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Location: San Francisco, CA | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations. Our engineers are extremely high leverage: we simultaneously drive multiple major revenue streams while optimizing one of Anthropic's most precious resources: compute. As we expand to more cloud platforms, the complexity of managing inference efficiently across providers with different hardware, networking stacks, and operational models grows significantly. We need product-minded backend engineers who can navigate these platform differences, design the services and abstractions that work across providers, and make architectural decisions that keep us reliable and cost-effective at massive scale. Your work will increase the scale at which our services operate, accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms, and ensure our LLMs meet rigorous safety, performance, and security standards. Key responsibilities Design, build, and own backend services and infrastructure that serve Claude across multiple CSPs, accounting for differences in compute hardware, networking, APIs, and operational models Work cross-functionally with internal inference, product API, systems, and security teams, among others, and with CSP partners to stand up the full serving stack on new cloud platforms, resolve operational issues, and influence provider roadmaps Build and evolve CI/CD automation systems, including validation and deployment pipelines, that reliably ship new model versions to millions of users across cloud platforms without regressions Design interfaces and tooling abstractions across CSPs that enable cost-effective inference management, scale across providers, and reduce per-platform complexity Contribute to capacity planning, autoscaling, and workload routing strategies that match supply with demand and direct requests to the most cost-effective accelerator and region Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads Minimum qualifications Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration Are curious about LLM serving; prior inference or ML experience is not required Thrive in cross-functional collaboration with both internal teams and external partners Have experience working with external partners to align goals and deliver impact Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description Preferred qualifications Direct experience working with CSPs to scale infrastructure or products across multiple platforms, navigating differences in networking, security, privacy, billing, and managed service offerings Hands-on experience with capacity management, cost optimization, or resource planning at scale across heterogeneous environments Solid understanding of multi-region deployments, geographic routing, and global traffic management Proficiency in Python or Rust The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations. Within Cloud Inference, the model & inference launch team owns the validation pipeline for our inference server and load balancer on these platforms. We're responsible for every inference change — model launches, performance improvements, safeguard integrations — landing on cloud platforms with correctness, performance, and reliability intact. This is high-leverage infrastructure work: validation has to be fast and cheap enough to run on the same accelerators that serve customers, trustworthy enough to replace manual checks, and consistent enough that a change working on Anthropic first-party means it works everywhere. This directly determines how fast frontier models and features ship to every cloud platform, and how quickly performance wins reach production — reclaiming capacity at a time when compute is our scarcest resource. Key responsibilities Be on the critical path for frontier model launches, bringing up inference for new model architectures and shipping them to cloud platforms in lockstep with our first-party platform Work with the core inference team to bring new inference features (e.g. structured sampling, prompt caching, and more) to cloud platforms, owning the platform-specific integration that gets them to production Identify and dive deep on the gaps that make inference behave differently across first-party and CSPs — config drift, observability, deployment patterns, hard cross-platform bugs — and fix them at the source rather than building platform-specific workarounds Design, build, and own the CI/CD infrastructure for the inference server and load balancer across cloud platforms, with shadow traffic, performance baselines (throughput and latency), and correctness checks that catch regressions before production Drive down merge-to-production cycle time by making validation faster, more parallel, and cost-effective enough to run on the same constrained accelerator pool that serves customers, without trading away reliability Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads Minimum qualifications Have a strong interest in LLM serving; prior inference or ML experience is not required Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users Have a track record of building automation or test infrastructure that measurably improved release velocity or reliability Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration Thrive in cross-functional collaboration with both internal teams and external partners Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description Preferred qualifications LLM inference optimization, batching, and caching strategies Capacity-constrained scheduling or shared-resource test infrastructure Solid understanding of multi-region deployments, request routing, load balancing, global traffic management Working with CSP partner teams to scale infrastructure across multiple platforms, navigating differences in networking, security, privacy, and managed service Proficiency in Python or Rust The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: New York City, NY; San Francisco, CA; Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Our Inference team is responsible for building and scaling the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. Key responsibilities Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide Develop resilient, flexible systems that adapt in real time to real world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators and multiple cloud providers Maximize compute efficiency and optimize cost across the fleet by autoscaling and orchestrating production, research, and experimental workloads across multiple cloud providers Build and operate production-grade deployment pipelines for releasing new models to users Provide high-performance inference infrastructure that enables researchers to develop next-generation models Integrate new AI accelerator platforms and support inference for new model architectures Minimum qualifications Significant software engineering experience, particularly with distributed systems Results-oriented, with a bias towards flexibility and impact Willingness to pick up slack, even if it goes outside your job description Desire to learn more about machine learning systems and infrastructure Thrive in environments where technical excellence directly drives both business results and research breakthroughs Care about the societal impacts of your work Preferred qualifications Experience with high-performance, large-scale distributed systems Experience implementing and deploying machine learning systems at scale Experience with load balancing, request routing, or traffic management systems Familiarity with LLM inference optimization, batching, and caching strategies Experience with Kubernetes and cloud infrastructure (AWS, GCP, Azure) Proficiency in Python or Rust Representative projects Designing intelligent routing algorithms that optimize request distribution across many accelerators in different environments Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads Building production-grade deployment pipelines for releasing new models to millions of users reliably Contributing to new inference features Supporting inference for new model architectures Analyzing observability data to tune performance based on real-world production workloads Managing multi-region deployments and geographic routing for global customers The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: United States Workplace: Remote About Cantina: Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning. If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future! About the Role: Cantina is a place where people create AI characters and the videos those characters star in, and the catalog grows far faster than anyone can browse. Search and recommendations are what turn that catalog into a product: they decide which characters a new user meets in their first minute, which creators get discovered, and what appears in every feed, leaderboard, and discovery surface we ship. We are hiring a Senior Staff Software Engineer to own that area end to end — retrieval, ranking, relevance quality, and the roadmap for all three. This is the first dedicated hire for search and recommendations, so you will inherit a real production system serving live traffic along with a large amount of unclaimed ground, and you will set the technical direction rather than execute someone else’s. What you'll do: - Own the architecture and roadmap for search and recommendations end to end — query understanding, retrieval, ranking, and the surfaces they feed: search, discovery, the home feed, and our trending and creator leaderboards. - Make relevance a measured discipline rather than an opinion: define the quality metrics per surface, build the offline evaluation and golden-set tooling, and run the online experiments that decide whether a ranking change ships. - Design and evolve the ranking stack — engagement signal pipelines, decay and freshness models, and the pattern we use to combine pre-computed index-time signals with live re-ranking at query time. - Own OpenSearch in production: index and mapping design, reindex and cutover safety, query performance, cost, and the operational headroom of the clusters behind every discovery surface. - Build candidate generation and personalization for recommendation surfaces, and partner with data and ML on the feature pipelines and models behind them. - Work directly with Product and Trust & Safety on what “good” means for each surface — quality gates, cold-start behavior for brand-new creators and characters, and what must never be recommended. - Set the engineering standard for the area: instrumentation, flag-gated rollouts, and runbooks that let other teams change ranking behavior without breaking it. - Act as the technical point of contact for discovery across backend teams, and mentor the engineers whose work touches it. What you'll bring: - 10+ years building production software, with substantial depth in search, ranking, recommendations, or ML-driven relevance on a consumer-scale product. - Hands-on expertise with a production search engine — OpenSearch, Elasticsearch, Lucene, Vespa, or similar — covering index and analyzer design, relevance tuning, and operating the cluster, not only querying it. - A rigorous approach to relevance measurement: you have owned offline evaluation, golden sets, and A/B or interleaving frameworks, and you can explain what moved a metric and why. - Fluency across the recommender stack — candidate generation, feature pipelines, embedding retrieval, re-ranking — and a working understanding of the serving constraints that make an offline win fail online. - Strong distributed systems and backend fundamentals, with production experience in Go or a comparable systems language, and comfort in the data layer behind it (SQL warehouses, streaming and batch pipelines). - Demonstrated ownership of an ambiguous area: you have picked up something with no dedicated owner, decided what mattered, and can show the result. - Clear written communication and the judgment to work with Product on real tradeoffs between relevance, freshness, safety, and latency. - Preferred: experience with AI-generated or rapidly growing content catalogs, severe cold-start conditions, or ranking under trust-and-safety constraints. Compensation: The anticipated annual base salary range for this role is between $250,000 - $320,000 (USD). When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.   Benefits: - Competitive salary and generous company equity - Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina - 42 days of paid time off, including: - 15 PTO days - 10 sick days - 15 company holidays - 2 floating holidays - Generous parental leave & fertility support - 401(k) retirement savings plan - Lifestyle spending account – $500/month to use however you’d like - Complimentary lunch and snacks for in-office employees - One Medical membership, and more!

Location: United States Our client is hiring a Staff-level engineer to lead a highly specialized team building cutting-edge, high-throughput signal processing systems that turn raw satellite radar data into SAR imagery, deployed on the ground and potentially on board spacecraft. Fully remote from the US; optional relocation to Vancouver later. What you will do • Lead the definition, specification, technical risk management, integration, verification and validation of SAR processors, new and existing • Supervise interface control document development; ensure hardware and software components integrate into the larger ground or space segment • Coordinate trade-offs between theoretical algorithms and their implementation on the actual processor • Troubleshoot root causes of processing errors and artefacts in image products and find mitigations; optimize processing time toward near-real-time • Take part in mission design trade-off studies; mentor the team; advise senior management and new business pursuits What you need • Degree in Electrical Engineering, Engineering Physics, Math or Physics (or equivalent) • 12+ years in an engineering environment, including 5+ years on complex signal processing systems (radar, medical imaging, computer vision or similar) and 10+ years in a large product development or systems engineering environment • Solid grounding in high-speed, high-throughput data analysis and transmission design • MATLAB, Python or C++ • Clear communicator to technical, sales, executive and customer audiences • US citizen or permanent resident Nice to have : SAR remote sensing (system design, operation, exploitation, calibration); satellite SAR payload design and operations; FPGA or ASIC based system design; geospatial data.

Компания Shopify, специализирующаяся на электронной коммерции и предоставляющая решения для создания и управления интернет-магазинами, ищет опытного Product Manager уровня Staff или Senior Staff. В обязанности входит руководство продуктовой стратегией и развитие платформы, ориентированной на поддержку бизнеса и частных лиц в онлайн-продажах. Кандидат должен обладать глубокими знаниями в области управления продуктами и опытом работы на аналогичной позиции.

Location: United States Our client, a global leader in Earth-observation satellites, is hiring a Staff Systems Engineer for its Synthetic Aperture Radar (SAR) missions. Fully remote from the US is fine for the first couple of years; relocation to the Vancouver, BC area later is optional, not required. What you will do • End-to-end oversight of SAR engineering across the full lifecycle of a SAR space mission • Own the mission concept of operations and high-level mission specs, including spacecraft budgets that drive the SAR payload • Lead technical solutions for current and future SAR missions: beam mode design, mission concept design, SAR image quality modelling • Lead mission-level risk management, integration, verification and validation • Run design trade-offs across spacecraft systems, coverage and access, SAR payload, SAR processor and end-user applications • Own the SAR side of commissioning, calibration and early operations • Advise senior management and new business; mentor the team What you need • Graduate degree in Electrical Engineering, Engineering Physics, Math or Physics (or equivalent experience) • 15+ years with radar, SAR or similar active imaging systems (hardware, processors and/or data products) • 10+ years in a space systems engineering or similar complex systems environment • SAR remote sensing experience: system design, operation, applications/exploitation and/or calibration • Strong communicator across technical, sales, executive and customer audiences • US citizen or permanent resident (export-control and Controlled Goods requirements) Nice to have : MATLAB, Python; satellite SAR payload design and operations; space mission design (coverage and access, orbital dynamics); spacecraft design (thermal, power, pointing); geospatial data.

Компания Vinted ищет Staff Product Designer для работы над продуктом Marketplace в Амстердаме и Берлине. В обязанности входит разработка и улучшение пользовательского опыта на платформе, которая объединяет миллионы пользователей в более чем 20 странах. Предлагается гибридный формат работы, сочетающий удалённую и офисную занятость. Кандидат должен обладать опытом в дизайне продуктов, ориентированных на онлайн-торговлю и маркетплейсы, а также уметь работать в международной команде.

As Staff Product Manager for Pricing, you will own the strategy and roadmap for how Xometry prices and evaluates manufacturability across the EMEA region — a technical, cross-functional, high-ownership role at the intersection of pricing strategy, manufacturing domain expertise, and applied AI.

Build the execution engine: Design, implement, test, and support query operators, expression evaluation, execution scheduling, runtime planning, and resource management. Improve runtime performance: Optimize vectorized processing, concurrency, parallelism, memory usage, data exchange, and disk spilling.

Location: Colombia Paired is a global staffing and recruiting agency that pairs remote work with top-tier talent. We help individuals from around the world connect with great companies that are looking for their specific skill set. Our mission is to provide great jobs to talented people, no matter where they are located. About the role Staff Accountant We are hiring on behalf of a fast-growing DTC men's apparel brand doing over $10M per month in revenue. Comfort-first, performance-minded basics: shorts, tees, hoodies, pants. California-rooted, 100% bootstrapped, running on Shopify with paid Meta as the growth engine. The Role This is not a back-office job. This is the financial nerve center of a fast-moving DTC operation. You will own the daily accounting engine covering AP, receiving reconciliation, vendor accounts, and COGS accuracy. Then you will do what most accountants cannot: turn those numbers into answers. Which SKUs are printing money and which are dead weight? Which vendors are quietly bleeding the company on variances? You will work directly with ownership. No layers, no bureaucracy. Ownership handles month-end close and the big strategic calls. You run the daily operation, surface what matters, and bring analysis sharp enough to change decisions. When you find something, it gets acted on that day. If you have ever caught a six-figure error nobody else saw, or built the analysis that killed a bad product line, this is your room. What You'll Own Accounts Payable, full cycle Process, code, and schedule vendor invoices across the full supplier base Execute 3-way matching (PO, receiving report, invoice) on every inbound shipment Run payment cycles, track terms, and capture early-pay discounts Resolve discrepancies directly with vendors Receiving and Inventory Accuracy Daily reconciliation of invoiced quantities against goods actually received Catch short ships, production variances, and pricing errors before they become write-offs Partner with fulfillment leadership to keep receiving documentation airtight COGS and Unit Economics Maintain weighted average cost accuracy across roughly 1,300 SKUs Reconcile landed costs including freight, duties, and inbound charges into true unit economics Support monthly COGS true-ups and inventory valuation reviews Vendor Management Own vendor account reconciliations, statement reviews, and terms compliance First line on anything billing-related with the supplier network Track vendor performance: variance rates, pricing drift, chargeback recovery Analysis Blended and category-level gross margin tracking SKU contribution, velocity, and markdown exposure across 1,300 SKUs Vendor scorecards on cost, accuracy, and reliability Ad hoc deep-dives for ownership: spend reviews, pricing scenarios, whatever needs answering that week Requirements Requirements 3 to 6 years in accounting or accounting plus FP&A, with real inventory, AP, or cost accounting exposure. Apparel, CPG, or DTC ecommerce strongly preferred Fluent in 3-way matching and comfortable pushing back on vendors when the numbers do not add up Excel killer: pivots, lookups, and models built from scratch You think in unit economics, not just journal entries ERP experience such as NetSuite, QuickBooks, or similar. Shopify ecosystem familiarity is a plus Self-directed and fast Benefits Work From Anywhere Competitive salary paid in US$

We are looking for a Staff Compensation & Data Analyst (IC4) to serve as the subject matter expert at the intersection of quantitative analysis, compensation strategy, HR technology, and AI-assisted analytics.

About this role As the Senior Staff Machine Learning Platform Engineer, you will own the technical vision and evolution of Faire’s ML platform. You will set standards, influence org-wide architecture, and lead complex, cross-functional initiatives that unlock data science velocity at scale. This role will also be key to adapting ML workflows to take advantage of modern AI productivity tools. You won’t just build models, you will architect the systems that allow those models to help tens of thousands of small retailers compete and grow their local businesses. What You Will Do: — Define and drive the long-term architecture of Faire’s ML platform including training, inference, feature management, governance — Establish company-wide standards for code quality, testing, MLOps (CI/CD), experimentation, model lifecycle management, and observability — Lead adoption and advanced use of Unity Catalog, multi-workspace strategies, and data/ML mesh patterns — Architect highly scalable ML workflows using Spark, Delta Lake, and MLflow — Optimize performance, reliability, and cost of the ML platform — Evaluate and integrate emerging Databricks features — Stay ahead of the curve by engaging with the latest developments in machine learning and AI — Serve as senior ML technical advisor to Faire’s data science and production engineering teams — Represent Faire at ML conferences and meetups — Mentor ML engineers and raise the overall bar for Machine Learning at Faire What it takes: — 10-12 years of experience building and improving large-scale ML or data platforms — A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field — Deep expertise in Databricks lakehouse architecture, including governance via Unity catalog, orchestration via Workflows, and cost optimization — Proven ability to design systems that support multiple data science teams and production workloads — Strong background in distributed systems, ML infrastructure, and cloud architecture — Demonstrated technical leadership across teams and orgs; ability to influence without authority — Experience integrating LLM workflows into enterprise platforms is a plus — Previous contributions to open source ML Infrastructure projects or research publications is a very strong plus Tech Stack: Faire uses a modern cloud based tech stack. For this role, you’ll want to be proficient with the following: — Languages: Python, SQL, Kotlin — ML Frameworks: PyTorch, PySpark, MLFlow — Big Data & Processing: Spark, Kafka, Databricks, Snowflake, Fivetran, Iceberg, Unity Catalog, Datadog, Airflow, Cockroach DB, MySQL — Cloud & Infrastructure: AWS, S3, SageMaker, Kubernetes, Docker, GitHub Actions, Terraform — Generative AI: Claude Sonnet 4.5, ChatGPT 5.2 Conditions: Hybrid work format with office presence 3 days per week (Tuesdays, Thursdays, and a flex day) and flexibility to work remotely up to 4 weeks per year. Remote work possible for candidates located in Ontario, Canada. Salary Range: $248,000 to $341,000 per year, eligible for equity and benefits. Actual base pay depends on skills, experience, market demands, and location. Base pay range subject to change.

Location: Foster City, CA Workplace: Hybrid Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. ABOUT THE ROLE: Help turn “I built a business” into “I have customers.” As a Staff Software Engineer on Replit’s Money team, you’ll help shape Agentic Ads: an emerging area focused on using AI to make customer acquisition more accessible to businesses built on Replit.   This role focuses on intelligent, advertiser-facing software—not ad-serving infrastructure, an ad exchange, or a real-time bidding engine. You’ll tackle problems at the intersection of AI, business growth, measurement, and trustworthy automation, turning complex decisions into clear, useful experiences.   You’ll help define a new product area, working closely with product, design, and engineering to discover customer needs and deliver practical solutions. This is a hands-on Staff role: you’ll own architecture, lead delivery across teams, mentor engineers, and turn an ambitious vision into incremental customer value. YOU WILL: - Set technical direction for Agentic Ads, translating customer needs into an architecture and roadmap that balance rapid learning with long-term reliability. - Build agent-powered experiences that help businesses make informed growth decisions, translating user goals into understandable recommendations and appropriately authorized actions. - Design extensible integrations with external services, using well-defined APIs and abstractions that accommodate changing provider capabilities and requirements. - Partner with product and data teams to establish reliable measurement, connect product activity to business outcomes, and address data quality, delayed feedback, and uncertainty. - Develop intelligent automation that learns from performance signals and helps users improve outcomes within their goals and constraints. - Make financial control a product requirement: scoped authorization, explicit approvals, budget limits, auditable decisions, clear reporting, and reliable pause controls. Distinguish recommendations from actions that commit customer spend. - Make cross-platform workflows reliable with durable state, idempotency, safe retries, reconciliation, observability, and recovery from partial failures, expired credentials, rate limits, and provider API changes. - Establish agent evaluations and production monitoring for plan quality, tool selection, policy compliance, spend safety, and verified execution. Partner on experiments that distinguish attributed results from incremental customer value. - Lead ambiguous initiatives across product, design, AI, data, security, and partnerships. Stay hands-on with implementation, define incremental milestones, mentor engineers, and own the quality and operation of what the team ships. REQUIRED SKILLS AND EXPERIENCE: - A track record of Staff-level technical leadership on complex customer-facing products or platforms: setting direction, resolving ambiguity, and delivering through launch and production operation across multiple teams. - Strong hands-on software engineering and system design skills across APIs, data modeling, distributed systems, asynchronous workflows, and customer-facing product experiences. - Experience building and operating third-party integrations that remain correct under duplicate requests, partial failures, rate limits, changing schemas, and inconsistent external state. - Practical experience shipping LLM-powered products or agentic workflows, including tool use, orchestration, evaluations, and safeguards for actions taken against external systems. - Strong data and measurement judgment: experience using instrumentation and experiments to evaluate product outcomes, and the ability to reason about noisy data, delayed feedback, uncertainty, and correlation versus causation. - Sound judgment around systems that act on a user’s behalf, including authentication, authorization, sensitive data, approval boundaries, and limits on consequential actions. - Demonstrated ability to align cross-functional teams, explain technical trade-offs, mentor engineers, and drive execution without relying on reporting authority. - A product-minded approach to simplifying complex workflows for non-experts, with hands-on ownership from prototype through reliable production operation. PREFERRED QUALIFICATIONS - Experience building advertiser-facing products, marketing automation, campaign-management tools, growth platforms, or software that helps businesses acquire customers. - Experience integrating advertising or marketing APIs; familiarity with account onboarding, campaign lifecycles, and platform requirements. - Working knowledge of conversion tracking, attribution, customer acquisition cost, return on ad spend, budget pacing, and the limits of optimizing with low conversion volume. - Experience with experimentation, incrementality measurement, constrained optimization, recommendation systems, or decision-making under uncertainty. - Experience building permissioned, multi-tenant products with approval workflows, budget controls, audit trails, and privacy-aware handling of customer and conversion data.   BONUS POINTS: - Experience with agent tooling, durable workflow execution, delegated authorization, or evaluation frameworks for agents that take consequential actions. - Experience connecting application events or server-side conversion signals to advertising platforms, or integrating creative generation and landing-page experimentation into growth workflows. - Experience building for small businesses or first-time advertisers, where clear guidance, limited budgets, and sparse data shape the product. - These are additional strengths, not a checklist. Experience with every ad platform is not expected; ad-serving infrastructure experience and an ML research background are not prerequisites. WHAT WE VALUE: - Customer outcomes: success means helping a business acquire qualified leads and customers—not merely connecting an account, launching a campaign, or increasing spend. - User control and trust: agents explain recommendations, act within explicit authority, and make budgets, costs, and consequential changes understandable. - Evidence over activity: we validate measurement, acknowledge uncertainty, and test whether a change improves business outcomes rather than treating attribution as proof of causality. - End-to-end ownership: we own the journey from a business goal through campaign execution, measurement, and ongoing improvement. - Pragmatic technical leadership: we build on existing ad platforms, ship focused increments, and invest in correctness and extensibility where they matter. - Clear collaboration: we document decisions, surface risks early, and help other teams and partners succeed. Full-Time Employee Benefits Include: 💰 Competitive Salary & Equity 💹 401(k) Program with a 4% match (US Only) ⚕️ Health, Dental, Vision and Life Insurance 🩼 Short Term and Long Term Disability 🚼 Paid Parental, Medical, Caregiver Leave 🏝 Flexible Time Off (FTO) + Holidays 🚗 Commuter Benefits (In-Office & US Only) 📱 Monthly Wellness Stipend 🧑‍💻 Autonomous Work Environment 🖥 In Office Set-Up Reimbursement (In-Office Only) 🚀 Quarterly Team Gatherings ☕ In Office Amenities (In-Office Only) Want to learn more about what we are up to? - Self-driving Company https://replit.com/blog/self-driving-company - Replit Agent at Scale https://replit.com/blog/evaluating-and-improving-agent-at-scale - AI Adoption https://replit.com/blog/ai-adoption - Build Open-Source Apps https://replit.com/build/open-source-app-builder   Interviewing + Culture at Replit - Operating Principles https://blog.replit.com/operating-principles - Reasons not to work at Replit https://blog.replit.com/reasons-not-to-join-replit To achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.

Location: United States of America What We Do: Cybercrime is growing, and more businesses are getting hit by threats that used to target only the biggest organizations. That pushes defenders like us to operate at the highest level, and it deepens our need for good people who want to make a meaningful impact. Founded in 2015 by former NSA cyber operators, Huntress is a remote-first team working to make enterprise-grade cybersecurity accessible to businesses of all sizes. We work closely with security teams and service providers protecting complex environments, often without the time or headcount to handle it all. That’s why we build our technology in-house and back it with a 24/7 human-led Security Operations Center (SOC). As a result, our platform is never disconnected from the experts who manage it, ensuring our customers' protection. Huntress now secures more than 6M endpoints and 16M identities worldwide. Those numbers keep growing because more businesses rely on us to help carry the load and operate with more confidence. Every day, you can see that commitment in how we stand with our customers and how we show up for each other. Reports to: Engineering Manager Location: Remote US Compensation Range: $200,000 to $220,000 base plus bonus and equity What You’ll Do: Huntress is looking for a highly strategic and collaborative Staff Software Engineer to drive the technical vision and architectural evolution of the Huntress Core Platform. Our Core Platform contains the foundational components that power the entire Huntress product suite, including the notification system, onboarding, authentication, integrations, and APIs. While you will remain deeply hands-on developing the most complex features for the platform, your scope expands beyond standard delivery. You will act as the technical anchor for your team, solving our most complex scaling challenges and eliminating cross-team dependencies. You will design the systems that empower all other engineering teams to build faster and more securely, acting as a technical thought leader who ensures our architecture anticipates future growth as we scale to protect the 99% . Responsibilities: Design, implement and mentor engineers on the most complex features the team builds Partner directly with the Engineering Manager to steer the team’s technical direction, improve overall team function, and set the standard for engineering excellence Take ownership of cross-team dependencies, actively collaborating with multiple engineering teams to eliminate roadblocks and ensure smooth feature delivery. Drive the Architectural Decision Record (ADR) process for major technical changes that impact the wider codebase or require alignment across multiple functions Focus on the entire lifecycle of the system, including evolution, configuration and technical risk management Mentor and coach engineers across the team, acting as a positive role model who promotes collaboration and engagement What You Bring To The Team: 10+ years of experience developing complex software products, with a proven track record of acting as the senior technical anchor for a team 5+ years of programming in Ruby on Rails, ideally with experience managing and scaling large monoliths Strong architectural experience, including a history of driving technical design decisions (ADRs) and managing system lifecycles, configuration and technical risk Experience with AWS or other public cloud environments, Linux-based infrastructure and advanced database management at scale Excellent technical, diagnostic, and troubleshooting skills Ability to grasp new tools and technologies quickly Ability to prioritize and execute multiple tasks at a time in a fast-paced environment, often operating independently Demonstrated ability to take highly ambiguous requirements or multi-team initiatives and decompose them into actionable work for the team Exceptional communication skills, with the ability to build strong relationships and coordinate smoothly across multiple teams, product managers, and leadership Experience partnering directly with Engineering Managers or Product Leaders to set team-level technical strategy and balance tech debt with product delivery Experience with AI coding tools and workflows, with the ability to help the wider team adopt them effectively, responsibly, and pragmatically What We Offer: 100% remote work environment - since our founding in 2015 Generous paid time off policy, including vacation, sick time, and paid holidays 12 weeks of paid parental leave Highly competitive and comprehensive medical, dental, and vision benefits plans 401(k) with a 5% contribution regardless of employee contribution Life and Disability insurance plans Stock options for all full-time employees One-time $500 reimbursement for building/upgrading home office Annual allowance for education and professional development assistance $75 USD/month digital reimbursement Access to the BetterUp platform for coaching, personal, and professional growth Huntress is committed to creating a culture of inclusivity where every single member of our team is valued, has a voice, and is empowered to come to work every day just as they are. We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, disability, veteran status, genetic information, marital status, or any other legally protected status. We do discriminate against hackers who try to exploit businesses of all sizes. Accommodations: If you require reasonable accommodation to complete this application, interview, or pre-employment testing or participate in the employee selection process, please direct your inquiries to accommodations@huntresslabs.com . Please note that non-accommodation requests to this inbox will not receive a response. Huntress uses artificial intelligence tools to assist in reviewing and evaluating job applications, including resume screening, skills assessment, and candidate matching and comparisons. These AI tools support our human recruiters in the initial review process, but do not make final hiring decisions without human involvement. By submitting your application, you acknowledge this use of AI in our recruitment process. Please review our Candidate Privacy Notice for more details on our practices and your data privacy rights. #BI-Remote

Задачи: — Вести инфраструктурные инициативы end-to-end: от проектирования до внедрения и дальнейшей поддержки, включая переход от монолита к гибридной архитектуре; — Развивать платформу на AWS и managed Kubernetes (EKS) и описывать всю инфраструктуру как код на Terraform; — Выстраивать и улучшать CI/CD для крупного проекта с quality gates; — Развивать observability и отвечать за стабильность продакшена в рамках ротации дежурств: инциденты, анализ первопричин, постмортемы; — Работать напрямую с продуктовыми и платформенными командами: получать высокоуровневые требования и самостоятельно доводить их до результата. Требования: — Опыт работы DevOps / SRE с проектами, которые вы вели от начала до конца; — Недавний практический опыт управления продакшен-инфраструктурой в AWS; — Уверенное знание managed Kubernetes (развертывание, настройка и администрирование кластеров); — Глубокий опыт с Terraform; — CI/CD для крупных проектов с quality gates (GitLab CI или аналоги); — Observability, автоскейлинг, безопасность и оптимизация затрат; — Уровень английского B1+; свободное чтение технической документации обязательно. Будет плюсом: опыт использования AI в работе с инфраструктурой. Условия: — Удаленный формат работы, часовой пояс - UTC+2 to UTC+4; — B2B-контракт, оплата в USD на банковский счет, в криптовалюте или комбинированно; — 30 оплачиваемых дней отдыха, включая праздники, плюс оплачиваемые больничные; — Wellness-бюджет и бюджет на обучение, компенсация рабочего оборудования.

Location: Remote, Canada; Remote, Israel; Remote, Poland; Remote, United Kingdom; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role We are hiring a Staff Product Security Architect to join our Security Platforms and Architecture organization at GitLab. Rather than operating as a purely consultative body, Security Architecture at GitLab functions as a hands-on technical driver. Our mission is to embed proactive guidance directly into modern developer workflows and automated coding environments, embedding security standards into the software development process from the outset. We strive to enable teams to deliver secure, resilient software seamlessly while minimizing reliance on manual security gates. In this role, you will collaborate closely with product engineering organizations, spearhead architectural strategy for critical capabilities, and serve as the primary Security Owner driving risk reduction for key entries within our risk management framework. Your daily work will span architectural design reviews, technical prototyping, and establishing scalable patterns that enable engineering teams to execute autonomously. What you’ll do Partner with engineering and product leadership across GitLab, developing enough context in their domains to anticipate security problems rather than react to them Lead security architecture and design work for strategic initiatives, and provide direction to the cross-functional teams delivering them Identify, assess, and prioritise systemic security risks, and act as Security Owner for high-priority items in the Product Security Risk Register, co-executing remediation with the teams who own the code Codify recurring security decisions into reusable artifacts — guardrails, standards, design patterns,skills, and reference threat models — delivered into developer and AI coding tool workflows Build proofs of concept and prototypes to unblock engineering teams and shorten the distance between a security requirement and a working implementation Conduct security architecture reviews for large or strategic projects, and coordinate with Application Security so that review coverage is comprehensive and correctly prioritised Threat model new and existing systems, and establish the patterns that let teams threat model their own work Work with Security Research on proactive exploration of unknown risks in GitLab's architecture Anticipate emerging security challenges and propose architectural responses before they reach implementation Mentor security engineers across the division, and represent security architecture to engineering audiences What you’ll bring Depth in application security architecture, including authentication and authorization models, privilege escalation, multi-tenant isolation, and trust boundary analysis Experience securing distributed systems, including service-to-service authentication, secrets handling, and the failure modes of security decisions made across process boundaries Working knowledge of software supply chain security: build and release integrity, artifact provenance, and dependency risk A track record of proactive architecture work — identifying risk before it becomes an incident, and designing something that prevents a class of problem rather than an instance of one Demonstrated ability to build trusted relationships with engineering leadership and influence technical direction through expertise rather than gatekeeping Experience defining security standards or patterns that teams adopted without being compelled to The ability to operate strategically while remaining hands-on, including reading unfamiliar code, building prototypes, and contributing changes Clear written communication, and the ability to make a security argument to an engineering audience that does not already agree with it A view on how security guidance should be authored and delivered for AI coding tools, not only for humans About the team Security Architects are a part of our Security Platforms and Architecture team, who address complex security challenges facing GitLab and its customers to enable GitLab to be the most secure software factory platform on the market. Composed of Security Architecture , Security Research , and Application Security, we focus on systemic product security risks and work cross-functionally to mitigate them while maintaining Engineering’s development velocity. In FY27, we're implementing a new organizational model where each architect is dedicated to a specific functional area of GitLab's product, enabling deeper context, stronger relationships, and more proactive security guidance. As the Core DevOps architect, you'll be part of a team that includes architects focused on AI and the Sec Section, creating opportunities for collaboration on cross-cutting security challenges while maintaining specialized expertise in your domain. The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $168,000 — $238,000 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .