Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work, and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! . See yourself at Twilio Join the team as Twilio’s next Machine Learning Engineer. About the job This position is needed to drive innovation and the development of cutting-edge products that serve developers, builders, and operators within Twilio’s Data & Observability Substrate organization. This is a hands-on, builder-focused engineering role that bridges Product, Design, and Engineering to develop, evaluate, and maintain scalable, low-latency, ML-based systems for real-time applications. You will lead rapid research-to-production cycles that translate business ideas into solutions for complex problems—such as streaming anomaly detection, recommendation systems, predictive modeling, and agentic AI frameworks—with the goal of delivering personalized customer experiences. You will collaborate closely with a cross-functional team of engineers, architects, product managers, UI/UX designers, and ML/data science partners to deliver robust, reliable solutions that power customer success. Responsibilities In this role, you’ll: - Partner with product, UX, and technical stakeholders to analyze business problems, clarify requirements, define scope, and translate them into measurable ML problem statements. - Design, implement, and maintain scalable, enterprise-grade ML solutions in production. - Build reproducible ML workflows for data preparation, training, evaluation, and inference using modern orchestration and MLOps tooling. - Implement monitoring and evaluation frameworks to continuously improve data quality, model performance, latency, and cost through feedback loops. - Partner cross-functionally with Product, Data Science/ML, Engineering, and Security to deliver resilient, scalable, and compliant ML-powered services. - Demonstrate end-to-end systems understanding and articulate the “why” behind model and system design choices. - Own operational excellence: SLAs, on-call, incident response, customer feedback triage, and blameless post-mortems. - Drive engineering excellence via AI-assisted SDLC, code reviews, automated testing, MLOps best practices, knowledge-sharing, and mentoring. - Actively adopt AI-assisted practices to improve implementation and collaboration efficiency. Qualifications Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table! *Required: - Strong foundation in ML/AI (statistics, probability, optimization) with the ability to apply these concepts to real-world problems. - 5+ years of experience building, deploying, and operating data and ML systems in production. - Proficient in Python, Java, and SQL; strong software engineering fundamentals (system design, testing, version control, code reviews). - Hands-on experience with workflow orchestration and data pipelines (e.g., Airflow, Kubeflow) and cloud data platforms/storage (e.g., SageMaker Feature Store, Snowflake, DynamoDB, OpenSearch). - Experience with the ML lifecycle and MLOps tooling (e.g., MLflow, Metaflow, SageMaker; LLM/agent frameworks such as LangChain/LangGraph; model evaluation/observability tools such as Galileo or similar). - Working knowledge of containerization and cloud infrastructure, including Docker and Kubernetes, GitOps/CI/CD tools (e.g., Argo CD), and at least one major cloud platform (AWS, GCP, or Azure). - Understanding of data modeling and scalable systems, including distributed computing and streaming frameworks (e.g., Spark/EMR, Flink, Kafka Streams); familiarity with GPU-based implementation is a plus. - Demonstrated ability to ramp up quickly and operate effectively in new application/business domains. - Strong written and verbal communication skills: able to document and present designs and decisions, and comfortable giving/receiving feedback in an Agile environment. Desired: - Familiarity with ML problem areas and techniques, including recommendation systems (e.g., graph-based approaches, two-tower models), time-series modeling (classical and deep learning), representation learning (e.g., embeddings), anomaly detection, and causal inference. - Practical experience with LLMs and generative AI workflows, including foundation model fine-tuning, RAG, and vector databases. - Evidence of technical leadership/impact, such as contributions to open-source data/ML projects and/or published technical presentations, blog posts, papers, or research. - Domain experience (plus) in communications, marketing automation, or customer engagement analytics. - Familiarity with AI-assisted development tools (e.g., Claude, GitHub Copilot/Codex, Cursor, etc.). - Advanced degree preferred (M.S. or Ph.D.) in a relevant field. Location This role will be remote, but is not eligible to be hired in CA, CT, NJ, NY, PA, WA. Travel We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings. What We Offer Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location. Compensation *Please note this role is open to candidates outside of California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington D.C., and Washington State. The information below is provided for candidates hired in those locations only. The estimated pay ranges for this role are as follows: - Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $155,520.00 - $194,400.00. - Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $164,640.00 - $205,800.00. - Based in the San Francisco Bay area, California: $182,960.00 - $228,700.00 - This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave. The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. Application deadline information Applications for this role are intended to be accepted until April 20th, but may change based on business needs. Twilio thinks big. Do you? We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call Twilio Magic. Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts. So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for, please consider other open positions. Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

• Develop and evaluate scalable deep learning algorithms that are central to our brain decoding initiatives. • Collaborate closely with data scientists to pioneer research in generative modeling and representation learning. • Identify bottlenecks in data processing pipelines and devise effective solutions, improving performance and reliability. • Maintain high standards of code quality, organization, and automatization across all projects. • Adapt machine learning and neural network algorithms to optimize performance in various computing environments, including distributed clusters and GPUs. • Write and revise papers, participate in conferences, communicate and disseminate results.

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. - Contribute to the execution of deployment and support activities for AI/ML developers; - Build high-quality, clean, scalable and reusable code by enforcing best practices around software engineering architecture and processes (Code Reviews, Unit testing, etc.); - Work with the product owners to understand detailed requirements and own your code from design, implementation, test automation and delivery of high-quality product to our users; - Experience with operating LLMs on NVIDIA GPUs. - Be a mentor for colleagues and help promote knowledge-sharing. 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. Used under license.

• Work with Pacvue’s Data, ML and AI team to support the development and experimentation of machine learning models • Collaborate with data scientists, ML engineers, and product managers to explore large-scale retail media datasets • Assist in building or improving data pipelines, feature engineering processes, or model evaluation frameworks • Participate in prototyping AI-enabled product features • Contribute to technical documentation and communicate findings