IND Applied AI Scientist

The Hartford India; Hyderabad; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

The Hartford India is seeking an IND Staff Engineer GCC094 to lead sophisticated ML initiatives and productionize models at scale. You will work on a range of data science problems, from NLP to GenAI-enabled solutions, leveraging Python, PyTorch/TensorFlow, and modern cloud platforms.

Ideal candidates bring 3+ years of deep learning experience, unstructured data handling, model monitoring, and the ability to communicate results to both technical and business audiences within an enterprise

Qualifications

• Experience in statistical modeling and machine learning using Python, including pandas, NumPy, scikit-learn; strong SQL for data exploration and feature development.
• 3+ years of experience applying deep learning architectures in real-world use cases.
• Experience end-to-end modeling lifecycle: problem framing, requirements, experimentation, offline evaluation, production validation and monitoring.
• Experience designing model evaluation and monitoring approaches, including metrics, A/B testing, drift detection, and performance tracking.
• Experience with unstructured data, including document parsing, OCR basics, and handling PII considerations.
• Experience with Git and Unix-based development, reproducible notebooks/pipelines; 3+ years exposure to container and cloud fundamentals for deployment.
• Ability to communicate modeling decisions and outcomes to technical and non-technical audiences, translating analytics into business impact.
• Experience with cloud-native AI platforms (Vertex AI, SageMaker/Bedrock, Azure AI) for experimentation, training, and deployment.
• Experience deploying models into production within enterprise environments (e.g., Duck Creek, Ratabase).
• Experience with NLP and Generative AI: embeddings, retrieval strategies, chunking, prompts, and RAG solutions.

Skills

Statistical modeling

Machine learning

Python

SQL

Model evaluation & monitoring

Communication (technical and non-tech)

Tools

Pandas

NumPy

scikit-learn

PyTorch

TensorFlow

Git

Unix

Docker

Job description

IND Staff Engineer - GCC094

Job Description

We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.

• Experience in statistical modeling and machine learning using Python, including extensive use of pandas, NumPy, scikit-learn, and strong SQL for data exploration, feature development, and knowledge preparation; familiarity with PyTorch and/or TensorFlow preferred.
• Experience across the end-to-end modeling lifecycle, including problem framing and requirements gathering, experiment design, offline evaluation, and ongoing production validation and monitoring.
• Solid understanding and practical application of core machine learning methods, with 3+ years of experience applying deep learning architectures in real-world use cases.
• Experience designing and operationalizing model evaluation and monitoring approaches, including test set creation (gold and/or synthetic), metric definition and tracking (e.g., classification, forecasting, ranking/IR, and business KPIs), and supporting A/B testing, drift detection, and performance regression monitoring.
• Experience working with unstructured data, including document parsing and OCR fundamentals, text normalization, metadata and lineage awareness, and PII detection or redaction considerations.
• Experience using Git and Unix-based development environments, with experience building reproducible notebooks or pipelines and ensuring repeatable analytical workflows; 3+ years of exposure to basic container and cloud fundamentals supporting deployment workflows
• Experience communicating modeling decisions, design tradeoffs, evaluation results, and risks to both technical and non-technical audiences, and translating analytical outcomes into measurable business impact.
• Experience working with cloud-based AI platforms such as Google Vertex AI, AWS SageMaker or Bedrock, or Azure AI Services, supporting experimentation, model training, and deployment.
• Experience deploying models and integrating scoring logic into production systems, including operation within complex enterprise or packaged application environments (e.g., Duck Creek, Ratabase).
• Experience with NLP and Generative AI capabilities, including embeddings, retrieval strategies (dense and hybrid), chunking approaches, prompt engineering, structured outputs, and contributing to Retrieval-Augmented Generation (RAG) solutions and evaluations.
• Experience or exposure to advanced GenAI applications and extensions, such as agent or tool-use concepts, domain-specific knowledge graph integration, synthetic data generation, sentiment modeling, and GenAI use cases in filing or compliance contexts.
• Experience working within enterprise AI governance expectations, including aligning model development with compliance, privacy, documentation, and ethical standards.