improvement. Take on an outstanding opportunity at Micron, where new ideas meet outstanding quality. As an OCT Diffusion/ Implant MFG Alignment Sr Engineer/ Staff Engineer in Hiroshima, you will maintain and improve our innovative manufacturing systems and methods. Collaborate with a group that shares your passion for detail and your aim to achieve international excellence! Responsibilities: Improve tool utilization to meet world-class standards by refining processes that eliminate underutilized tools and enable cost savings through strategic cold/warm shutdowns. Develop globally aligned warm shutdown procedures that ensure safety and flawless recovery to production. Standardize practices and proven methods (BKMs) across process areas by establishing global alignment tea

P-1563 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 in Bengaluru , India ! As a software engineer with a backend focus, you will work with your team to build infrastructure for the Databricks platform at scale. About the Team We manage the infrastructure efficiency for one of the world's largest data and AI platforms. Operating at massive scale across AWS, Azure, and GCP, our mission is to ensure that every dollar spent on cloud infrastructure is optimized. The MCE team builds the critical tools, frameworks, and automated systems that provide deep cost visibility and ensure maximum resource utilization. We aren't just cutting costs; we are engineering systems to scale efficiently as our cloud footprint expands into the hundreds of millions of dollars. The Role As a Staff Software Engineer, you will serve as the technical lead for the Bengaluru MCE chapter. You will be responsible for defining the technical strategy for efficiency projects where the solutions are not yet known. You will lead cross-functional efforts, working with finance and cost team, to tackle massive-scale engineering challenges, ensuring our systems can automatically drive cost efficiency and handle the complexity of global, multi-cloud data processing without compromising on performance or stability. As one of the founding senior engineers of the Bengaluru MCE chapter — a team that has already deliver

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, CPU families, and clouds. The Capacity Engineering team is responsible for making sure all of our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute — one of the company's largest areas of spend. As the Senior Engineering Manager for Capacity Engineering, you will lead the team that builds and operates these production systems. You'll set technical direction, grow and develop a team of senior and staff-level engineers, and be accountable for the reliability and correctness of surfaces that leadership, research engineering, inference, infrastructure, and finance all depend on. This is a hands-on leadership role and will be onsite 5 days a week: we expect you to stay close enough to the systems to review designs, make sound architectural calls, and step into an incident when the team needs you — while spending most of your time on people, priorities, and cross-organizational alignment. The team's work spans three overlapping areas, and you'll be responsible for balancing investment across them as business priorities shift: Data platform — Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Consumers range from research engineers to finance to leadership, s

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are seeking an exceptional and technically grounded Senior Manager, Software Development Engineering to lead our core Data Loss Prevention (DLP) engineering team within the Zero Trust Exchange department. Based in San Jose, CA, and reporting to the Senior Director, Software Development Engineering, you will lead the architecture, design, and delivery of high-throughput, low-latency DLP engines, dictionary matching systems, and intelligent content inspection pipelines running in C across FreeBSD and Linux environments. In this role, you will balance strategic leadership with deep systems rigor, bridging deterministic inspection mechanisms with next-generation Named Entity Recognition (NER) and ML models while navigating real-time inline performance trade-offs. What you'll do (Role Expectations) Manage, mentor, and grow a world-class team of systems software engineers and principal architects responsible for hi

About the Role The Backend Platform team is the backbone of Perplexity’s product reliability, scalability, and performance, enabling every product and AI team to build with confidence. This high‑impact group builds and maintains critical infrastructure, including backend systems for authentication, authorization, real-time data flows, service orchestration, and sandboxing, to ensure fast, reliable, and secure user experiences. By setting rigorous standards for code quality, uptime and performance, the Platform team ensures everyone at Perplexity can innovate at speed on top of a robust, well-architected foundation. Key Responsibilities Lead the design and implementation of our sandboxing platform to safely execute untrusted and user‑generated code while meeting strict performance and reliability requirements. Define and extend our RBAC and authorization primitives, ensuring they scale with new product capabilities and enterprise controls. Own key backend services involved in authentication and encryption flows (including BYOK‑related pieces), partnering with Security and Infra on defense‑in‑depth. Set the technical bar for backend platform design and operations, driving best practices in reliability, observability, and incident response for always‑on systems. Partner with product and AI teams to define clear platform interfaces, SLAs, and integration patterns so new features can reliably build on shared backend capabilities. Provide technical leadership across the backend platform area, mentoring other engineers and making long‑term architectural decisions that keep the foundation simple, secure, and evolvable. Qualifications Experience designing and building backend systems that run in production (typically 4+ years for mid-level, more for senior and staff). Strong system design skills, with a track record of creating efficient, reliable, and scalable architectures. Hands-on experience with modern infrastructure (for example AWS, Kubernetes, and related cloud techn

Role Purpose We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on ex

Machine Learning Engineer – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like A

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper

About the role Chime is looking for a Director of Engineering to lead our AI & App Experience (AAX) organization — the team building the next generation of the Chime member experience. AAX owns Jade, Chime’s AI-powered financial assistant, our AI platform infrastructure as well as the core app experiences and shared design system. In this role, you’ll own the multi-quarter strategy for AAX engineering, translating company priorities into scalable plans across these teams. You’ll build and lead a bench of TLM (tech leader managers) and senior technical staff, set the technical bar for how Chime builds AI-native, member-facing products, and partner with Product, Design, Data Science, and our Risk team to shape where AAX invests next. This is a role for a leader who is equally comfortable setting long-range technical vision and staying close enough to the details to guide hard architectural calls — someone who has helped build or scale AI/LLM-powered consumer products and knows how to grow the engineering leaders around them. In this role, you can expect to In partnership with our product team you will own the multi-quarter strategy for AAX engineering, translating company and product priorities into our roadmap plans across consumer facing AI experiences, AI Platform, App Journey, and Design Systems. Build, lead, and hire a high-caliber leadership bench of highly technical leaders/IC’s as well as building a team culture that exemplifies a builder mindset. Partners with your team to set technical direction for the org, driving architectural alignment across our consumer facing AI experiences, AI Platform, App Journey, and Design System. You will continue to drive our AI-native engineering culture: setting the bar for how LLM-powered features get shipped safely at scale. Own engineering’s strategic role in product direction, partnering with Product, Design, Data Science, and Risk leadership to shape roadmaps, challenge assumptions, and integr

About the Team Dots is building personal AI agents that help people make progress on their goals, including when they are away from ChatGPT. These agents can learn preferences, maintain context, work across applications, and use cloud computers to carry out tasks. Our team brings together product engineering, design, and research to turn frontier model capabilities into useful everyday experiences. We are defining how people delegate work, understand what an agent is doing, and stay in control. Engineers help shape both the product and the systems behind it, from early prototypes through launch and iteration. About the Role We are looking for Senior and Staff Full Stack Software Engineers to build Dots product experiences from the interface through the services that power them. You will help define how people delegate tasks to personal agents, follow their progress, and collaborate with them over time. This role combines hands-on product development with the systems work needed to make persistent, asynchronous agent experiences reliable. In this role, you will: Build and launch features across web interfaces, APIs, backend services, and data models. Create workflows for task creation, progress updates, agent feedback, and results that remain coherent across sessions and devices. Translate emerging model capabilities into product prototypes with research, product, and design partners. Design clear interfaces between product surfaces and agent execution systems. Improve performance and reliability across the stack, including user-facing latency and recovery from partial failures. Own projects from early exploration through architecture, implementation, launch, and iteration based on user feedback. Help establish technical direction, testing practices, and observability as the product grows. You might thrive in this role if you: Have significant experience building and shipping products across frontend and backend systems. Can move comfortably between user interfaces,

About the Team Dots is building personal AI agents that help people make progress on their goals, including when they are away from ChatGPT. These agents can learn preferences, maintain context, work across applications, and use cloud computers to carry out tasks. Our team brings together product engineering, design, and research to turn frontier model capabilities into useful everyday experiences. We are defining how people delegate work, understand what an agent is doing, and stay in control. Engineers help shape both the product and the systems behind it, from early prototypes through launch and iteration. About the Role We are looking for Senior and Staff Software Engineers to build the mobile web experience for Dots. You will create responsive, accessible interfaces that let people start work, follow progress, and guide their agents from a phone or browser. You will help establish interaction patterns for ongoing, asynchronous work and make sophisticated agent capabilities feel clear and approachable. In this role, you will: Design and ship mobile web experiences for creating tasks, reviewing agent activity, and providing feedback or direction. Build interfaces that handle streaming updates, long-running tasks, interrupted sessions, and changing connectivity. Improve responsiveness, loading performance, accessibility, and usability across screen sizes and browsers. Partner with design and product to prototype interaction patterns that give users visibility and control over agent actions. Work with backend and full stack engineers on APIs, client state, and reliable synchronization between the interface and agent services. Own features from exploration and technical design through launch, measurement, and refinement. Help set frontend architecture and engineering practices while staying hands-on with implementation. You might thrive in this role if you: Have substantial experience shipping polished web applications, with deep expertise in mobile web development