Senior Applied AI Engineer

Acuity Analytics

1d

About The Position

You’ll work at the intersection of data science, data engineering, AI engineering, and operations, embedded closely with our DaaS Delivery Operations team and cross-functional stakeholders. You’ll design and build the technical foundations that power our data products—developing data pipelines, quality systems, evaluation frameworks, and ML-assisted solutions that directly improve delivery outcomes and operational efficiency. This role is highly execution-focused and ideal for someone who enjoys building end-to-end systems, solving complex data and ML problems in production environments, and working closely with delivery teams to unblock work through strong technical implementation. You should be comfortable owning solutions from design through deployment and iteration, with minimal reliance on hand-offs.

Requirements

• 5+ years in data science, data engineering, or ML engineering roles
• Strong proficiency in Python and SQL
• Hands-on experience with data tooling (pandas, Plotly, Streamlit, Dash)
• Practical experience working with LLMs and deploying ML solutions in production environments
• Experience integrating and working with APIs and technical systems
• Strong problem-solving skills with a bias toward implementation and delivery
• Excellent collaboration and communication skills in cross-functional teams

Responsibilities

• Build and maintain scalable data pipelines and transformation workflows
• Implement data quality checks, validation frameworks, and monitoring systems
• Design and operationalize evaluation frameworks for datasets and ML outputs
• Package and deliver production-ready datasets with clear documentation and QA standards
• Develop ML-assisted tools and workflows to improve data processing and delivery efficiency
• Generate, augment, and validate synthetic datasets to support client and internal use cases
• Deploy lightweight ML/LLM-powered solutions to solve operational bottlenecks
• Improve automation and repeatability across data workflows
• Work directly with delivery teams to implement and maintain production workflows
• Debug, troubleshoot, and resolve technical issues across data pipelines and systems
• Continuously improve tooling, processes, and measurement approaches used in delivery
• Identify and implement practical improvements that increase speed, reliability, and quality of delivery outcomes

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed
• Number of Employees: 1,001-5,000 employees