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Software Product Security Engineer in San Francisco

129 active opportunities · Updated October 2026

Explore current software product security engineer jobs in San Francisco. Filter by work mode, employment type, experience, department, date posted and distance.

SC
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $150K/yr

Quick readStrong listing-quality and freshness signals

About This Role This is not your average Account Executive role. At Sigma, we believe that people are our most valuable resource, and so we relentlessly invest in our team. Account Executives are set up to thrive while generating meaningful pipeline, winning new customers, and directly contributing to the success of our organization. Working with Sigma gives you the opportunity to get in on the ground floor of a high-growth startup. Our Account Executives are crucial for growing our customer base and our company, making this one of Sigma’s most critical roles. Who You Are: A go-getter who is hungry for personal growth and career advancement Someone who understands the power and value of data in driving innovation and business initiatives Someone who is principled, honest, humble, and hard-working What You Care About: Learning from leaders who are dedicated to your success Working in a role you genuinely love with people you enjoy being around Making an impact in the fast-paced world of data Growing your leadership skills for a long and rewarding career You’ll Contribute By: Maintaining, creating, and updating accurate customer, pipeline, and forecast information in Salesforce Using knowledge of the data and analytics space to interact with a diverse set of businesses in consultative sales Owning your sales process — from first call to demo to proposal to proof of concept to contract Working alongside a team of motivated reps on a high-functioning, energetic team Bringing on new customers and developing advocates for Sigma in the business intelligence market Engaging with partners in the data ecosystem to build pipeline or support specific customer needs and initiatives Generating new revenue for a rapidly growing company Your Qualifications: Ideally two or more years of experience closing deals Experience in the data analytics or BI space (Looker, Tableau, Domo, etc.) is preferred Background in high-tech software sales is

PythonSQLAIGo
DU
📍 San Francisco, Canada
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last mile logistics in the long term. If you have a passion for applying robotics solutions in a service used by millions of people, then we want to talk to you! About the Role We are hiring an Autonomy Platform Engineer to build and evolve the foundational software that runs our autonomy stack across robot and compute platforms. The Autonomy Platform team works across embedded Linux, compute and sensor enablement, robotics middleware, process orchestration, data capture and replay, system observability, and performance. You will develop production software and tooling that enables autonomy engineers to bring up new hardware, deploy services reliably, diagnose failures, and validate system performance across robot generations. You will work closely with autonomy, firmware, electrical, hardware, manufacturing, and validation engineers and report to the Autonomy Platform Lead. We expect this role to be hybrid with some time in-office and some time remote. You’re excited about this opportunity because you will… Build and maintain core runtime, middleware, and platform services used by autonomy applications. Enable new compute, camera, lidar, and other sensor platforms. Improve process orchestration, messaging, configuration, startup and shutdown behavior, resource isolation, and fault recovery. Develop system observability, tracing, performance measurement, diagnostics, and regression-detection capabilities. Build reliable data capture, replay, and debugging workflows. Create provisioning, packaging, deployment, integration-test, and platform-readiness tooling. Lead complex debugging across application, middleware, OS, driver, networking, timing, and hardware boundaries. We’re excited about you because… Strong production C++ and Python experience. Experience with embedded Linux, robotics, autonomous vehicles, or complex mechatronic systems. Solid u

PythonGitLinuxC++
SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $134.4K/yr

Quick readStrong listing-quality and freshness signals

At Scale, we believe that the next frontier of artificial intelligence is embodied. The Physical AI team is focused on building general AI that can reason and act in the physical world. By leveraging Scale’s massive, industry-leading data infrastructure, we are partnering with frontier labs to build Foundation Models for Physical AI that will redefine the future of automation. To support our rapid hardware-software iteration cycles and ensure a world-class R&D environment, we are looking for a Safety Coordinator / Lab Lead to anchor our physical testing operations. Role Overview As the Safety Coordinator / Lab Lead , you will play a mission-critical role in scaling our physical testing infrastructure safely and efficiently. This is a high-impact position where your highest-priority responsibility will be owning the end-to-end execution of safety audits and incident documentation . Operating at the intersection of cutting-edge AI foundation models and complex robotics hardware, you will ensure our researchers, engineers, and autonomous systems interact in a secure, compliant, and highly organized environment. Core Responsibilities Priority Focus: Safety Audits & Incident Documentation Rigorous Safety Audits: Design, schedule, and execute routine safety audits across all physical testing environments, robot cells, and hardware workspaces to ensure continuous compliance with internal benchmarks and industrial safety standards. Incident & Near-Miss Documentation: Own the end-to-end incident management pipeline. Act as the primary point of contact for documenting, archiving, and analyzing any lab incidents, mechanical anomalies, or near-misses. Root-Cause Analysis (RCA): Lead structured post-incident investigations to identify systematic risks, authoring comprehensive RCA reports and implementing Corrective and Preventive Actions (CAPA). Data-Driven Risk Mitigation: Treat safety data as a core operational asset—tracking safety metrics and audit trends to proa

AWSRestAIGo
SL
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $110K/yr

Quick readStrong listing-quality and freshness signals

Location - Hybrid This is a hybrid role based out of our San Francisco, Corporate Headquarter office, 3 days in the office, 2 days work from home. About Us Sauce Labs is the world’s largest full-lifecycle, test automation platform, and the company behind Selenium. Trusted by 80% of the world’s top ten largest financial institutions and over 300,000 enterprise users, Sauce Labs provides the only AI platform capable of turning business intent into autonomous testing and quality assurance. With a proprietary dataset of 8.7 billion test runs, Sauce Labs empowers the Fortune 2000 to bridge the gap between AI-driven code generation and enterprise-grade software quality. Learn more at http://saucelabs.com . Release Assurance at the Speed of AI | Meet the new Sauce Labs The Role The Senior GTM Strategy & Planning Analyst will play a key role in supporting go-to-market (GTM) strategy through sales forecasting, churn forecasting, revenue analytics, and capacity planning across the GTM teams. This role will partner closely with Sales, Marketing, Customer Success, and Finance to align GTM initiatives with company growth objectives and contribute to executive-level insights for board presentations. Responsibilities GTM Board Materials: Support preparation of sales forecasting, churn forecasting, and revenue insight materials for executive and board review, ensuring data accuracy and alignment with company strategy. Executive Reporting: Help develop executive-level reporting materials, including presentations that translate complex data into clear, actionable insights. Forecasting: Build and maintain sales forecasting models in partnership with Sales Leadership, modeling pipeline generation, deal velocity, close rates, and other key metrics. Build predictive models to forecast customer churn, leveraging historical data and customer behavior insights to inform retention and renewal strategies. GTM Capacity Planning: Build and maintain capacity models to help ensure GTM t

AIGoRustExcel
DU
📍 San Francisco, Canada· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last mile logistics in the long term. If you have a passion for applying robotics solutions in a service used by millions of people, then we want to talk to you! About the Role We are hiring a Firmware Validation & Integration Engineer for our autonomy software team. This is a critical role to build robust and scalable validation for our firmware and systems to ensure reliability at every level. In this role, you will work with our electrical, firmware, and autonomy engineers to build the infrastructure and test suites required to validate the system. This includes designing and implementing our Hardware-in-the-Loop (HIL) simulation environments and automation frameworks from the ground up. You will report to the Autonomy Platform Lead on our Autonomy Platform Team at DoorDash Labs. We expect this role to be hybrid with some time in-office and some time remote. You’re excited about this opportunity because you will… Play an integral role on a small and focused team. Design and build Hardware-in-the-Loop (HIL) systems to simulate vehicle dynamics and sensor data for comprehensive firmware and system-level validation. Develop automated test infrastructure and software tools to exercise multiple embedded platforms throughout our robot system. Interface many layers of our control system including vehicle controls, power management, and motion control to ensure seamless system integration. Implement low-level test sequences and validation algorithms to safely stress-test vehicle components such as batteries, drive-train, and thermal management devices. Collaborate with cross-functional teams to identify edge cases and hardware-software corner cases that impact vehicle safety and performance. We’re excited about you because… BS/MS degree in Computer Science, Robotics, Electrical Engineering, or related technical field. 5+ years of experience in validati

PythonAWSGitLinux
SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $290.4K/yr

Quick readStrong listing-quality and freshness signals

Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework. Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation. Research and integrate state-of-the-art technologies to optimize our ML system. Ideally you’d have: Passionate about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills to operate in a cross functional team environment. Nice to haves: Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity,

AWSRestAIGo
SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $189.6K/yr

Quick readStrong listing-quality and freshness signals

Scale’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation Research and integrate state-of-the-art technologies to optimize our ML system Ideally you’d have: Strong excitement about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills and the ability to operate in a cross functional team environment Nice to haves: Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the positi

AWSRestAIGo
SL
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $230K/yr

Quick readStrong listing-quality and freshness signals

Location - Hybrid This is a hybrid role based out of our San Francisco, Corporate Headquarter office, 3 days in the office, 2 days remote OR one of our Hub locations, Boston, MA or Raleigh, NC, which means you may be expected to work from a designated co-working space from time to time, and will otherwise work remotely from home, until such time as a dedicated office is established. About Us Sauce Labs is the world’s largest full-lifecycle, test automation platform, and the company behind Selenium. Trusted by 80% of the world’s top ten largest financial institutions and over 300,000 enterprise users, Sauce Labs provides the only AI platform capable of turning business intent into autonomous testing and quality assurance. With a proprietary dataset of 8.7 billion test runs, Sauce Labs empowers the Fortune 2000 to bridge the gap between AI-driven code generation and enterprise-grade software quality. Learn more at http://saucelabs.com . Release Assurance at the Speed of AI | Meet the new Sauce Labs The Role The Senior Director, Growth is an AI-first revenue leader responsible for setting the macro strategy, revenue architecture, and cross-functional alignment of an intelligent, end-to-end pipeline engine. Reporting to executive leadership, this role bridges marketing and sales executive strategy—focusing on expanding our outbound/inbound SDR function, driving predictive pipeline models, and enabling functional marketing leads to scale their teams. Rather than managing day-to-day tactical execution, you will focus on high-level channel architecture, budget optimization, sales leadership alignment, and scaling our revenue operations to maximize global pipeline output. Responsibilities Pipeline Strategy & Executive Revenue Alignment Align on global pipeline target setting, forecasting models, and macro growth strategy across inbound and outbound channels. Champion an agentic AI revenue stack, equipping functional leaders and teams with predictive tools, d

SQLAIGoRust
DU
📍 San Francisco, Canada· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

Role Overview We are seeking a Staff Simulation Engineer to build an end-to-end aerial autonomy simulation stack at DoorDash Labs. This is a highly technical, hands-on leadership role focused on defining and implementing the simulation architecture that underpins autonomy development, validation, CI/CD testing, and pilot training. You will operate as the technical authority for simulation: owning core architecture decisions, developing key components yourself, and setting engineering standards. You will build and mentor a small, high-caliber simulation team while remaining deeply involved in implementation and system design. This role is ideal for someone who has built simulation systems from first principles, understands simulator internals deeply, and is excited to create a world-class platform from scratch. Key Responsibilities Architect and implement an end-to-end simulation stack for aerial autonomy at DoorDash Labs.. Develop high-fidelity simulation capabilities, including: Flight dynamics modeling Contact modeling and constraint handling Sensor and perception simulation Autonomy software-in-the-loop (SITL) integration Design and implement scalable simulation infrastructure to support: Regression testing in CI/CD pipelines Continuous validation of flight autonomy and autopilot software stack Mission-level testing and scenario generation Build cloud-deployed simulation systems to enable large-scale parallel testing and pilot training. Partner closely with autonomy, controls, and aircraft teams to ensure simulation fidelity and validation alignment. Establish technical direction, architecture standards, and performance benchmarks for simulation. Mentor and grow a small team of simulation engineers while remaining deeply hands-on. Required Qualifications Master’s or PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, Aerospace Engineering, or a related field. 10+ years of experience in robotics or physics-based simulation. Deep expe

AWSCI/CDGitRest
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