AI / ML Engineer

Job Description

We’re looking for a hands-on AI/ML Engineer to build and deploy production-grade machine learning solutions focused on extracting structured data from large, complex documents (e.g., multi-thousand-page PDFs).

This role will work across global teams (US, EU, India) and play a key part in scaling intelligent document processing using Python, AWS, and GenAI. The ideal candidate has strong experience taking ML models from concept to production and can operate confidently across the full ML pipeline with a focus on performance, scalability, and data quality.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

5+ years of experience in Machine Learning Engineering

Strong proficiency in Python (including ML/data libraries) [Senior ML...igence (1) | Word]

Solid experience with SQL and data modeling [Senior ML...igence (1) | Word]

Proven experience deploying ML models into production environments

Hands-on experience building end-to-end ML pipelines

Experience with GenAI applications, including:

Prompt engineering

Model selection and evaluation

Deployment and monitoring

Experience working with AWS for ML systems (e.g., SageMaker, Lambda, Step Functions)

Strong understanding of scalability and cost optimization in cloud environments

Ability to clearly articulate past projects and technical decisions

Self-starter mindset with ability to work autonomously in a highly hands-on (~80% technical) role Experience with multimodal ML (text + image processing)

Experience with document intelligence / OCR tools (Textract, Azure Document Intelligence, etc.)

Familiarity with RAG, transformers, or large language models (LLMs)

Experience processing large PDFs and image-based data (e.g., PyMuPDF, OpenCV, Pillow)

Background in document classification, segmentation, or extraction systems

Experience with evaluation frameworks, experimentation, or hypothesis testing

Exposure to big data tools on AWS (S3, Redshift, EMR, Glue)

Domain experience in insurance or healthcare