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

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Applied Scientist (Integrity)

Prolific is building the human data infrastructure that powers the next generation of AI systems. As frontier AI labs scale their use of human-generated data for training, evaluation, and alignment, the way we measure quality, performance, and operational efficiency becomes increasingly important.

The Role

You’ll join Prolific’s Integrity team, which protects the platform from fraud and misuse. This is a new role focused on verification - in particular identifying and validating high quality expert participants. This is an emerging area, so part of the role will be to shape the problem space:  working with other teams to find,validate and model useful signals for participant quality. The ideal candidate will help define the right problems to solve, not just execute against a fixed brief.

The Applied Scientist role combines data science, ML and statistics to build practical systems that drive real business outcomes. This isn’t a pure research role, although you may explore papers and explore new ideas. The focus is on turning promising approaches into production ready solutions. It is also not an ML engineering role: you don’t need engineering experience, but you should understand what deploying a model involves and the practical constraints around it. We care about approaches that actually work in production, not ones that are too slow or expensive to run, and about the judgement to tell the difference.

How You’ll Work

• You’ll be the first data person in this area, so you’ll help shape the role and create structure where there isn’t much yet, with support from leadership. You don’t need to have all the answers on day one.
• You spot problems worth solving and start on them, rather than waiting to be assigned.
• You will be comfortable (and ideally enjoy) collaborating with others.

What We are looking for

• Deep expertise in one applied ML, statistics, or data science specialism. Examples could be risk modelling, LLM detection, and reinforcement learning, but any area of genuine depth counts
• Judgement about when to reach for simple statistics, classical ML, LLMs, or agentic approaches.
• 3+ years applying ML, AI research, or data science to real problems.
• Python skills sufficient to build, test, and iterate on working prototypes independently.
• Able to take a loosely defined product or customer problem and turn it into clear hypotheses, experiments, and metrics.
• You must be comfortable working on ambiguous problems, and suggesting solutions rather than waiting to be told exactly what to do.

Nice to have

• An MSc or PhD in Computer Science, Maths, Statistics, ML, or a related field — or equivalent knowledge gained another way.
• Experience working alongside product and engineering teams.

Why Prolific is a great place to work

We’ve built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.

We believe that the next leap in AI capabilities won’t come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity.

Working for us will place you at the forefront of AI innovation, providing access to our unique human data platform and opportunities for groundbreaking research. Join us to enjoy a competitive salary, benefits, and remote working within our impactful, mission-driven culture.

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By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific’s Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal information.

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