DevIQ

Machine Learning Engineer

• Own ML solutions end to end — framing the business problem, exploring data, training and evaluating models, and iterating based on rigorous error analysis — through to production deployment and monitoring
• Apply generative AI and LLMs where they fit the problem, selecting appropriate techniques and adapting as the field evolves
• Establish MLOps best practices: CI/CD for models, experiment tracking, model and drift monitoring, and responsible-AI practices
• Translate ambiguous business problems into well-scoped solutions, setting clear expectations on feasibility, timelines, and trade-offs
• Serve as a trusted technical advisor — presenting demos and recommendations, and explaining models, their limitations, and uncertainty clearly to audiences from engineers to executives
• Mentor teammates and collaborate across multi-disciplinary teams of engineers, data scientists, and designers
• Adapt quickly to new industries, tools, and client environments while staying current with the evolving AI landscape
• Operate as a flexible consulting engineer within DevIQ’s delivery model, contributing beyond AI/ML when project needs and team availability require it, including adjacent work such as discovery, data exploration, data engineering, application development, DevOps, solution documentation, technical analysis, internal tooling, or other client-supporting utility tasks.

Senior AI/Machine Learning Engineer

Full-stack Engineer

• Lead the architecture, design, and implementation of modern software solutions for clients, serving as the senior technical voice on consulting engagements
• Use agentic AI tools (Claude Code, Codex, Cursor, or similar) as a primary development workflow, delegating implementation, testing, and refactoring tasks to agents while maintaining rigorous quality standards
• Design codebases to be agent-friendly, with clear conventions, strong automated test coverage, and documentation that enables AI tooling to work effectively
• Establish review and verification practices for AI-generated code, ensuring correctness, security, and maintainability in everything the team ships
• Build and maintain prompts, custom agents, and CI/CD integrations that automate routine engineering work across client projects
• Serve as a trusted advisor to clients, communicating complex technical concepts clearly to both technical and non-technical stakeholders, setting realistic expectations, and building lasting relationships
• Listen actively and empathetically to client needs, asking thoughtful questions and translating business goals into pragmatic technical roadmaps
• Mentor and coach engineers on AI-native development practices, raising the velocity and quality of every team you work with
• Partner with sales and leadership on pre-sales activities, including technical discovery, solution design, and estimating
• Foster a collaborative, inclusive team culture, giving and receiving feedback constructively, navigating disagreement respectfully, and owning the problem as a team
• Evaluate emerging AI development tools and patterns and decide which earn a place in the stack

Senior AI/Machine Learning Engineer

Lead AI-Native Software Engineer