Senior AI/Machine Learning Engineer

Company DescriptionDevIQ specializes in building modern cloud and data solutions – and we believe in the power of software and technology to improve lives. Join us to partner with passionate mid-market companies focused on reducing energy costs, curing disease, improving education, building smart cities, and more. From true innovation and synergetic cloud & technology partnerships to competitive full-time benefits and a strong team culture, DevIQ is a great place to work.At DevIQ, you’ll: Build your career with a supportive, inclusive team that appreciates people, creates value, embraces growth, and “owns the problem” as a team.Enjoy opportunities to learn, exposure to new industries, and building end-to-end solutions through meaningful work on active client projects.Work remotely and/or from our modern studio in downtown Denver.Bring your unique perspective and experience to multi-disciplinary teams.Collaborate on and contribute to transformative digital experiences that touch millions of lives, watching your work make an impact.Please note that you must be a U.S. citizen or eligible to work in the U.S. to be considered for this role, and third-party candidates will not be accepted.Job DescriptionWe’re looking for a hands-on Senior AI/Machine Learning Engineer to design, build, and deploy AI and machine learning solutions that solve real business problems for our clients. This is a consulting role that blends hands-on engineering, applied AI/ML expertise, and client-facing advisory work. You’ll partner directly with client stakeholders to understand their goals, translate ambiguous problems into well-scoped solutions, and see your work through from prototype to production. Success in this role depends as much on communication, empathy, and professionalism as it does on technical depth.Key Responsibilities: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 monitoringApply generative AI and LLMs where they fit the problem, selecting appropriate techniques and adapting as the field evolvesEstablish MLOps best practices: CI/CD for models, experiment tracking, model and drift monitoring, and responsible-AI practicesTranslate ambiguous business problems into well-scoped solutions, setting clear expectations on feasibility, timelines, and trade-offsServe as a trusted technical advisor — presenting demos and recommendations, and explaining models, their limitations, and uncertainty clearly to audiences from engineers to executivesMentor teammates and collaborate across multi-disciplinary teams of engineers, data scientists, and designersAdapt quickly to new industries, tools, and client environments while staying current with the evolving AI landscapeOperate 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.QualificationsRequired:Machine learning depth4+ years building, training, and deploying ML models in production — owning the modeling work, not just integrating model APIs.Strong modeling fundamentals: framing a problem as a learning task, feature engineering, model selection, and reasoning about bias/variance, regularization, and overfitting.Rigorous evaluation discipline: sound train/val/test methodology, avoiding data leakage, choosing metrics that fit the business goal, and error analysis to diagnose why a model underperforms.Deep learning fundamentals — architectures, loss functions, training dynamics — enough to build and debug models in PyTorch or TensorFlow, not just call them.Solid math/stats foundation (linear algebra, probability, statistics) and the judgment to know when ML is the right tool versus a simpler approach.Applied AI and engineering:Hands-on LLM/generative-AI