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Staff Machine Learning Engineer - job 1 of 3

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:

We are a group of researchers, applied scientists, engineers, and product managers 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.

You will play a major part in building next generation Large Language Models(LLM's) for Enterprise Language Generation that will power NOW platform with AI experiences in day to day work of our customers. 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 9k+ enterprise customers around the world.

What you get to do in this role:

  • Confronted with real-world challenges and datasets, you will need to use your AI/ML expertise and creativity to apply existing methods and develop new ones to solve these problems in a practical and scalable way.
  • Research, propose and implement appropriate models/techniques for LLM benchmarking.
  • Participate in data collection and synthetic data generation, and generate custom benchmarks to evaluate diverse LLMs capabilities.
  • Collaborate daily with a team of like-minded developers, applied research scientists, product managers and quality engineers to produce quality software.
  • Contribute to the implementation of tools to facilitate LLMs evaluation and perform model / error analysis.
  • Develop innovative patentable ideas that ensure the competitiveness of this product within the domain of similar work being done in the industry.
  • Potentially write research papers in collaboration with our Research Group, to be published to the most notorious AI Conferences.
  • Work with product owners to understand detailed requirements and own your code from design, implementation, testing and delivery of high-quality & high-impact solutions to our users.

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. 
  • 6+ years of relevant experience with a Bachelor's degree; or 4 years with a Master's degree; or a PhD with no experience; or equivalent work experience.
  • Solid expertise in Python.
  • Solid Machine Learning / Deep Learning theoretical knowledge and hands-on experience.
  • Experience with LLM benchmarking and evaluation is required; experience generating synthetic data is a plus.
  • Ability to read and experiment with ideas from recent research papers.
  • High level of creativity, quick problem-solving abilities, and adaptability.
  • Effective communication skills to convey research findings to both technical and non-technical stakeholders, ensuring a clear understanding of the benefits and limitations of LLMs across the organization.

 

Not sure if you meet every qualification? We still encourage you to apply! We value inclusivity, welcoming candidates from diverse backgrounds, including non-traditional paths. Unique experiences enrich our team, and the willingness to dream big makes you an exceptional candidate!

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. Learn more here.

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 [email protected] 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. ©2024 Fortune Media IP Limited. All rights reserved. Used under license. 

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Average salary estimate

$238050 / YEARLY (est.)
min
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$173100K
$303000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Staff Machine Learning Engineer, ServiceNow

At ServiceNow, we are excited to invite you to join our team as a Staff Machine Learning Engineer! Here, in our vibrant Santa Clara office, you'll be part of an innovative group that's at the forefront of AI technology. Our mission is to build and enhance an AI platform that empowers organizations around the world to work smarter. In this role, you will confront real-world challenges head-on, utilizing your AI and machine learning expertise to develop and implement cutting-edge solutions. You'll work closely with a diverse team of researchers, applied scientists, and product managers, collaborating daily to create AI-powered experiences that revolutionize how our customers operate. As a Staff Machine Learning Engineer, you'll engage in benchmarking large language models, participate in synthesizing data, and contribute to the development of tools that facilitate LLM evaluation. Your creativity and problem-solving abilities will be essential as you develop innovative ideas that keep us competitive in the rapidly evolving tech landscape. With over 8,100 customers looking for smarter solutions, your contributions will play a crucial role in shaping the future of work. We value diverse experiences and encourage candidates from all backgrounds to apply. If you're looking to make a significant impact and grow your career in a collaborative environment where your ideas are valued, we would love to hear from you!

Frequently Asked Questions (FAQs) for Staff Machine Learning Engineer Role at ServiceNow
What are the responsibilities of a Staff Machine Learning Engineer at ServiceNow?

As a Staff Machine Learning Engineer at ServiceNow, you will be tasked with developing and implementing AI solutions, engaging in LLM benchmarking and evaluation, and contributing to innovative projects that enhance our AI capabilities. Your role will involve collaborating with a dynamic team, conducting research, and utilizing your expertise to solve real-world challenges in machine learning.

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What qualifications are required for the Staff Machine Learning Engineer position at ServiceNow?

To qualify for the Staff Machine Learning Engineer position at ServiceNow, candidates should possess a Bachelor's degree with 6+ years of relevant experience or a Master's degree with 4 years of relevant experience. A PhD with no experience is also acceptable. In addition, candidates should have solid skills in Python, deep learning, and experience with LLM benchmarking.

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What kind of projects will a Staff Machine Learning Engineer work on at ServiceNow?

At ServiceNow, a Staff Machine Learning Engineer will work on exciting projects focused on building next-generation large language models that will serve our enterprise customers. You will collaborate with researchers and engineers to develop tools, evaluate AI models, and contribute to innovative research that drives our AI platform forward.

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How does ServiceNow support professional development for a Staff Machine Learning Engineer?

ServiceNow is committed to the professional development of its employees, including Staff Machine Learning Engineers. We offer opportunities for collaboration on research papers, attendance at renowned AI conferences, and a supportive environment for sharing ideas and innovation, enabling you to grow your skills and career in the AI field.

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What type of work environment can a Staff Machine Learning Engineer expect at ServiceNow?

At ServiceNow, Staff Machine Learning Engineers can expect a flexible and collaborative work environment that fosters creativity and innovation. We embrace a distributed work model, allowing for a healthy work-life balance while encouraging teamwork and communication among team members.

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Common Interview Questions for Staff Machine Learning Engineer
Can you describe your experience with large language models?

When answering this question, highlight your specific projects or tasks that involved large language models. Discuss how you approached LLM benchmarking, any challenges you faced, and the outcomes you achieved, showcasing your expertise and understanding of their importance in today's AI landscape.

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How do you approach solving real-world problems with AI?

In your response, outline your problem-solving process. Emphasize your ability to analyze data, develop models, and adapt existing methods to find creative solutions. Provide examples of previous work where your approach led to successful outcomes, showcasing your hands-on experience in tackling practical challenges.

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What machine learning frameworks and tools do you prefer to use and why?

Discuss your familiarity with popular machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Explain why you find these tools beneficial in your work, considering aspects like ease of use, scalability, and community support. This shows your practical knowledge and standing within the field.

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How do you keep up with recent advancements in machine learning research?

Share your strategies for staying updated with the latest research and trends. Mention specific journals, conferences, online courses, or communities you engage with, demonstrating your commitment to lifelong learning and adaptation in the evolving field of machine learning.

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Describe a project where you had to collaborate with a non-technical team. How did you communicate complex ideas?

In your answer, provide a specific example of a project where communication was key. Explain how you simplified complex concepts and ensured effective understanding among non-technical stakeholders, emphasizing your communication skills and adaptability in a collaborative environment.

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What has been your most significant contribution to AI in your previous roles?

Bring attention to an impactful project or responsibility you had. Explain your role, the technologies used, and the results of your efforts, showing your ability to drive meaningful changes and innovations in AI.

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What challenges do you foresee in the future of AI development?

In your response, discuss potential ethical considerations, technical limitations, and the need for regulations in AI. This reflects your understanding of the complexities surrounding AI development and your ability to think critically about its future.

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How do you approach testing and validating machine learning models?

Discuss your systematic approach to model validation. Outline methods such as cross-validation, performance metrics, or A/B testing that you implement to ensure model accuracy and reliability, showcasing your thoroughness in developing AI solutions.

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What strategies do you use to develop innovative ideas in machine learning?

Describe your creative process, including brainstorming, research, and experimentation. Mention how you draw inspiration from existing work and your willingness to take calculated risks, highlighting your innovation and creativity in the field.

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Can you provide an example of a time when you had to pivot a project's direction? What was the result?

Share a specific instance where adapting to new information or challenges was necessary. Explain how you reassessed goals, made strategic changes, and the eventual impact of your decisions, demonstrating your flexibility and initiative.

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We're on a mission to become the defining enterprise software company of the 21st century.

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CULTURE VALUES
Inclusive & Diverse
Mission Driven
Rise from Within
Diversity of Opinions
Work/Life Harmony
Empathetic
Feedback Forward
Take Risks
Collaboration over Competition
BENEFITS & PERKS
Medical Insurance
Dental Insurance
Vision Insurance
Mental Health Resources
Life insurance
Disability Insurance
Health Savings Account (HSA)
Flexible Spending Account (FSA)
Conferences Stipend
Paid Time-Off
Maternity Leave
Equity
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DEPARTMENTS
SENIORITY LEVEL REQUIREMENT
TEAM SIZE
EMPLOYMENT TYPE
Full-time, on-site
DATE POSTED
March 23, 2025

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