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Seldon was founded in 2014 with a simple yet ambitious mission: to accelerate the adoption of machine learning to solve the world’s most challenging problems. We’re committed to responsible, trustworthy, and holistic AI development. Our vision is a future where artificial intelligence transforms how we live, work, and interact, harnessed ethically by enterprise organizations and the open source community.
As machine learning becomes central to connected businesses, we seek talented individuals to advance our mission, delivering industry-leading MLOps solutions and making a significant impact in the space.
We foster a culture driven by passionate, talented teams and an open, collaborative ethos. Operating on the cutting edge of technology within an evolving agile environment, we offer unique opportunities for career growth and shaping the future of MLOps.
About the role
- Realize product vision: delivering production-ready machine learning models quickly, simplifying enterprise-grade MLOps.
- Design, build, and extend Seldon’s core MLOps tools and products.
- Assist enterprises in deploying machine learning models at scale across various use-cases and sectors.
- Advance the state of the art in MLOps, managing ML models throughout their lifecycle—from deployment to testing and updates.
Essential skills
- Degree or higher in a scientific or engineering field, or relevant experience.
- Experience designing complex systems from start to finish.
- Minimum of 4+ years industry experience.
- Strong proficiency in Golang.
- Experience with Kubernetes and Cloud Native tools.
- Building infrastructure with a focus on observability.
- Contributions to open source projects.
- Experience deploying machine learning tools in production.
- Broad understanding of data science and machine learning.
- Knowledge of explainable AI or ML monitoring in production.
- Familiarity with Python tools for data science.
High-profile projects
- Developing and maintaining a black box model explainability tool.
- Contributing to open source projects related to ML serving.
Technologies used
- Go for backend infrastructure, including our core services.
- Python for machine learning and related tools.
- Service mesh leveraging Envoy, Istio, or similar.
- gRPC protobuf for schema standardization.
- TypeScript and JavaScript for enterprise user interfaces.
- Kubernetes and related cloud native technologies for orchestration.
Location & Benefits
- London or Cambridge, UK - Hybrid working (2 days/week in-office).
- Impactful role with growth opportunities.
- Supportive, collaborative team environment.
- Learning and career development with a £1000 annual L&D budget.
- Flexible hybrid working arrangements.
- Share options aligned with company success.
- 28 days annual leave plus bank holidays.
- Enhanced parental leave, private medical insurance, life assurance (4x salary), pension scheme (5% employee / 3% employer).