JD 展示墙
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2026年10月4日远程 - Remote Compliance Administrator
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2026年10月4日远程 - Sales Engineer
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2026年10月4日远程 - Strategist
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2026年10月4日远程 - Territory Sales Representative (Los Angeles)
Staples is business to business. You're what binds us together.
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2026年10月4日远程 - TikTok Shop Growth Manager
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2026年10月4日远程 - Scrum Master (Information Technology/Software/Remote)
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2026年10月4日远程 - Sr Manager, Solutions Advisory
As the Senior Manager, Solutions Advisory, you will play a pivotal role in shaping Icertis' success in the AMER region.
2026年10月4日远程 - Sr. Accountant
Program:Financial MarketsBLI Name:RentokilDesignation:Process Manager - FP&A Accounting SupervisorNo of Head Count (s):1New Hires/Replacement Hires (HC) by DesignationNew HireBilled /Unbilled / BU / OPS BenchBilledSFDC ID for Billed New OpportunityN/AReasons to hire Unbilled / BenchN/ACity / Location:Alabang, PhilippinesStandardized skillset: [Refer attached excel]Accounts Payable | Accounts Receivable | General LedgerShift (APJ / EMEA / US / Any combination):USReporting Manager :Marlon Cano Educational Background:Bachelor of ScienceExperience Required:8-10 yearsJob Description:see tabClient Approval mail:seeseparate email in threadCommentsexpansion of service from RentokilPreferred Start date: (induction date)ASAPCollaborators:Marlon Cano , Alan Novillas Workplace: WFM, WIO, HybridWFH
2026年10月4日远程 - Property & Casualty Licensed Insurance Representative -- Remote
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2026年10月4日远程 - Remote Property Customer Support / Administration Specialist
Remote positionJob Title: Remote Property Customer Support / Administration Specialist Company Overview:Evolution Sports Group is a leading property management company that specializes in managing properties for sports teams and athletes.
2026年10月4日远程 - Field Marketing Manager (Europe)
Field Marketing Services Manager - Europe | Remote (UK based) 12-month fixed-term contract Are you passionate about creating content that inspires travellers and campaigns that drive bookings?
2026年10月4日远程 - Remote Fundraising Assistant / Donor Relations Coordinator
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2026年10月4日远程 - Technical Solutions Architect II
Do you enjoy designing and building public cloud solutions for customers?
2026年10月4日远程 - Manager, Corp. Tax -Japanese Bilingual
Ready to advance your career? We are a top-tier U.
2026年10月4日远程 - AssemblyAI: Senior Research Engineer
AssemblyAI
Headquarters: Remote Why AssemblyAI AssemblyAI builds the best-in-class Voice AI models powering the next generation of voice applications. Our models serve 600M+ inference calls monthly, process 1M+ hours of audio daily, and power 2 billion+ end-user experiences. The Voice AI space is at an inflection point; we’re looking for folks truly excited to join a small team and help define the future of the industry. We are one of the most capital-efficient AI companies on the planet - with under 100 people generating roughly $600K ARR per employee, we sit among the top 5 most revenue-dense teams within the fastest-growing AI companies today. That's not an accident; it's a deliberate choice to stay lean, move fast, and give every person on the team outsized ownership and impact. With thousands of customers including Granola, Fireflies, Figure AI, and CallRail, the company has real scale - processing over 2 million hours of audio daily and handling more than 1 million API calls every day. This is a rare growth-stage opportunity where the business is proven and the trajectory is steep, but the team is still small enough that your fingerprints are on everything. If you've ever felt buried under layers of bureaucracy, starved of real ownership, or frustrated watching your work disappear into a slow-moving org, AssemblyAI is built differently. The company operates as a true meritocracy, with no heavy planning or approval processes and no gatekeeping on the tools or information you need. For anyone who genuinely cares about voice AI, not as a trend to chase, but as a technology to build, this is the place where the most interesting problems at the most interesting scale are being solved by a team small enough that you'll actually know everyone's name. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. No matter your race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply!About the Role We're looking for a Senior Research Engineer to join our Research team, developing and improving the systems behind large-scale distributed training, data processing, and inference. Our goal as an organization is to solve customer problems and improve our products quickly through model development and measurement — and how fast we move depends on how quickly anyone here can run an experiment, measure it, and find out what's wrong. Raising that ceiling is the heart of this role. You'll be working inside the pipeline you're improving, not alongside it. The ideal candidate has a deep understanding of modern deep learning systems, combined with strong engineering expertise across JAX and TPUs, layer-level optimization, large-scale distributed training, streaming, low-latency and asynchronous inference, inference compilers, and advanced parallelization techniques. This is a cross-functional role. You'll work closely with our researchers, our infrastructure team, and production engineering — not as a handoff point, but as the person who learns enough of each domain to follow problems through to resolution. At times you'll train models, run evaluations, and analyze data yourself, both to deliver impact directly and to learn what's worth building to multiply the team's work. The bar is someone who understands the end-to-end impact they intend to make, measures it from the outset, and would rather find out they were wrong in a week than in a quarter. That discipline is what turns cross-functional ownership into an advantage. The role is embedded within the Research team. What You’ll Do Raise the team's experimental velocity — make it faster to launch an experiment job, get a number back you can trust, and know what to try next. Maintain and evolve our JAX training framework, keeping it scalable and efficient for large-scale distributed training runs on TPU. Improve the data our models learn from: investigating quality issues, building the tooling to surface them, and turning what you find into measurable accuracy gains. Analyze the accuracy of production models, build evaluation harnesses, and work out which improvements will matter most to customers. Translate research prototypes into production-ready systems, refactoring and modernizing model architectures and infrastructure along the way. Optimize production inference for speech language models, both from a serving architecture perspective and through advanced techniques such as quantization and speculative decoding. Investigate and resolve performance bottlenecks across the stack, from low-level kernels (XLA, Pallas) to high-level system design. Partner with researchers, infrastructure, and production engineering to trace problems to their real source and ship fixes that hold. What You’ll Need Expert-level proficiency with JAX and TPUs, including the surrounding ecosystem (Flax, Optax, the XLA compilation pipeline). Measurement discipline. You define what success looks like before you start, you stay skeptical of your own results until they hold up, and you treat an unexplained improvement as a problem rather than a win. Appetite for the whole pipeline. Your core strength might be JAX and TPU performance, but when a customer issue traces back to a data problem or an evaluation blind spot, you want to go find it yourself. The people who do well here went deep in one area first, then kept expanding outward. Strong experience optimizing inference systems for production, ideally with LLMs or speech models. Deep understanding of distributed training at scale, modern deep learning systems, and ML infrastructure best practices. Familiarity with modern inference optimization techniques: continuous batching, KV-cache management, sharding strategies, quantization. Enthusiasm for refactoring and improving existing systems — you thrive on making products and code faster and better. Strong Python skills; C++ or Rust experience for kernel-level work is a plus. Excellent communication and a collaborative mindset — you can clearly explain complex tradeoffs and prioritize high-impact work. Bonus Domain knowledge in Speech-to-Text: ASR architectures, audio processing, streaming inference. Pay Transparency: AssemblyAI strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on paying competitively for our size, stage, and industry, and are one part of many compensation, benefit, and other reward opportunities we provide. There are many factors that go into salary determinations, including relevant experience, skill level, qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. The provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range which will be communicated to candidates throughout the interview process. Salary range: $270,000 - $310,000AI to Interview: If you’re selected for an interview, please review this resource to better understand how AssemblyAI approaches the use of AI in our interview process. GDPR privacy notice: Candidates from the EU should review this job applicant privacy notice before applying. Keep Exploring AssemblyAI: Speech-to-text | Streaming speech-to-text | Speech Understanding | LLM GatewayTry the PlaygroundOur $50M Series C fundraiseCheck us out on YouTube! To apply: https://weworkremotely.com/remote-jobs/assemblyai-senior-research-engineer
2026年10月4日远程 - AssemblyAI: Senior GTM AI Engineer
AssemblyAI
Headquarters: Remote - North America Why AssemblyAI AssemblyAI builds the best-in-class Voice AI models powering the next generation of voice applications. Our models serve 600M+ inference calls monthly, process 1M+ hours of audio daily, and power 2 billion+ end-user experiences. The Voice AI space is at an inflection point; we’re looking for folks truly excited to join a small team and help define the future of the industry. We are one of the most capital-efficient AI companies on the planet - with under 100 people generating roughly $600K ARR per employee, we sit among the top 5 most revenue-dense teams within the fastest-growing AI companies today. That's not an accident; it's a deliberate choice to stay lean, move fast, and give every person on the team outsized ownership and impact. With thousands of customers including Granola, Fireflies, Figure AI, and CallRail, the company has real scale - processing over 2 million hours of audio daily and handling more than 1 million API calls every day. This is a rare growth-stage opportunity where the business is proven and the trajectory is steep, but the team is still small enough that your fingerprints are on everything. If you've ever felt buried under layers of bureaucracy, starved of real ownership, or frustrated watching your work disappear into a slow-moving org, AssemblyAI is built differently. The company operates as a true meritocracy, with no heavy planning or approval processes and no gatekeeping on the tools or information you need. For anyone who genuinely cares about voice AI, not as a trend to chase, but as a technology to build, this is the place where the most interesting problems at the most interesting scale are being solved by a team small enough that you'll actually know everyone's name. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. No matter your race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply!About the Role We're hiring our first Senior GTM AI Engineer. This is a software engineering job inside the revenue org. You will build the pipelines, internal tools, and agents that decide which companies we go after, how we reach them, and what our sellers see when they open their laptop in the morning. Most of what a sales ops team used to do by hand is now something you can write software to do. Finding every company building voice AI before they contact us. Researching an account and drafting the first email. Watching product usage and telling an AE when a customer is about to expand or churn. Keeping the CRM clean without anyone filling in forms. You will build those systems, run them in production, and be judged on whether pipeline and revenue move. Your users are our AEs, SDRs, and GTM leaders. Your job is to make a small team perform like one three times its size. What You'll Do Write code every day. Python services, SQL models, scheduled jobs, and small internal apps are most of the job. You'll use Claude Code and similar tools to ship in days what used to take a quarter. Build agents that do the work: account research, lead qualification, outreach drafting, CRM hygiene, and usage monitoring. Design them, give them tools and data, evaluate their output, and keep them running. Turn product usage data in BigQuery and Looker into signals sellers act on: usage alerts, expansion triggers, and account health scores. Build the account targeting machine: sourcing, enrichment, dedupe, and ICP scoring, from raw data to a ranked list in a rep's queue. Integrate the systems the team already uses (our CRM, enrichment providers, outbound tools) so data moves between them without a human in the loop. Keep funnel data trustworthy: routing rules, field governance, and attribution. Prototype fast, measure what works, kill what doesn't, and work directly with Sales and Marketing leadership on what to build next. Document what you build so it keeps running without you. What You'll Need 4+ years as a software engineer, data engineer, or growth/GTM engineer, with time spent shipping systems that other people depend on. Strong Python and SQL. You have owned production automations end to end: APIs, webhooks, scheduled jobs, retries, error handling, and monitoring. Experience building with LLMs beyond a single prompt: multi-step agents, tool use, retrieval, and evaluation. You can tell whether an agent's output is good, and you know when a plain script is the better tool. AI-assisted development is how you work. You use Claude Code or similar tools daily, and you have the engineering judgment to review, test, and stand behind what they produce. Solid fundamentals: clean code, version control, code review, debugging, and a habit of thinking in systems. You do not need an engineering team to ship. Curiosity about how a sales org works. You don't need a RevOps background, but you need to care about how deals get found and closed, and be willing to learn our CRM and the tools around it quickly. A builder's mindset with an operator's judgment: you scope for business impact, ship iteratively, and measure results in pipeline and revenue. Low ego, high ownership, and comfort being the single-threaded owner of an entire domain. Nice to Have Hands-on Salesforce or other CRM work at the object and API level, or experience with enrichment and outbound tools like Clay. dbt, BigQuery, and Looker, or an equivalent warehouse and BI stack. Time at a developer-facing or API-first company, or selling to technical buyers. You've been the first engineer in a sales or growth org and built the function from scratch. Pay Transparency: AssemblyAI strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on paying competitively for our size, stage, and industry, and are one part of many compensation, benefit, and other reward opportunities we provide. There are many factors that go into salary determinations, including relevant experience, skill level, qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. The provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range which will be communicated to candidates throughout the interview process. Salary range: $160,000 to $220,000AI to Interview: If you’re selected for an interview, please review this resource to better understand how AssemblyAI approaches the use of AI in our interview process. GDPR privacy notice: Candidates from the EU should review this job applicant privacy notice before applying. Keep Exploring AssemblyAI: Speech-to-text | Streaming speech-to-text | Speech Understanding | LLM GatewayTry the PlaygroundOur $50M Series C fundraiseCheck us out on YouTube! To apply: https://weworkremotely.com/remote-jobs/assemblyai-senior-gtm-ai-engineer
2026年10月4日远程 - Stripe: Abuse Research Engineer
Stripe
Headquarters: Remote from the US Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Abuse Research Group (ARG) handles proactive threat hunting and adversary behavior analysis across Stripe products. Rather than reacting to alerts, the team maps end-to-end fraud and abuse paths, validates novel attack vectors, and identifies product conditions that enable fraud. Using agentic automated testing and simulation tools, ARG translates research into actionable threat advisories, strategic control recommendations, and regression scenarios to systematically eliminate vulnerabilities. What you’ll do As an Abuse Research Engineer in the Abuse Research Group, you will play a critical role in safeguarding Stripe’s financial ecosystem by proactively hunting for advanced threats, dissecting complex fraud vectors, and extracting actionable adversary intelligence. Rather than relying solely on reactive alerts, you will develop and execute hypothesis-driven threat hunting operations across internal telemetry and external sources to uncover fraudulent tools, tactics, and techniques (TTPs) before they impact Stripe’s platform. Central to this work is FT3 (Fraud Taxonomy 3.0), Stripe’s multi-layered taxonomy that decomposes monolithic fraud into structured kill chains. Collaborating cross-functionally with Fraud Ops, Strategy, Risk, Onboarding, and Security, you will integrate threat intelligence, build agentic simulation workflows, and systematically eliminate product vulnerabilities. Responsibilities Proactive Threat Hunting & Kill Chain Analysis: Formulate hypotheses and conduct iterative threat hunting operations across Stripe systems and external data. FT3 Taxonomy: Apply and enrich the FT3 framework across empirical datasets and incidents, standardizing threat intelligence across kill chain phases and targeted API endpoints. Threat Intelligence & Signal Expansion: Partner with teams like Fraud Intelligence to integrate, curate, and automate threat feeds into engineering workflows. Cross-Functional Advisories & Strategic Controls: Translate raw research and retrospective findings into actionable threat advisories and control recommendations (policy, technical systems, support workflows, and detection mechanisms) for stakeholders across Fraud, Risk, Onboarding, and Security. Agentic Testing & Adversary Simulation: Utilize agentic automated testing frameworks to simulate adversary TTPs, validate whether deployed controls interrupt empirical kill chains, and generate regression scenarios to exercise controls. Who you are We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements 5+ years of experience conducting threat intelligence, threat hunting, or technical incident response within cyber security, product abuse, or trust domains. 5+ years of experience analyzing large, complex datasets using data analytics tools to identify anomalies, map behavioral trends, and solve complex fraud problems. B.S. or M.S. in Computer Science, Cybersecurity, or a related technical field, or equivalent practical experience. Expert proficiency in Python and SQL, with demonstrated experience using code and scripting to automate workflows, build investigative tools, or query big data pipelines. Hands-on experience in log analysis (e.g., application logs, API route telemetry, network security events), digital forensics, and cyber investigation methodologies. Strong communication skills with a proven ability to translate complex technical research into clear, actionable recommendations and advisories for cross-functional partners. Preferred qualifications Deep technical understanding of threat actor motivations, infrastructure, and TTPs specific to financial fraud (e.g., ATO, Card Testing, Credential Stuffing). Familiarity with standardized taxonomies such as FT3 or MITRE ATT&CK. Proficiency with engineering, data processing, and analysis platforms such as Databricks, Trino, PySpark, Pandas, or Scikit-Learn. Proven background utilizing Threat Intelligence Platforms (TIPs), tactical threat feeds, OSINT, and breach intelligence. Demonstrated capability building or leveraging agentic LLM tools, automated testing systems, or control validation frameworks to model adversary behavior at scale. Participation in industry conferences, webinars, or threat-sharing groups, alongside relevant professional certifications (e.g., GCTI, GCFA, OSCP). To apply: https://weworkremotely.com/remote-jobs/stripe-abuse-research-engineer
2026年10月4日远程 - 金马科技招聘全职远程工作财务主管/运营
kakaxi168168
财务主管/运营专员 4名 🚩办公地:居家（接受海外优先）🔴大专及以上学历，会计、财务管 […]
2026年10月4日远程