Remotely
machine learningmlopsfraud detectionpipelinesci/cdexperiment trackingfeature storesmodel registries
Job Description
📋 Description
- Lead and grow a multidisciplinary Identification Accuracy team spanning ML engineers, data
- Own the team’s technical roadmap with senior engineering leadership, improving model quality and
- Drive measurable model accuracy outcomes by designing, training, evaluating, and deploying ML
- Oversee production ML systems across data pipelines, feature engineering, model development
- Collaborate with platform and API engineering to meet requirements, performance, and latency
- Partner with Product and customer-facing teams to translate customer needs into technical
🎯 Requirements
- 5+ years in software engineering, ML, data science, or related field; at least 2 years leading an
- Proven experience delivering production ML systems from data pipelines to deployment.
- Strong track record building multidisciplinary teams of engineers, data scientists, analysts, and
- Deep technical understanding of ML and data systems; familiarity with MLOps, experiment tracking
- Experience with large-scale behavioral/event data; hands-on with data stack/tools like dbt.
- Excellent written and verbal communication; ability to convey trade-offs to technical and
🎁 Benefits
- Competitive compensation; US-based ranges: 159,000–215,000 USD.
- Fully remote with a globally distributed team.
- Opportunity to lead a multidisciplinary ML and data organization at scale.
- Exposure to cutting-edge ML, fraud detection, identity, and data technologies.
- High autonomy and influence over technical strategy and product outcomes.
- Inclusive environment valuing diverse experiences and backgrounds.
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