About the Company
A fast-growing technology firm is transforming how the global insurance market operates by automating complex workflows across sales, servicing, and claims. Starting with cutting-edge voice automation and now expanding into full end-to-end workflow automation, the team is pushing the boundaries of reasoning agents capable of managing the entire spectrum of insurance operations.
Location
Boston, MA or Berkeley, CA – hybrid schedule (2 days per week in-office)
The Role
We are seeking an experienced Data Scientist to drive large-scale Generative AI initiatives. You will design and build advanced LLM-powered conversational pipelines and automation systems that reshape how insurance tasks are performed. This is a hands-on, strategic role for someone who can both set a high-level vision and dive into the technical details.
- Key Responsibilities
- Design, architect, and build GenAI conversation pipelines across chat, voice and SMS using techniques such as multi-agent orchestration and retrieval-augmented generation (RAG).
- Develop scalable evaluation pipelines to measure the performance of enterprise-grade AI/ML solutions.
- Work closely with ML engineers to deploy, operate and continually optimize large-scale solutions.
- Collaborate with product managers to shape user journeys, design feedback loops, and analyse user telemetry.
- Deliver end-to-end AI/ML product experiences tailored to insurance workflows.
- 5+ years of industry experience delivering ML/AI solutions in production.
- Proven success in building and scaling GenAI or Agentic AI systems in a professional setting.
- Ability to think strategically while remaining hands-on with optimisation and implementation.
- Comfort working in a fast-moving, ambiguous environment and translating complexity into clear action.
- Strong communication skills for sharing innovations internally and externally.
- Deep understanding of machine learning algorithms and evaluation frameworks, including:
- Deep learning frameworks
- Supervised fine-tuning of LLMs
- Preference optimisation methods for domain adaptation in LLMs
- Track record of applying trustworthy AI/ML practices in collaboration with cross-functional stakeholders.
- Competitive base salary (range dependent on experience)
- Meaningful equity participation
- Comprehensive benefits package, including location-specific plan options
