Staff Quality Engineer Jobs

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

About the Role We’re looking for a Senior Web QA Engineer to join our Web QA team and help maintain the quality of the core web experience used by millions of people every day. In this role, you’ll test the web products and work closely with engineers to find, report, and help resolve issues early. You’ll also look at how the web experience fits into the wider Perplexity product ecosystem, making sure key flows work consistently across surfaces. Key Responsibilities Test Perplexity’s web product across browsers, devices, and screen sizes, checking functionality, reliability, and performance throughout the development cycle. Run end-to-end integration testing with other Perplexity products, validating shared flows, accounts, and features. Work directly with engineers to prioritize critical bugs, write clear and actionable bug reports, and help get issues resolved. Create and maintain test documentation, including test cases, checklists, and test plans, keeping them current as the product changes. Analyze high-impact user-reported issues and incidents, then share insights that help improve both the product and our QA process. Fix small, low-risk issues yourself where appropriate, shipping simple fixes to reduce engineering overhead and speed up resolution. Qualifications 5+ years of experience in QA, with strong hands-on experience testing web applications Solid experience with web testing, including cross-browser and responsive testing, debugging with browser DevTools (console, network, performance), and validating functionality across environments and builds Experience with integration and end-to-end testing across multiple connected products or services Strong communication skills, with the ability to work effectively with engineering, product, and other QA teams Proactive use of AI coding tools (e.g. Cursor, Claude Code) to navigate the codebase, debug issues, and ship small fixes independently

About the Team At DoorDash, design means making experiences for the people who order, the people who prepare, and the people who deliver. As a Designer at DoorDash, you want to build things that matter to real people. You're at your best when you can move from idea to shipped product quickly, bringing experiences to life that reach and influence users at massive scale. You'll care about whether the product you make solved a real problem for real people, or changed how someone experiences their day. You'll work shoulder-to-shoulder with Engineering and Product Management, dig into the data, and use LLM-powered tools alongside traditional design tools. If the LLM powered tools don’t exist yet, you build them. About the Role We’re looking for a Staff Product Designer to join our Support Design team and shape how we as a product and brand show up for our customers, dashers, and merchants when they are looking to us for help. We design the system and experiences across the full support journey, from proactively preventing issues from happening to delivering exceptional quality support that drives loyalty. Our scope spans immersive, multi-modal mobile experiences (order tracking, self-help, chatbot and voice ai) to operationally critical internal tooling and infrastructure (case management, agent training, performance, automation). You will report to the head design for Customer Experience and Integrity, working alongside designers focused on support experience, support tooling, fraud, trust, safety, and compliance. We operate in a hybrid model with 1-2 days per week in our New York City office. You’re excited about this opportunity because you will… Define projects with a clear point of view on what to build, writing briefs that synthesize business and customer inputs into roadmap milestones; balance customer needs, business goals, and feasibility to shape what your team builds and why Bring clarity to ambiguous, cross-team problems and turn them into actiona

The opportunity Datadog’s Infrastructure products help engineers understand and operate the systems their applications depend on. Our customers work in complex environments like Kubernetes and serverless, where infrastructure changes constantly, information is dense, and decisions about reliability, performance, and cost are closely connected. We’re looking for a Staff Product Designer to join Modern Compute, with an initial focus on Containers Autoscaling. Autoscaling helps engineering teams make better decisions about how their applications and infrastructure use resources. Designing these experiences requires making deeply technical systems understandable, helping customers act with confidence, and fitting into the tools and workflows they already use. The team is rethinking how workload and cluster autoscaling come together as a more coherent product experience. This includes how customers get started, understand recommendations, evaluate value, and safely apply changes across their environments. The work also connects to other parts of Datadog, including observability, Cloud Cost Management, permissions, and AI-assisted workflows. As a Staff Product Designer, you will help define that direction and lead the work from early problem framing through shipped product. You will partner closely with product and engineering, bring a high level of interaction and visual craft to complex workflows, and help raise the quality of design across Modern Compute. At Datadog, we place value in our office culture, the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to help our Datadogs find a work-life rhythm that works for them. What you’ll do Lead end-to-end product design for Modern Compute, initially focused on our Autoscaling product. Help define the product direction for an area that is still evolving, from early framing and exploration through detailed design and delivery. Design clear, trustwort

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

Our mission: Creating the freedom for SMEs to succeed in business and beyond, by delivering Europe's leading finance workspace. Our journey: Founded by Alexandre and Steve in July 2017, Qonto has rapidly gained trust, serving over 600,000 customers with a team of 1,600+ Qontoers across Europe. Our beliefs: We evaluate applicants based on skills and potential — no boxes to tick. Our team is 55% international, 44% women, and 20% parents. Discover the steps we took to create a discrimination-free hiring process. ⭐ Mission Join us as a Freelance Full-Stack Engineer to build one of Qonto's first internal applications: a modern, high-quality People platform that transforms the daily experience of 1,700+ Qontoers - from compensation cycles and performance reviews to everyday HR workflows. You'll work hand-in-hand with Mélodie, our Head of People Systems, on a high-ownership mission: co-define the product vision, design the architecture, and ship to production. This is not a staff-augmentation engagement - it's a mandate for someone who builds like an owner. 👩‍💻🧑‍💻 As a Freelance Full-Stack Engineer, you will • Ship the People platform MVP by December 2026: migrate key Workday modules into a custom internal app (React for the front, Go for the back) that handles comp cycles, performance reviews, and daily HR workflows for 1,700+ Qontoers - on time and with zero compromise on quality. • Co-define the product vision and roadmap with Mélodie: run user discovery with People teams, challenge specs, and help decide what gets built first - not just how to build it. • Design for security and compliance from day one: architect systems that handle sensitive People data (GDPR, access controls, data residency) with the rigor the context demands. • Ship faster with AI: leverage AI tools (Cursor, Claude Code, Copilot…) in your daily workflow and build AI-enabled features where they create real leverage for the People team. • Enable long-term adoption: document your work, r

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

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. As a Staff or Senior Staff Technical Program Manager on the Data Center Deployment and SRE team, you will drive complex programs spanning hardware, software, infrastructure, and data center operations. You will connect technical dependencies, operational data, and engineering workflows to improve how systems are deployed and scaled. This role combines deep technical understanding with hands-on program leadership, using automation and data to improve execution, visibility, and decision-making across teams. This role is hybrid, based out of Toronto, Canada. 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 A self-directed technical leader who can take ambiguous, cross-functional problems and turn them into structured, executable programs. A systems thinker with a strong understanding of computer architecture, operating systems, runtime systems, and the dependencies between hardware and software. Hands-on with data, tooling, and automation, with the ability to connect systems and improve the quality and accessibility of program information. An effective technical partner who can work deeply with engineering teams while communicating risks, tradeof

About the Role We're hiring software engineers for the Model Behavior team to help shape how Perplexity’s AI products behave: the style of their responses, and the way they use tools, skills, and memory. The team designs prompt and context engineering strategies to deliver high-quality user experiences across multiple domains and models. The ideal candidate for this role has a strong software engineering background, and an analytical, experiment-driven approach to solving challenging problems. You’ll work on context and prompt engineering to shape model behavior and style, and to guide how models use tools, skills, and memory across our products. What you'll do Context Engineering: Design, test, and optimize the prompts, skills, tools, and memory that shape Perplexity responses across products, features, and use cases. Build self-improvement loops to steer the prompt, improve tool/skill use, and improve the ability to draw on memory. Model Releases: Help experiment with and release new models. Research & Analysis: Identify inconsistencies and failure modes in model outputs through well-designed research projects, for both internal and production systems. Knowledge Sharing: Help engineers across teams build intuition for prompt design and context engineering best practices. Staying Current: Track the latest prompting, context engineering, and alignment techniques from industry and academia, and bring the best ideas back to the team. What We're Looking For Required 2 to 10+ years of experience in software engineering or research. Strong background in software engineering fundamentals, and a technical understanding of LLM-driven and agentic systems. Experience shaping LLM behavior through prompts, tool and skill design, or memory systems. Strong written and verbal communication skills, particularly in explaining complex concepts to diverse stakeholders. Nice to have Recent experience working on modern LLM-driven products. Experience working across teams or with ext

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. As a Smart Manufacturing Product Owner at Micron Technology, Inc., you will be responsible to enable innovation and new frontier technology for Smart manufacturing to define, drive and deliver end to end smart manufacturing solution, coordinated across functions of the business. The team will look into applying industry-leading the best methodologies in automation, AI and machine learning to improve Micron’s product development, business and administrative processes across the company. You are joining a team where 'we' matter and hold high standards to achieve perfection. Key Responsibilities Lead the development and implementation of AI-driven Smart Manufacturing solutions to improve product yield, quality, test coverage, and system-level performance across Micron's semiconductor operations. Partner with Test Solutions Engineering, Product Engineering, Global Quality, and multi-functional collaborators to find opportunities and drive digital transformation initiatives. Collaborate with Data Scientists, Machine Learning Engineers, Solution Architects, and Data Engineers to define requirements, prioritize solutions, and deliver end-to-end projects. Translate business needs into detailed business requirements, user stories, acceptance criteria, and data requirements while ensuring alignment with enterprise standards and governance. Develop arguments for proposed solutions, including value quantification, analysis of return on investment and net present value, success metrics, and impl

At Curai, we believe that access to high-quality healthcare is a fundamental human right, not a privilege. Our mission is to radically transform healthcare delivery by harnessing the power of artificial intelligence and clinical expertise to make care more affordable, accessible, and effective for everyone. Patients interact with advanced AI systems at every step of their care and follow-up. Licensed physicians review each case with the patient for the clinical decision in our integrated virtual clinic. We ground our approach in rigorous research, continuous learning, and a deep commitment to clinical integrity. We focus on making a real impact: improving health outcomes, expanding access to care, and setting new standards for what trustworthy, patient-centered healthcare is. Read some of our latest publications. About the Senior Software Engineer, Agentic AI role We are hiring a Full-Stack Senior Software Engineer across a range of seniority levels to push the frontier of agentic / applied AI in healthcare. As a member of the technical staff on the artificial intelligence engineering team, you will design, build, and ship ML and LLM systems (agentic AI workflows) that directly shape how clinicians and patients interact with our platform. You will work end-to-end: framing the problem, exploring data, training and evaluating models, productionizing inference, and measuring real-world clinical and product impact. The bar is high and the surface area is large; we are looking for engineers who want significant ownership and are excited to operate where research meets production. What You'll Do Lead the technical execution of complex AI initiatives, owning the design and delivery of solutions within a product or technical domain while partnering with senior engineers on broader architectural direction. <span style="

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. Job Title: Technical Leadership Plrogram - Member Of Technical Staff – HBM Verification Location: Hyderabad, India Experience : 12&#43; years in Design Verification (experience with Pre-Silicon Verification OR DDR/GDDR/LPDDRmemory/SerDes PHY IP Verification is preferred) Role Description Join the Micron HBM team where you will drive verification architecture for next-generation HBM, ensuring robust methodologies and sign-off strategies. This role is perfect for a hands-on silicon verification expert who is passionate about developing best-in-class verification methodologies, testbench design, AI enabled verification and developing novel solutions to improve quality and efficiency of verification workflows. Key Responsibilities Define and drive verification architecture and methodology for next generation HBM designs. Develop verification plans, coverage strategies, and sign-off criteria. Architect and implement UVM-based testbenches and reusable verification components. Apply Formal Verification techniques for critical Collaborate strictly with build teams to ensure verification completeness and quality. Mentor and guide verification engineers on guidelines and advanced methodologies. Evaluate and integrate AMS Co-Simulation techniques for mixed-signal IP verification. Work closely with EDA vendors to adopt the l

About the Role: We're hiring Senior and Staff Data Platform Engineers to join the Data Infrastructure teams in Toronto. Together these teams own the infrastructure that processes billions of events per day: Spark-on-Kubernetes, Flink and Kinesis pipelines, a multi-petabyte Delta Lake, a large-scale MemoryDB feature store, Databricks multi-environment operations, and the catalog and lifecycle systems that govern it. The team is small and senior. Each engineer owns major platform components: you design it, build it, and support it in production. 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: Spark-on-Kubernetes — EKS-based compute platform for Spark workloads: cluster configuration, Pod Identity IAM, job environment setup, Kustomize overlays, and shadow canary validation Event ingestion — Rust services and Flink jobs processing billions of events per day over Kinesis; throughput, reliability, on-call response, and AI-assisted operational tooling to reduce toil Platform infrastructure — Terraform modules for environment provisioning, cross-account AWS IAM, ARC runner infrastructure, and CI/CD for data platform changes Feature store and ML compute — Flink-based real-time feature pipelines feeding a large-scale MemoryDB cluster; GPU capacity governance and Databricks multi-environment operations for ML training workloads Workflow orchestration and CDC — Airflow-based DAG deployment, change data capture pipeline operations, and data quality monitoring Your Background: 3+ years building and operating production data platform infrastructure at the cluster or platform level, across Spark, Flink, Kinesis, Kubernetes, or equivalent Deep experience in at least one of: Spark-on-K8s cluster operations, Rust-based data or systems engineering, Kubernetes platform engineering and IaC, or data catalog and governance tooling Production AWS experience or equivalent: EKS, S3, Kinesis, and mu

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. As an Industry 4.0 (I4.0) Product Owner at Micron Technology, Inc., you will lead the definition, development, and delivery of end-to-end smart manufacturing solutions to empower Micron Assembly and Test Operation to improve cost, scale, quality and productivity. You will bridge business, engineering, and data science teams to drive Industry 4.0 transformation, leveraging industry best methods, advanced analytics, automation, and AI/ML to optimize planning and manufacturing operations. This role requires deep expertise in I4.0 technologies and strong hands-on data science skills to deliver impactful, scalable solutions across global operations. Key Responsibilities Product Ownership & I4.0 Leadership Define and drive the I4.0 product roadmap, aligning with business objectives and manufacturing strategies. Lead cross-functional teams (engineering, IT, data science, operations) to deliver integrated smart manufacturing solutions. Gather, analyze, and prioritize requirements from end users and stakeholders, develop business cases, validate impact, and propose high-ROI projects for implementation. Understands business problems and effectively translates user requirements into technical specifications—and vice versa—for data science, technical