Gremlin

Data Scientist, AI/ML

USA, United States full-time Mid Salary not listed
full-time Mid level Technology & IT Curated
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About the role

Data Scientist, AI/ML

Job Description:

Today’s complex, fast-paced systems have become a minefield of reliability risks, any of which could cause an outage that costs millions and destroys customer confidence. That’s why high-availability teams use Gremlin to find and fix reliability risks before they become incidents.

Gremlin Reliability Platform helps software teams proactively monitor and test their systems for common reliability risks, build and enforce reliability standards, and automate their reliability practices organization-wide. As the industry leader in Chaos Engineering and reliability testing, we work with hundreds of the world’s largest organizations where high availability is non-negotiable.

About the Role of the Data Scientist, AI/ML

As a Data Scientist, AI/ML at Gremlin, you will have the opportunity to improve the reliability of the internet at large by turning millions of chaos engineering experiments into automated failure analysis and remediation. You will be able to leverage your applied machine learning experience to inform product direction as well as solve complex technical problems that directly impact our customers (which range from the Fortune 500 to smaller organizations). You will work closely with a small, talented engineering team focused on quality, delivery, and predictability with an emphasis on providing our customers a great user experience.

In this role, you’ll get to:

Analyze Gremlin’s proprietary dataset of millions of chaos engineering experiments to identify failure patterns, root causes, and resilience signals across complex distributed systems

Pretraining and fine-tuning machine learning models that automatically detect, classify, and explain failures observed during chaos experiments

Build intelligent systems that deliver automated remediation recommendations, and eventually orchestration, by learning from historical experiment outcomes and system behavior

Develop scalable data pipelines and feature stores to process, enrich, and serve large volumes of experiment data for both model training and real-time inference

Collaborate closely with platform engineers and SREs to integrate AI-driven failure analysis and remediation capabilities directly into Gremlin’s core product

Apply advanced techniques, including causal inference, graph ML, time-series modeling, and reinforcement learning, to continuously improve the accuracy and actionability of automated failure analysis

Translate insights from millions of chaos experiments into AI-powered features that help customers automatically understand blast radius, pinpoint root causes, and accelerate recovery

Research and productionize novel ML approaches, including causal AI and agentic systems, that turn raw chaos experiment data into automated, reliable remediation strategies

We’ll expect you to have:

Experience as a self-driven and collaborative problem solver with strong communication skills

5+ years professional experience building and productionizing machine learning, ideally for distributed systems, infrastructure, or DevOps and SRE use cases with more overall years of experience in software development.

Hands-on experience with techniques such as causal inference, graph ML, time-series modeling, or reinforcement learning

Experience building data pipelines and feature stores that support both offline training and real-time inference

Experience with agile development environments and practices

Strong advocate and practitioner of rigorous experimentation, model evaluation, and engineering best practices

Comfort partnering with platform engineers and SREs to turn research into shipped product features

Strong at breaking down ambiguous problems into concrete actions and milestones

Bonus Experience:

Experience with chaos engineering, site reliability engineering, or distributed systems

Background in agentic AI systems or large-scale causal inference in production

Experience standing up MLOps tooling such as model serving, monitoring, or feature store infrastructure

Working in Remote first environments

Has been on-call and participated in an incident management program

*The role does not offer sponsorship employment benefits.

**If you don’t think you meet all of the criteria above but still are interested in the job, please apply. Nobody checks every box, we’re looking for candidates that are particularly strong in a few areas, and have some interest and capabilities in others.

Compensation

We expect the salary range for this role to be $220,000 - $290,000. We recognize that salary varies from person to person depending on level of experience and we welcome direct conversations about it. The final offer will vary based on assessment of a candidate's skills and ability and our budget and market data.

Gremlin offers competitive total compensation packages including 401k Matching, Equity and other benefits such as flexible time off and paid company holidays.

About Gremlin:

Gremlin is a team of industry veterans and people eager to learn from one another. We set the standard for reliability and equip leading organizations with the mindset and expertise needed to drive reliability improvements that move the world forward. We’re backed by top-tier investors Index Ventures, Amplify Partners, and Redpoint Ventures. Our customers love us, and we’re thrilled to be a partner in their success.

What Do We Care About:

We Care about our People

People are our critical differentiators. The company strives to treat our people with respect, empathy, and dignity. We expect that our people will treat each other similarly. In both cases, we will assume good intent. All are welcome at Gremlin. We know our differences make us stronger and that our best ideas and contributions can come from anyone at any level.

We Care about Collaboration

Gremlin is strongest when we come together as one team with shared goals. Be the glue, not the glitter. But as a remote company, teamwork and collaboration won’t happen by accident. We approach every challenge as a shared challenge. We rely on each other for diverse perspectives and creative ideas. We celebrate our wins as a team.

We Care about Results

Be high productivity, low drama. Results matter. To keep our pace, everyone owns the outcomes of their actions and takes action when needed. We reward speed over perfection. We empower each other to iterate and experiment. You are welcome at Gremlin for who you are. The more voices and ideas we have represented in our business, the more we will all flourish, contribute, and build a more reliable internet.

Gremlin is a place where everyone can grow and is encouraged. However you identify and whatever background you bring with you, please apply if this sounds like a role that would make you excited to come into work everyday. It’s in our differences that we will find the power to keep building a more reliable internet by building and designing tools used by the best companies in the world.

Visit our website to learn more - https://www.gremlin.com/about

Interview prep

Walk in with sharper answers.

Use this as a quick practice sheet before you speak with the employer.

Mid
Technology & IT Project Management Remote Collaboration Data Scientist Technology Mid level

Likely questions

  1. Tell us about work you have done that is close to the Data Scientist, AI/ML role.
  2. How would you approach your first 30 days at Gremlin?
  3. Which of Project Management, Remote Collaboration and Data have you used recently, and what did it help you achieve?
  4. Describe a time you solved a problem without waiting to be told exactly what to do.
  5. How do you handle busy days, changing priorities, or pressure at work?

Prepare before the call

  • A recent example that proves your experience with Project Management, Remote Collaboration and Data.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the Data Scientist, AI/ML role because I can bring practical experience in Project Management, Remote Collaboration and Data, learn the team quickly, and contribute to the outcomes Gremlin needs from this hire.

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