- Chicago, Illinois, United States +14 more
- $87K–$294K per year
- 5+ years
11–20 jobs· newest first
$87K–$294K
Hybrid · Principal
On-site · Full-time · Mid

Full-time · Senior
Manager
On-site · Full-time · Senior

Hybrid
+10K new in the last hour
Lead the development and implementation of responsible AI solutions, ensuring fairness, transparency, robustness, and privacy across client engagements.
Role Location California $94,400 to $293,800 Colorado $94,400 to $253,800 Connecticut $94,400 to $253,800 District of Columbia $100,500 to $270,300 Illinois $87,400 to $253,800 Maine $80,400 to $216,200 Maryland $94,400 to $253,800 Massachusetts $94,400 to $270,300 Minnesota $94,400 to $253,800 New York $87,400 to $293,800 New Jersey $100,500 to $293,800 Ohio $87,400 to $235,000 Virginia $87,400 to $270,300 Washington $100,500 to $270,300
Lead technology strategy and program management for Verizon’s Enterprise Architecture team, driving AI and generative solutions across the organization.
Support the development, integration, and deployment of machine learning capabilities for a government customer in Huntsville, Alabama.
Senior Data Scientist focused on generative AI, LLMs, MLOps, and AI solution architecture within EY GDS – Data and Analytics.
EY · Posted Nov 5, 2026
Senior Data Scientist with 8-11 years of experience in Data Science and Machine Learning, specializing in NLP, Generative AI, LLMs, MLOps, and AI solution architecture, responsible for designing, implementing, and optimizing AI solutions for enterprise use cases.
Accenture Infrastructure and Capital Projects, LLC · Posted Nov 4, 2026
Architect large language models that can process and generate natural language, design neural network parameters, and work with extensive datasets to ensure effective training.
Fine‑tunes Large Language Models with emphasis on instruction fine‑tuning and domain adaptation to enhance model relevance and performance in specific contexts.
Fine-tunes Large Language Models with emphasis on instruction fine-tuning and domain adaptation to enhance model relevance and performance in specific contexts.
Develop and maintain AI and computer vision components for embedded ADAS systems in automotive platforms.
Develop scalable and efficient AI pipelines for training, testing and deploying machine learning models in a production environment.
Competitive salary Discretionary Annual Bonus