• Model development • AI integration into existing systems • Optimization of ML pipelines • Applied generative AI (GenAI) use cases

Company Description It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today - ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone. Job Description What you get to do in this role: Please note that this role requires you to be in our Santa Clara office for two days per week. PLATO (Platform Engineering and AI Technology Organization) at ServiceNow is a customer-focused innovative group building intelligent software using a variety of technology stacks to enable end-to-end, industry-leading work experiences for our customers. We are a group of people deeply invested in the success of our customers that happen to have expertise and knowledge in advanced technologies and software engineering best practices. We are data driven, structured, committed and we enjoy what we are doing. We prioritize robustness, performance and user experience over the technology stack and tools. We are a group of technology professionals and platform engineers with a dual mission. We build and evolve the AI platform, and partner with teams to build products and end-to-end AI-powered work experiences. In equal measure, we lay the foundations, research, experiment, and de-risk AI technologies that unlock new work experiences in the future. As a Staff Machine Learning Engineer you will: Contribute to the design, development and implementation of infrastructure, platform, deployment and observability features that power AI workloads. Collaborate with researchers, AI engineers, and infrastructure teams to ensure our GPU clusters perform efficiently, scale well, and remain reliable. Contribute to the continuous improvement of the SRE practice by turning operational use cases into requirements for software tooling. Qualifications To be successful in this role you have: Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry. Proficient in prompt engineering and developing LLM based features Working experience building VoIP systems using SIP protocol and SBC/PBX/PSTN infrastructures Experience in using AI productivity tools such as Cursor, Windsurf, etc Exposure with operating LLMs on NVIDIA GPUs. 4+ years of development experience with Python, GoLang, Java or similar languages. 4+ years of experience operating highly available distributed workloads on Kubernetes following a DevOps approach. Experience with DevOps tooling (e.g. Helm / Ansible / Kubernetes / Prometheus /Splunk/ GitLab CI); Strong working experience operating distributed systems built on Linux and J2EE; Experience with software-defined networking, infrastructure as code and configuration management; Experience building software for compliance and security in regulated environments Ability to drive outcome in projects with material technical risk. Asset: 4+ years of experience with infrastructure and platform operations, deployments, SRE, and DevOps with a continued focus on improving Platform health; For positions in this location, we offer a base pay of $173,100 - $303,000, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. 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Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams - People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more - provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block. The Role The CashApp Financial Crimes Machine Learning team is responsible for detecting, preventing, and reporting illegal activity across all markets in which Block operates. We work globally with partners in business, engineering, counsel and product to ensure we are providing a safe user experience for our customers while minimizing or eliminating bad activity on our platform. We leverage Machine Learning as a necessary part of our toolkit to fulfill our mission. We employ scalable solutions to monitor billions of dollars in transactions. We uncover and put an end to money laundering, terrorist financing, and other illegal activities before they impact our users. We are looking for senior MLEs who want to solve critical business problems using all tools necessary. (Work from anywhere: This role can be performed from any location in the United States and Canada) You Will Design, develop, and deploy machine learning models to detect and prevent financial crimes such as money laundering, human exploitation, and terrorist financing Collaborate closely with stakeholders, business partners, and product engineering teams to ensure that data can be leveraged effectively to build efficient solutions within our regulatory program Produce and maintain thorough documentation of our program that can withstand regulatory scrutiny Proactively identify new opportunities and future needs of our ML teams Lead by example by applying ML and engineering best practices Stay current on ML developments in the field, foster an environment of continuous learning, and apply new learnings when applicable You Have 6+ years of machine learning experience with a focus on modeling and deployment A degree (preferable graduate level) in Computer Science, Engineering, Statistics, Physics, Applied Math or a related technical field Expertise in at least one area of the following areas: Natural Language Processing, Graph Neural Networks, Reinforcement Learning, or model explainability Prior experience working with product, engineering, and business to prioritize, scope, design, and deploy ML tooling and infrastructure at scale An ability to clearly convey both technical and non-technical concepts while collaborating with cross-functional, globally distributed teams Natural curiosity and desire to grow and help shape all aspects of our team Technologies We Use and Teach Python (NumPy, Pandas, Scikit learn, PyTorch, etc.) with occasional Kotlin and Java Snowflake, GCP, AWS, and orchestration tools such as Prefect and Airflow Transformer models (BERT, LLMs, etc.) We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances. We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build a workplace that is fair and square? Check out our I+D page . While there is no specific deadline to apply for this role, U.S. roles are typically open for an average of 55 days before being filled by a successful candidate. Please refer to the date listed at the top of this job page for when this role was first posted. Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.

About Assembled Great customer support requires human agents and AI in perfect balance, and Assembled is the only unified platform that orchestrates both at scale. Companies like Canva, Etsy, and Robinhood use Assembled to coordinate their entire support operation — in-house agents, BPOs, and AI — in a single operating system. With AI Agents that resolve cases end-to-end, AI Copilot for agent assistance, and AI-powered workforce management that optimizes both human and AI capacity, Assembled helps teams deliver faster, better service while making smarter decisions about how to staff and automate. Backed by $70M from NEA, Emergence Capital, and Stripe, we're building the platform that makes AI and human collaboration actually work. What we build on Forecasting & Scheduling Contact-volume forecasting: data pipelines, statistical/ML models and inference services that predict ticket volumes, agent demand and time to resolution. Queueing simulation: realistic models of synchronous (phone, chat) and asynchronous (email, messaging) queues that forecast wait times, staffing demand considering clearing weekend backlogs while still receiving new tickets. Scheduling tooling: a calendar-like UI that lets managers create and adjust rosters for thousands of agents while respecting preferences, labor laws and SLAs. Agent empowerment: self-service pages for shift swaps, time-off requests and overtime management. What you’ll do with us Lead the architecture and delivery of new ML features end-to-end: research → prototype → production. Drive technical roadmaps, code reviews and design sessions to share your knowledge with the rest of the team. Mentor engineers, unblock thorny problems and act as subject-matter expert for data science topics. Collaborate with Product and Design to turn unclear customer problems into shippable solutions. What we’re after 5+ years shipping production time-series forecasts or similar ML systems. Proficient in a typed backend language (Go, Java or Rust) and comfortable with Python for research. Experience owning services in AWS or similar cloud. Demonstrated technical leadership: design docs, trade-off decisions, mentoring, incident ownership. Product mindset: ability to balance model accuracy, latency, cost and user experience. Even-better-ifs Prior work on large-scale scheduling or optimization problems (e.g. nurse-rostering). Exposure to Kubernetes, Terraform or CDK. Front-end empathy; willing to tweak a React component when needed. Our U.S. benefits Generous medical, dental, and vision plans. Paid company holidays, sick time, and unlimited time off. Monthly credits to spend on professional development, general wellness, Assembled customers, and commuting. Paid parental leave. Hybrid work model with catered lunches everyday (M-F), snacks, and beverages in our SF & NY offices. 401(k) plan enrollment. We know great candidates don’t always meet every requirement listed in a job description. If the role excites you and you believe you can make an impact at Assembled, we encourage you to apply. We value diverse perspectives and are committed to building an inclusive workplace where everyone feels like they belong and has the opportunity to do their best work. We look forward to hearing from you!