Product Sales in San Francisco

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. SoFi’s Credit team manages credit risk activities for our lending products (Student Loan Refinance, Private Student Loan, Personal Loan, Credit Card, and Mortgage) - including credit strategies/policies for new account origination and portfolio management, collections/recovery strategies and operations, and risk and operational data science and analytics. The team designs data-driven strategies to ensure the growth in lending is consistent with the company’s risk appetite and helps create the products and experiences that put our members’ interests first. The Credit Strategy Lead will work in the Credit team and have responsibilities to analyze and evaluate data to develop and propose value-added credit risk strategies and models for SoFi’s lending products, including Personal Loan, Student Loan Refinance, Private Student Loan, and Credit Card. The Credit Strategy Lead will collaborate with cross-functional teams such as Business Units, Capital Markets, Product and Engineering, and use business knowledge and quantitative and analytical skills to drive revenue, control risk, and provide value to the company and consumers. The ideal candidate will possess a data-driven analytics background and the strategic acumen to direct a function that draws strategic insights from data using database and statistical anal

At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization. As a Staff Android Engineer, on the Rider App group in the Rider org, you will work on one of Lyft’s most critical Rider flows. The Rider App group is responsible not only for the critical flows in the app but also the app platform and quality. We build and iterate on rider facing products that not only ensure a seamless experience for our riders, but also aim to build and deepen Rider-Lyft relationships. As an experienced app developer you will be solving complex problems, delivering significant impact and ensuring excellence for the Rider Android team. This means excellent development practices, scalable and reliable code architecture, and safe, rapid releases. You will not only influence the architecture, platform, processes but also influence the culture and coach, guide engineers across the group. Responsibilities: Work across our product teams to design, build, and release exciting features and products in the Lyft Rider application, used by millions of people every day Define long term roadmap and architecture based on technology and our needs Oversee major changes to our Android architecture Work with Product Managers, Designers, and other Engineers to deliver best in class user experience and collaborate closely with local and global colleagues Continuously discover, evaluate and implement new technologies to maximize developer efficiency Mentor and support other developers on your team with code reviews, design feedback, and advice and guidance Solve complex real-time data transfer and synchronization issues Implement pixel perfect designs with advanced interactions, which are a joy to use Experience: 6+ years of experience as an Android developer Experience with leading a technical team is a bonus Advanced knowledge of Java and Kotlin Familiarity with RxJav

At Qualia, we've built the leading B2B real estate technology that transforms the home buying and selling experience into a simple, secure, and enjoyable process. Our SMB and Enterprise products bring together users from across the real estate ecosystem---homebuyers and sellers, lenders, title and escrow agents, and real estate agents---onto a single shared digital closing platform, providing greater clarity and transparency to real estate transactions. Today, through our business customers across the country, millions of consumers use Qualia to close on homes every year. WHAT YOU'LL WORK ON The FP&A team at Qualia is the analytical engine of the Finance organization. We own the company's planning and forecasting processes, serve as trusted business partners to functional leaders, and produce the financial insights that inform our most important strategic decisions, all in an environment where AI is actively reshaping how we work. As a Senior Manager of FP&A, you will be a central force in shaping how Qualia plans, forecasts, and makes decisions as we scale. You will own high-impact analytical workstreams end-to-end, serve as the go-to financial partner for senior functional leaders, and help set the direction for how the FP&A function evolves, from the models we build to the processes we run to the way we leverage AI to work smarter. This is a high-visibility individual contributor role with direct exposure to executive and C-level audiences. RESPONSIBILITIES Own Qualia's planning and forecasting infrastructure : Lead the design, build, and continuous improvement of our operating model, annual plan, and long-range financial plan, ensuring they accurately reflect the current and future state of the business Drive financial rigor at the executive level: Lead preparation of monthly and quarterly management reporting, Board materials, and investor-facing financial packages; distill complex financial results into clear narratives that drive action at the lea

About Scale AI At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. Reinforcement learning environments are now the center of gravity for that work: the difference between a model that demos well and a model that reliably completes long-horizon work is almost always the quality of the environments and reward signals it was trained against. Responsibilities As a Staff Software Engineer, RL Environments, you'll own the technical foundation for how Scale builds, runs, verifies, and delivers RL environments at scale. An RL environment is a real piece of software: a containerized world with real dependencies, real state, real tools, and a grader that has to be correct even when the agent is creative about breaking it. Building one is a full-stack engineering problem. Building thousands of them reproducibly, cheaply, with trustworthy reward signals and throughput measured in millions of rollouts is a systems problem that very few people have solved. You'll work on both. You'll design the platform: sandboxed execution, environment packaging and versioning, rollout orchestration, trajectory capture, verifier frameworks, and the authoring surfaces that let engineers and domain experts produce environments without reinventing infrastructure each time. And you'll go deep on the environments themselves by instrumenting real applications, designing task suites that expose specific capability gaps, and building graders that

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborate with cross-functional teams to define, design, and deliver new features. Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. Present technical information to teams and stakeholders, providing

About Scale AI At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI) and building upon our prior model evaluation work with enterprise customers and governments to deepen our capabilities and offerings for public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we produce is some of the most critical work for how humanity will interact with AI. About Our FDE Team Generating high-quality data is the core problem our business solves. We aim to make producing and delivering high-quality data seamless and efficient for operators and customers. Our Team is building customer and operator-specific infrastructure to provide high-quality data with low turnaround time. You'll be exposed to the cutting edge of the Generative AI industry while directly interfacing with the leading model-building organizations in the space, including the top AI research labs and government agencies. Join us in shaping the future of Artificial General Intelligence. As a Forward Deployed Engineer, you'll be at the forefront of providing the critical data infrastructure that powers the most advanced AI models, directly influencing how humanity interacts with AI. You will work with the world’s leading AI companies and government agencies to solve their most complex AI data-related problems. Responsibilities: Drive Impact: Directly contribute to the advancement of AI by delivering critical data solutions for leading AI innovators and

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Discord has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there’s one thing that nearly everyone does: play video games. Discord plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games. We're looking for someone who gets excited about building data infrastructure at massive scale and cares deeply about the gaming communities we serve. Someone with passion for building lovable products for Discord users and Discord engineers. We're building the next generation Data Platform that powers decisions for one of the most vibrant platforms in the world. If you're the kind of Staff Engineer who sees ambiguity as an invitation — who builds systems that make whole teams faster, shapes technical strategy across the org, and wants your decisions to directly impact millions of gamers worldwide — we want to talk to you. To learn more about Discord's Data Platform, read our engineering blog, including how we built our modern data stack leveraging open-source tools! This position is based in our San Francisco office. What You'll Be Doing Own the technical direction of major Data Platform initiatives like GRC, scaling, or stream processing, from problem to production system and post-launch health Be a force multiplier: build reusable primitives, unblock teammates, and raise the quality bar across the team Stay a top code contributor. You write real production code while helping others reach the same bar Partner with XFN stakeholders to translate business problems into clear technical strategy Champion debate, decide, and commit and 80/20 thinking to drive robust technical solutions supporting multiple team What you should have 7+ years of software engineering experience with a track record of driving large, ambiguous technical initiatives end-to-end Expertise in distributed systems and data infrastructu

About the Role As the Fleet Coordinator, you will be the single source of truth for the fleet: tracking what configuration each aircraft is flying and where it is, with no aircraft cleared to fly outside its approved configuration.You'll oversee all aircraft configuration that supports engineering and Part 135 operations, while keeping aircraft audit-ready. You will play a key role in supporting safe, compliant, and reliable operations by dispatching aircraft, tracking configuration and compliance records, and acting as the connective tissue between engineering, operations, maintenance control, and the FAA. You're excited about this opportunity because... Fleet Configuration & Testing: Maintain and verify compliance across the Part 107 test and Part 135 Commercial aircraft inventory: registration, airworthiness status, maintenance logs, and battery/component life-cycling." Maintain accurate software, hardware, and firmware configuration records for every aircraft, including designated testing candidates, so results are always traceable to a known config. Track aircraft location across the fleet ensuring one hundred percent accountability. Initiate and track parts requests tied to configuration changes, testing, and scheduled maintenance. Operations & Compliance: Maintain OpSpecs and the general maintenance manual, ensuring maintenance procedures and standards align with Part 135 requirements. Maintain the maintenance, training, and flight-log records the FAA expects an air carrier to produce on demand. Act as point of contact during FAA audits, representing the accuracy of aircraft configuration records and documentation against the maintenance program's compliance requirements. Fleet Dispatch & Availability: Decide which aircraft flies which mission (dispatch-style), verifying maintenance status before an aircraft is released. Track each aircraft's real-time location and availability, including movements between bases, hangars, and maintenance fac

As a member of our Frontier Tech Consultant team, you will play a critical role in advancing cutting-edge AI innovations by conducting high-impact experiments and ensuring seamless execution at the highest quality standards. Your work will directly contribute to Scale AI’s growth, shaping the future of artificial intelligence. In this role, you will be working on various types of projects, including but not limited to: research experiments, dataset generation, data quality improvements, and in-depth technical analysis. You will tackle complex, technical and operational challenges while collaborating closely with Scale’s ML research scientists and SPM team. The ideal candidate is analytical, detail-oriented, and results-driven, with strong problem-solving abilities and excellent communication skills. We are looking for someone who thrives in a fast-paced environment, is proactive in overcoming challenges, and is committed to delivering exceptional outcomes. If you are eager to contribute to the forefront of AI innovation, we encourage you to apply. You will be responsible for: Design and execute research experiments Build and evaluate frontier LLM datasets Develop training and testing material for frontier pipelines Improve quality of existing and new products Ideally you’d have: Strong machine learning knowledge, either by being in the final years of a ML PhD career or having already graduated Strong writing and verbal communication skills An action-oriented mindset that balances creative problem solving with the scrappiness to ultimately deliver results Analytical, planning, and process improvement capability Experience working in a fast-paced, entrepreneurial environment Technical skills including familiarity with Python, GPU, AWS, API, LLM, ML, and SQL Pay: $60-80/hr Commitment: This is a fully remote, US-based part-time (10-20 hours per week), on-going contract position staffed via HireArt. HireArt values diversity and is an Equal Opportunity E

Scale Labs, Research Scientist — Safety Post Training As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Safety Post-Training you will develop and apply post-training methods and interpretability techniques to make frontier AI systems safer, and better understood by researchers and policymakers.. For example, you might: Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment properties; Develop interpretability-informed evaluations that reveal how and why models produce unsafe, deceptive, or otherwise undesirable behaviors, and use those insights to guide targeted mitigations; Collaborate with policymakers, engineers, and other researchers to translate post-training and interpretability findings into actionable safety standards, evaluation benchmarks, and best practices. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches. A track record of published research in machine learning, particularly in generati