Principal Machine Learning Engineer
Accelerant3 months ago
United Kingdom (city not specified)Staff+
Responsibilities
- Own the ML platform from data and feature pipelines through training infrastructure, model registry and lineage, inference services, and deployment.
- Design and build integrations with Accelerant’s platform, third-party providers, and systems owned by other engineering teams.
- Establish model versioning, staged rollouts, rollback procedures, and deployment practices.
- Build monitoring that distinguishes data drift, pipeline failures, and genuine model performance decay, including when labels are delayed.
- Develop infrastructure for agentic AI, including orchestration, tool and API integration, retrieval, caching, and cost and latency controls.
- Own reliability, cost, and performance across batch scoring and low-latency ML services.
- Create model governance and audit trails for regulators and internal risk committees.
- Lead and grow a small engineering function by setting standards, coaching engineers, and partnering with data scientists.
Requirements
- Substantial experience running machine learning systems in production, including post-launch operations.
- Strong engineering foundations in Python, infrastructure as code, containers, orchestration, and at least one major cloud provider.
- Data engineering experience with pipelines, orchestration, storage and access patterns, and SQL proficiency.
- Experience integrating systems across organizational boundaries and influencing teams without direct authority.
- Statistical literacy sufficient to evaluate model performance with data scientists.
- Experience leading or coaching engineers and making sound infrastructure cost and reliability decisions.
- Willingness to work with LLMs and agentic AI as everyday tools.
- Strong communication skills and credibility to assess whether systems are production-ready.
Benefits
- Ownership of an engineering function with freedom to determine how it operates.
- A strong team of data scientists and collaborators across engineering, actuarial, underwriting, and product functions.
- High autonomy and low bureaucracy on a lean, senior team.
- Opportunity to shape AI and ML foundations across more than 20 countries and 250 specialty insurance products.
- Work spanning overnight batch scoring, low-latency services, and agentic systems.
Categories
About Accelerant
Accelerant builds a data-driven risk exchange for specialty insurance, connecting MGAs and underwriters with aligned risk capital and software to run their programs. Its platform ingests and analyzes underwriting and claims data to support pricing, capacity allocation, and operations, and it partners closely with specialty underwriting teams. Founded in 2018 and headquartered in Atlanta, the company focuses on improving efficiency and profitability for program-based insurance businesses.