IND Lead Engineer
The Hartford (company site, opens in a new tab)On-siteDirect career pageEst. 25–45 LPA
Posted 20h ago
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Job description
Structured overview of role & requirements
About This Role
- Lead the end-to-end lifecycle of AI and machine learning models focusing on statistical modeling, feature engineering, validation, and production monitoring.
- Design, develop, and deploy advanced conversational AI solutions including chatbots, virtual assistants, and Retrieval-Augmented Generation (RAG) pipelines in regulated insurance environments.
- Implement business intelligence and semantic layer solutions within data warehouses or lakes, ensuring compliance with AI governance frameworks and operational KPIs tracking.
Minimum Requirements
- Proficient in Python with experience in pandas, NumPy, scikit-learn, and strong SQL skills; familiarity with PyTorch and/or TensorFlow preferred.
- Experience in AI/ML lifecycle including experiment design, offline evaluation, and production monitoring in regulated industries like insurance.
- Knowledge of cloud-based AI/analytics platforms such as Google Vertex AI, AWS SageMaker or Azure AI Services.
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in practical application of machine learning, deep learning, and NLP algorithms specifically within insurance or regulated settings.
- Skilled in advanced NLP, Generative AI, embeddings, RAG, and conversational AI solution deployment with a focus on compliance and ethical standards.
- Capable of communicating complex technical AI/ML concepts clearly to both technical and non-technical stakeholders, aligning AI solutions with business strategy.