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Urgent! ML Engineer, AI Safety Job Opening In Sahibzada Ajit Singh Nagar – Now Hiring TaskUs

ML Engineer, AI Safety



Job description

About TaskUs: TaskUs is a provider of outsourced digital services and next-generation customer experience to fast-growing technology companies, helping its clients represent, protect and grow their brands.

Leveraging a cloud-based infrastructure, TaskUs serves clients in the fastest-growing sectors, including social media, e-commerce, gaming, streaming media, food delivery, ride-sharing, HiTech, FinTech, and HealthTech.

The People First culture at TaskUs has enabled the company to expand its workforce to approximately 45,000 employees globally.Presently, we have a presence in twenty-three locations across twelve countries, which include the Philippines, India, and the United States.

It started with one ridiculously good idea to create a different breed of Business Processing Outsourcing (BPO)! We at TaskUs understand that achieving growth for our partners requires a culture of constant motion, exploring new technologies, being ready to handle any challenge at a moment’s notice, and mastering consistency in an ever-changing world.

What We Offer:At TaskUs, we prioritize our employees' well-being by offering competitive industry salaries and comprehensive benefits packages.

Our commitment to a People First culture is reflected in the various departments we have established, including Total Rewards, Wellness, HR, and Diversity.

We take pride in our inclusive environment and positive impact on the community.

Moreover, we actively encourage internal mobility and professional growth at all stages of an employee's career within TaskUs. Join our team today and experience firsthand our dedication to supporting People First.

Software Engineer, AI Safety Services
Build the tools that keep AI trustworthy.

The impact you’ll make

  • Enable rapid, responsible releases by coding evaluation pipelines that surface safety issues before models reach production.

  • Drive operational excellence through reliable, secure, and observable systems that safety analysts and customers trust.

  • Advance industry standards by contributing to best‑practice libraries, open‑source projects, and internal frameworks for testing alignment, robustness, and interpretability.

  • What you’ll do

  • Design & implement safety tooling—from automated adversarial test harnesses to drift‑monitoring dashboards—using Python, PyTorch/TensorFlow, and modern cloud services.

  • Collaborate across disciplines with fellow engineers, data scientists, and product managers to translate customer requirements into clear, iterative technical solutions.

  • Own quality end‑to‑end: write unit/integration tests, automate CI/CD, and monitor production metrics to ensure reliability and performance.

  • Containerize and deploy services using Docker and Kubernetes, following infrastructure‑as‑code principles (Terraform/CDK).

  • Continuously learn new evaluation techniques, model architectures, and security practices; share knowledge through code reviews and technical talks.

  • Experiences you’ll bring

  • 3+ years of professional software engineering experience, ideally with data‑intensive or ML‑adjacent systems.

  • Demonstrated success shipping production code that supports high‑availability services or platforms.

  • Experience working in an agile, collaborative environment, delivering incremental value in short cycles.

  • Technical skills you'll need

  • Languages & ML frameworks: Strong Python plus hands‑on experience with PyTorch or TensorFlow (bonus points for JAX and LLM fine‑tuning).

  • Cloud & DevOps: Comfortable deploying containerized services (Docker, Kubernetes) on AWS, GCP, or Azure; infrastructure‑as‑code with Terraform or CDK.

  • MLOps & experimentation: Familiar with tools such as MLflow, Weights & Biases, or SageMaker Experiments for tracking runs and managing models.

  • Data & APIs: Solid SQL, exposure to at least one NoSQL store, and experience designing or consuming RESTful APIs.

  • Security mindset: Awareness of secure coding and compliance practices (e.g., SOC 2, ISO 27001).

  • Nice to have: LangChain/LangGraph, distributed processing (Spark/Flink), or prior contributions to open‑source ML safety projects.

    How We Partner To Protect You: TaskUs will neither solicit money from you during your application process nor require any form of payment in order to proceed with your application.

    Kindly ensure that you are always in communication with only authorized recruiters of TaskUs.


    DEI: In TaskUs we believe that innovation and higher performance are brought by people from all walks of life.

    We welcome applicants of different backgrounds, demographics, and circumstances.

    Inclusive and equitable practices are our responsibility as a business.

    TaskUs is committed to providing equal access to opportunities.

    If you need reasonable accommodations in any part of the hiring process, please let us know.

    We invite you to explore all TaskUs career opportunities and apply through the provided URL.


    Required Skill Profession

    Computer Occupations



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    • The Work Culture

      An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at TaskUs adheres to the cultural norms as outlined by Expertini.

      The fundamental ethical values are:
      • 1. Independence
      • 2. Loyalty
      • 3. Impartiality
      • 4. Integrity
      • 5. Accountability
      • 6. Respect for human rights
      • 7. Obeying India laws and regulations
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    • Interview Tips for ML Engineer, AI Safety Job Success
      TaskUs interview tips for ML Engineer, AI Safety

      Here are some tips to help you prepare for and ace your job interview:

      Before the Interview:
      • Research: Learn about the TaskUs's mission, values, products, and the specific job requirements and get further information about
      • Other Openings
      • Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.
      • Dress Professionally: Choose attire appropriate for the company culture.
      • Prepare Questions: Show your interest by having thoughtful questions for the interviewer.
      • Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.
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      • Be Punctual: Arrive on time to demonstrate professionalism and respect.
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      • Follow Up: Send a thank-you email to the interviewer within 24 hours.
      Additional Tips:
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      Final Thought:

      To prepare for your ML Engineer, AI Safety interview at TaskUs, research the company, understand the job requirements, and practice common interview questions.

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