Data Scientist, AI/ML

Bazeta; Northern (KY); Remote; USD 220,000 - 290,000; Full time

Benefits offered by this job

401k Matching

Equity

Flexible time off

Paid company holidays

Job summary

Gremlin is seeking a Data Scientist, AI/ML to advance our reliability platform by turning chaos experiment data into automated failure analysis and remediation strategies.

You will work with distributed systems data, applying causal inference, graph ML, and time-series modeling to build production-ready AI features that reduce blast radius and accelerate recovery.

Qualifications

• 5+ years of professional experience building and productionizing machine learning for distributed systems
• Hands-on experience with causal inference, graph ML, time-series modeling, or reinforcement learning
• Experience building data pipelines and feature stores to support offline training and real-time inference

Responsibilities

• Analyze Gremlin's large chaos engineering dataset to identify failure patterns and resilience signals
• Pretrain and fine-tune ML models to automatically detect and classify failures
• Build intelligent systems delivering automated remediation recommendations and orchestration
• Develop scalable data pipelines and feature stores for training and real-time inference
• Collaborate with platform engineers and SREs to integrate AI-driven failure analysis into the product
• Advance techniques including causal AI, agentic systems, and productionizing ML approaches

Skills

ML for distributed systems

Causal inference

Graph ML

Time-series modeling

Reinforcement learning

Data pipelines

Feature stores

Agile development

Experimentation discipline

Tools

Model serving

Monitoring

Job description

4. Data Scientist, AI/ML# Data Scientist, AI/ML## DescriptionData Scientist, AI/MLJob 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/MLAs 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 strategiesWe'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 milestonesBonus 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.CompensationWe 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 PeoplePeople 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...Source: Jobicy (https://jobicy.com/jobs/152746-data-scientist-ai-ml)