DevIQ
Technology
SeniorAI/MachineLearningEngineer
Neural analysis suggests this role is
optimal for mid candidates.
“Senior AI/Machine Learning Engineer at DevIQ. Skills: Machine learning, AI, MLOps, Generative AI. Own ML solutions end to end. Explore data”
What You'll Achieve.
Solve real business problems; See work through to production
Industry & Context.
Translate ambiguous problems; Rigorous error analysis
U. S. citizen or eligible to work, Third-party candidates not accepted
What They're Looking For.
Must Have
4+ years building ML models, Modeling fundamentals, Rigorous evaluation discipline, Deep learning fundamentals, Solid math/stats foundation, Hands-on LLM/generative-AI delivery, Python and modern ML stack, Solid SQL, Experience deploying ML workloads on cloud, Client-facing or consulting experience, Self-directed and comfortable with ambiguity
Nice to Have
Experience with Databricks, Lakehouse architectures experience, Large-scale data engineering workflows experience, Experience supporting pre-sales efforts, Depth in ML domains, Research or open-source signal in ML, Master's degree in Computer Science, Master's degree in Machine Learning, Master's degree in equivalent practical experience
What You'll Do.
Own ML solutions end to end
Iterate based on error analysis
Production deployment
Apply generative AI and LLMs
Select appropriate techniques
Establish MLOps best practices
Responsible-AI practices
Translate business problems into solutions
Set expectations on feasibility
Set expectations on timelines
Set expectations on trade-offs
Serve as technical advisor
Present recommendations
Explain model limitations
Explain model uncertainty
Collaborate across teams
Adapt to new industries
Adapt to client environments
Stay current with AI landscape
Operate as consulting engineer
Contribute to discovery
Contribute to data exploration
Contribute to data engineering
Contribute to application development
Contribute to solution documentation
Contribute to technical analysis
Contribute to internal tooling
Contribute to client-supporting utility tasks
How You'll Work.
Team & Collaboration
Multi-disciplinary teams; Client stakeholders; Engineers; Data scientists; Designers; Executives
Communication Scope
Client-facing advisory; Presenting demos; Explaining models; Explaining limitations; Explaining uncertainty
Process & Methodology
Scoping, Estimating
Full Job Description
DevIQ 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. We’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 produ
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