Applied AI Data Scientist

This is a fully remote position, open to applicants in Connecticut, +3 more states.

📋 Description

• Construct and enhance machine learning, deep learning, and generative AI models utilizing contemporary frameworks such as PyTorch, TensorFlow, and scikit-learn.

• Create and implement retrieval-augmented generation (RAG) pipelines, hybrid retrieval systems, and vector-based search workflows.

• Develop intelligent AI solutions that encompass tool orchestration, reasoning processes, and secure execution strategies.

• Conduct structured experiments employing evaluation metrics like BERTScore, BLEURT, semantic similarity, and retrieval precision/recall.

• Incorporate solutions within Google Cloud Platform (GCP) using Vertex AI, Workbench, and Vector Search, as well as Amazon Web Services (AWS) utilizing SageMaker and Bedrock.

• Establish ingestion, enrichment, and semantic retrieval workflows aimed at high-quality knowledge and feature engineering.

• Collaborate with both onshore and offshore data science and machine learning engineers to maintain quality, consistency, and shared technical methodologies.

⛳️ Requirements

• 3–5+ years of experience in Data Science, Machine Learning Engineering, Applied AI, or Generative AI roles.

• Proficient in Python and SQL; experienced with deep learning and machine learning libraries.

• Practical experience in constructing RAG systems, vector search pipelines, and generative AI applications.

• Familiarity with contemporary large language model (LLM) platforms such as Vertex AI, OpenAI, Bedrock, and Azure OpenAI.

• Experience in applying evaluation methodologies for both machine learning and generative AI.

• Capability to convert ambiguous business challenges into well-defined machine learning or generative AI solutions.

• Experience in designing multi-step agent workflows and reasoning pipelines.

• Strong foundation in statistics, experimental design, and feature engineering.

• Ability to clearly communicate complex concepts to both technical and business stakeholders.

• Comfortable collaborating with agile teams and coordinating across different time zones.

• Experience working with subject matter experts to validate and refine AI outputs.

• Familiarity with Snowflake or other enterprise data platforms is preferred.

• Knowledge of the insurance domain, including underwriting, claims, or risk analysis, is preferred.

• Experience with multimodal large language models or enterprise prompt/agent frameworks is preferred.

🏝️ Benefits

• Health insurance

• 401(k) matching

• Flexible working hours

• Paid time off

• Professional development opportunities

• Short-term or annual bonuses

• Long-term incentives

• On-the-spot recognition