Software Development Enginner in San Francisco

About VSCO For years, we've helped photographers create their work. Now we're building what comes next. VSCO exists for photographers. Not as a side feature, not as an afterthought, but as the whole point. We build the connected system photographers rely on, and we've spent over a decade earning the trust of a global creative community that takes the craft seriously. Photography is at an inflection point. AI is reshaping what's possible for creative work, and that's where our mission shines. VSCO is building the full photographer's workflow: from creating and editing your work, to delivering it to clients, to running your business. All of it built thoughtfully, with photographers leading the way. We believe the future of photography tools creates more space for creativity, handling the busy work so photographers can focus on the craft. If you care about craft, community, and what technology can unlock for creative people, this is the work. We're a mission-driven and focused company where your work ships quickly, is meaningful, and reaches tens of millions of people worldwide. You'll have a real say in what we build and how we build it. We hire people who don't wait to be asked, naturally connect the dots, care about the quality of what they ship, and believe the best outcomes come from building together. About The Role VSCO is hiring a Senior Software Engineer to be a primary contributor on Reflex, our production GPU image-processing engine, and significantly guide the path it takes into Studio Pro on iOS and macOS. You will deepen a stack that is already in customers’ hands: new capabilities (RAW, large-image export, desktop), production quality (color correctness, memory, performance), and the contracts that let product engineers ship on top of the engine without becoming graphics programmers. In This Role, You Will Be a primary contributor on the Reflex imaging engine: DAG execution, WGSL operators, GPU resource/memory budgets, and color management (linear workin

Senior Software Engineer - Observability and Reliability About the Role We are growing the engineering team and looking for engineers who have the chops to build and deliver world-class technology. You will be part of a talented team of engineers with a shared mission to make data easily accessible. What You Will Be Doing Build observability tools and platforms, including: metrics, logging, distributed tracing, dashboarding, alerting, application performance management Build with modern tools and languages like Go, Open Telemetry and Kubernetes Participate in on-call rotation and ensure uptime of services Create runtime tools/processes that optimize cloud triaging and limit downtime Define best practices around making our systems and services measurable Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies. We expect successful candidates to be coding a majority of their time Qualifications We Need Strong Computer Science fundamentals 5+ years industry experience building and maintaining high-quality software, especially software other engineers use You apply a product mindset to infrastructure systems and feel accomplished enabling others Desire to be a great teammate and have fun at work Strong sense of craftsmanship, and a healthy academic curiosity Qualifications We Want (also, skills you’ll learn!) Experience building systems for data analytics Distributed systems monitoring and profiling skills Knowledge of cloud application security models Administered cloud service infrastructure (GCP, AWS, Azure) Startup experience Additional Job details Additional Job details The base salary range for this position is $170k - $240k annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize e

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability. You will: Own large new areas within our product Work across backend, frontend, and interacting with LLMs and ML models Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly Ideally you'd have: 7+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) 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 position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval

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

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail. What You’ll Do: Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Collaborate with platform, product teams and our customers directly to develop and implement innovative infrastructure that scales to meet evolving needs. Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly What We’re Looking For: 4+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences 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 fo

About the Team DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves — real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs — delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper). We also own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, leading the design and architecture of our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll set technical direction across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability, and mentor engineers as you go. This role is ideal for a senior engineer who enjoys owning ambiguous, high-impact systems and pushing the cost/performance frontier of GPU inference and fine-tuning in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly. You’re excited about this opportunity because you will… Lead the design of infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Own and evolve our open-weights serving stack — real-time GPU endpoints, high-thr

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing pipelines, data structures, and data warehouse architectures; this team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Senior Data Engineer to be a technical powerhouse to help us scale our data infrastructure, automation and tools to meet growing business needs. This is a hybrid position and you must be located in Sunnyvale, San Francisco, or Seattle. You're excited about this opportunity because you will... Work with business partners and stakeholders to understand data requirements Work with engineering, product teams and 3rd parties to collect required data Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Develop and implement data quality checks, conduct QA and implement monitoring routines Improve the reliability and scalability of our ETL processes Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We're excited about you because... 5+ years of professional experience 3+ years experience working in data engineering, business intelligence, or a similar role Proficiency in programming languages such as Python/Java 3+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP Expert in Database fundamentals, SQL and distributed computing 3+ years of experience with the Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink. Experience working with Snowflake, Redshift, PostgreSQL and/or other DBMS platforms Excellent communication skills and experience working with technical and non-tec

About the Team The Spark Platform team owns and operates DoorDash's Apache Spark ecosystem — the execution runtime, remote shuffle service, cluster scheduler, and reliability tooling that powers the company's data, analytics, and ML workloads. We run Spark across the company at significant scale and continue to expand the workloads, capabilities, and consumer base we serve. Orchestrating and operating thousands of Spark cluster deployments is a complex distributed system problem which the team invests heavily in runtime optimization, systems architecture, multi-tenant scheduling, and end-user tooling. About the Role As a Senior Software Engineer on Spark Platform, you will set the technical direction for our in-house Spark deployment and shape the architecture that will run DoorDash's data, analytics, and ML compute for the next five years and beyond. You will own the deep, cross-cutting problems that span the runtime, the shuffle service, the scheduler, and the overall service reliability — making the architectural calls that compound across the platform's lifetime. You will partner with the Engineering Manager on technical roadmap, hiring, and team shape, and act as the senior technical voice in cross-team partnerships with Data Engineering, ML Platform, and product engineering teams that depend on the platform. You must be located in San Francisco, Sunnyvale, Seattle, or New York City for this hybrid position. You will report into the Engineering Manager on our Spark Platform team. You're excited about this opportunity because you will… Set the multi-year technical direction for an in-house Spark-on-Kubernetes platform — runtime, shuffle, scheduler, reliability — and make the architectural calls that compound for years. Own the deepest distributed-systems problems on the team: shuffle architecture, multi-tenant scheduling, runtime performance, and the failure modes that only show up at scale. Partner with the Engineering Manager on technical roadmap, hiring, inte

#TeamNextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors As a Software Engineer at Nextdoor, you’ll join a focused team of developers, product managers, and designers who are passionate about using technology to cultivate a kinder world where everyone has a neighbor they can rely on. We are a small, high performing team of engineers that wear multiple hats and prioritize impact for our customers. We care about moving fast and delivering impact, without compromising on quality and reliability as guided by our Engineering Principles . You will have the opportunity to learn from your co-workers and teach them. As a team, we will make each other better and build great software. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make We believe in empowering our teams to own all aspects of bringing Nextdoor to life. As such, you’ll get the opportunity to make key contributions across our engineering stack - thi