Senior Machine Learning Engineer

Posted 7 Hours Ago
Be an Early Applicant
Hyderabad, Telangana
Hybrid
50K-150K
Senior level
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
We're putting AI to work for people.
The Role
The Senior Machine Learning Engineer will generate synthetic data, fine-tune models, implement metrics, improve AI solutions, and ensure AI safety.
Summary Generated by Built In

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:

  • Generate and evaluate synthetic data tailored to improve the robustness, performance, and safety of machine learning models, particularly large language models (LLMs).
  • Train and fine-tune models using curated datasets, optimizing for performance, reliability, and scalability.
  • Design and implement evaluation metrics to rigorously measure and monitor model quality, safety, and effectiveness.
  • Conduct experiments to validate model behavior and improve generalization across diverse use cases.
  • Collaborate with engineering and research teams to identify risks and recommend AI safety mitigation strategies.
  • Participate in the development, deployment, and continuous improvement of end-to-end AI solutions.
  • Contribute to architectural and technology decisions related to AI infrastructure, frameworks, and tooling.
  • Promote modern engineering practices including continuous integration, continuous delivery, and containerized workflows.

  • Qualifications
    Key qualifications:

  • 5+ years of experience in machine learning, deep learning, and AI systems.
  • Proficiency in Python and frameworks like PyTorch, TensorFlow, and NumPy.
  • Experience in synthetic data generation, model training, and evaluation in real-world environments.
  • Solid understanding of LLM fine-tuning, prompting, and robustness techniques.
  • Knowledge of AI safety principles and experience identifying and mitigating model risks.
  • Hands-on experience deploying and optimizing models using platforms such as Triton Inference Server.
  • Familiarity with CI/CD, automated testing, and container orchestration tools like Docker and Kubernetes.

  • 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.

    Top Skills

    Docker
    Kubernetes
    Numpy
    Python
    PyTorch
    TensorFlow
    Triton Inference Server

    What the Team is Saying

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    The Company
    HQ: Santa Clara, CA
    26,000 Employees
    Hybrid Workplace
    Year Founded: 2004

    What We Do

    As the AI platform for business transformation, we're putting AI to work across organizations — freeing people for work that matters. Making old tech work with new tech. Reaching across departments, from the front office to the back office and every office in between. Our ambition? To become the defining enterprise software company of the 21st century (or "DESCO21C," as we like to call it).

    With more than 8,100+ customers, we serve approximately 85% of the Fortune 500®, and we're proud to be a Fortune 100 Best Companies to Work For® and World's Most Admired Companies™.

    Explore your future career with us, visit www.servicenow.com/careers.

    From Fortune. ©2024 Fortune Media IP Limited. All rights reserved. Used under license.

    Why Work With Us

    By joining ServiceNow, you are part of an ambitious team of change-makers who have a restless curiosity and a drive for ingenuity. We're committed to helping our people do their best work and live their best lives so we can fulfill our purpose together. At the fastest-growing enterprise software company , you can grow can grow your career faster.

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    ServiceNow Offices

    Hybrid Workspace

    Employees engage in a combination of remote and on-site work.

    At ServiceNow, we lead with flexibility and trust. For some, home is the primary workplace. For those who come into a ServiceNow workplace, you are empowered to make team-guided and individual-led decisions on how and when you use the workplace.

    Typical time on-site: Flexible
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