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 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. You will play a major part in building AI and Machine Learning (ML) solutions that transform the user experience and workflow efficiency of enterprise services. Traditional analytical tools tend to require a technically knowledgeable user to produce even simple results. We are taking a completely fresh approach with the expectation that any user, regardless of technical knowledge, can use the AI/ML solutions we develop to operate the services in the enterprise setting in a thoughtful and scalable manner. We are just getting started with our early-adopter customers and we need your help in building and making available an amazing range of solutions to our 5k+ enterprise customers around the world. What you get to do in this role: - Lead the design and implementation of VoIP and CCaaS integrations, connecting ServiceNow's AI platform with enterprise contact center providers. - Design and architect VoIP infrastructure, telephony platforms, and observability features that power AI-driven voice workloads - Collaborate with engineering, Product, and infrastructure teams to ensure our voice and AI platforms perform efficiently, scale reliably, and integrate seamlessly across SIP/RTP, Kamailio, RTPEngine, and related telecom systems. - Contribute to the continuous improvement of the SRE practice by turning operational telephony and AI workload use cases into requirements for software tooling. - Lead the execution of deployment and support activities for VoIP systems and AI/ML developers operating in production voice environments. - 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 product owners to understand detailed requirements and own your code from design, implementation, test automation, and delivery - spanning both telephony infrastructure and LLM integration layers. - Integrate AI capabilities - including LLM-powered features and conversational workflows - into real-time voice pipelines. - Be a mentor for colleagues and help promote knowledge-sharing across telecom and AI engineering disciplines. Qualifications To be successful in this role you have: - Extensive experience building VoIP systems using SIP/RTP protocols; - Practical knowledge of Kamailio, RTPEngine, FreeSWITCH, SBCs, and PSTN systems (or similar); - Working knowledge of PSTN infrastructure and telecom protocols; - Experience integrating applications on top of LLMs (using existing models, not building them); - Experience in prompt engineering and developing LLM based features - 10+ years of development experience with Python, GoLang, Java or similar languages. - 10+ years of experience operating highly available distributed workloads on Kubernetes following a DevOps approach. - Working experience building distributed systems with cloud-native software; - Experience with software-defined networking, infrastructure as code and configuration management; - Experience with DevOps tooling (e.g. Helm / Ansible / Kubernetes / Prometheus /Splunk/ GitLab CI) is considered an asset - Experience building software for compliance and security in regulated environments is considered an asset - 10+ years of experience with infrastructure and platform operations, deployments, SRE, and DevOps with a continued focus on improving Platform health is considered an asset - 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. - Experience in using AI productivity tools such as Cursor, Windsurf, etc For positions in this location, we offer a base pay of $236,000 - $413,000, 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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Interns will utilize statistics and computer science to solve complex problems in healthcare. Problem areas include: diagnostic analytics such as image analysis, signal processing and pattern recognition, NLP, scheduling, risk analysis and prevention, outcome analysis, targeting and socio-economic behaviors, personalization – including sentiment, interests and affinities modeling, and process improvement (e.g. making sure patients are referred to the care teams they need). The Intern will interact with vast amounts of clinical and non-clinical data (external data sources, digital, etc.). Interns will learn the data science lifecycle including data acquisition, transformation, data engineering, exploratory data analysis, feature engineering, algorithm development, and algorithm deployment into a relevant clinical and/or business context. Interns are expected to help formulate analytical questions, perform hypothesis testing, algorithm optimization, algorithm deployment, and integrate feedback rapidly from stakeholders. Candidate needs to have an open mind and ability to take concepts developed by other industries and apply them to healthcare. Candidates should be effective communicators and good team players. Candidates who have coursework, projects, and evidence of interest in data science (e.g. participating in Kaggle competitions) but lack industry experience are ideal for this position. **This position is not eligible for visa sponsorship; Also, Mayo Clinic DOES NOT participate in the F-1 STEM OPT extension program. Why Mayo Clinic Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans – to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic. Benefits Highlights - Medical: Multiple plan options. - Dental: Delta Dental or reimbursement account for flexible coverage. - Vision: Affordable plan with national network. - Pre-Tax Savings: HSA and FSAs for eligible expenses. - Retirement: Competitive retirement package to secure your future. Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives. Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is. Equal Opportunity All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the "EOE is the Law". Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization.

About SafeGraph SafeGraph is a Data as a Service (DaaS) company with one focus: curating the most accurate, precise, and fresh points of interest (POI) database on the planet. We provide product builders, data scientists, and analytics teams with the location data they need to power site selection, transaction enrichment, advertising audiences, competitive intelligence, and more. Our customers include companies like Plaid, Mapbox, Clear Channel — spanning fintech, retail, real estate, adtech, logistics, and government. We’re fully remote, lean by design, and serious about data quality. The Role You’ll be a generalist responsible for building and running large-scale data, machine learning, and agentic systems. The focus is operational ML/AI, including agentic systems and geospatial data pipelines.  You should be comfortable owning the full lifecycle: from data ingestion and distributed processing to model development, deployment, and monitoring. This role requires the ability to iterate quickly from initial concept to a robust, production-ready solution.   Key Responsibilities - Take ownership of the end-to-end AI/ML lifecycle, with a strong focus on dealing with complex and messy data, thorough evaluation of different approaches, and successfully deploying robust models, and handling cost vs performance tradeoffs. - Implement and integrate large-scale, agent-based systems with access to external systems, building these solutions from the ground up and integrating them with our existing infrastructure. - Establish observability for pipelines, models, and agents (metrics, tracing, alerting). - Collaborate with product and customer teams to drive revenue.

About SafeGraph SafeGraph is a Data as a Service (DaaS) company with one focus: curating the most accurate, precise, and fresh points of interest (POI) database on the planet. We provide product builders, data scientists, and analytics teams with the location data they need to power site selection, transaction enrichment, advertising audiences, competitive intelligence, and more. Our customers include companies like Plaid, Mapbox, Clear Channel — spanning fintech, retail, real estate, adtech, logistics, and government. We’re fully remote, lean by design, and serious about data quality. The Role You’ll be a generalist responsible for building and running large-scale data, machine learning, and agentic systems. The focus is operational ML/AI, including agentic systems and geospatial data pipelines.  You should be comfortable owning the full lifecycle: from data ingestion and distributed processing to model development, deployment, and monitoring. This role requires the ability to iterate quickly from initial concept to a robust, production-ready solution.   Key Responsibilities - Take ownership of the end-to-end AI/ML lifecycle, with a strong focus on dealing with complex and messy data, thorough evaluation of different approaches, and successfully deploying robust models, and handling cost vs performance tradeoffs. - Implement and integrate large-scale, agent-based systems with access to external systems, building these solutions from the ground up and integrating them with our existing infrastructure. - Establish observability for pipelines, models, and agents (metrics, tracing, alerting). - Collaborate with product and customer teams to drive revenue.