Location: Jersey City, NJ / Remote Experience: 6 + years Employment Type: Contract Position Overview We are seeking an accomplished AI/ML Engineer with extensive experience in ML, DL, NLP, and GenAI solutionswithin the insurance domain—particularly underwriting and claims. The ideal candidate will lead through the full data science lifecycle, leveraging advanced language processing and large language models on platforms like AWS SageMaker and Databricks Key Responsibilities Design, develop, and implement end-to-end ML solutions across insurance underwriting and claims workflows. Apply NLP techniques including OCR-based extraction, document classification, and summarization. Build, fine-tune, and deploy LLMs and GenAI models, delivering domain-specific AI capabilities. Utilize cloud-based ML infrastructure such as AWS SageMaker and Databricks for scalable model development. Guide the full ML lifecycle—from data ingestion and preprocessing to prototyping, validation, and deployment. Partner with stakeholders to translate business requirements into AI-driven technical solutions. Optimize models for performance, accuracy, and alignment with business objectives. Produce clear technical documentation and mentor junior team members. Must-Have Qualifications Bachelor’s degree in Computer Science, Data Science, or a related field—Master’s preferred. 6–10 years of experience in AI/ML engineering, with a focus on NLP and GenAI implementations. Significant insurance domain experience, especially in underwriting and claims processing. Advanced proficiency in Python and ML libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Demonstrated hands-on experience with LLMs and generative AI projects. Skilled in NLP techniques: OCR, text extraction, classification, and summarization. Experience deploying scalable AI solutions on AWS SageMaker, Databricks, or equivalent environments. Palantir Foundry and AIP experience is a strong plus. Strong communication skills, with the ability to convey insights to both technical and non-technical audiences. Preferred Qualifications Experience in risk assessment or fraud detection applications within insurance. Understanding of regulatory requirements and compliance for AI systems in the insurance industry. Familiarity with computer vision, MLOps practices, and production-grade model monitoring. Application Process: Please submit your resume and a brief summary of relevant GenAI/NLP projects, particularly those applied to insurance underwriting or claims. Highlight your proficiency with LLMs, cloud ML platforms, and any Palantir Foundry/AIP exposure.