Senior AI/Machine Learning Engineer at DevIQ

Denver, Colorado, United States -

Full Time

Start Date

Immediate

Expiry Date

12 Sep, 26

Salary

170000.0

Posted On

14 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Generative AI, Large Language Models, PyTorch, TensorFlow, Python, SQL, MLOps, RAG, Cloud Computing, Model Deployment, Feature Engineering, Data Exploration, Client Advisory, Model Monitoring, Statistics

Industry

Software Development

Description

Company 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. Job Description 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 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. Qualifications Required: Machine learning depth 4+ 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 delivery — RAG, embeddings, fine-tuning, and major model APIs (e.g., Anthropic, OpenAI, Bedrock) — with judgment to choose between prompting, retrieval, and fine-tuning. Strong Python and the modern ML stack (PyTorch or TensorFlow, scikit-learn), plus solid SQL. Experience deploying and monitoring ML workloads on at least one major cloud (AWS, Azure, or GCP), including versioning, drift monitoring, and retraining. Consulting and communication: Client-facing or consulting experience, able to explain technical trade-offs — including model limitations and uncertainty — to non-technical stakeholders Self-directed and comfortable with ambiguity across multiple engagements Willingness and ability to work beyond a narrowly defined AI/ML role, contributing to adjacent engineering, data, discovery, DevOps, consulting, and utility activities as needed in a project-based consulting environment. Preferred: Experience with Databricks, lakehouse architectures, or large-scale data engineering workflows Experience supporting pre-sales efforts (solution design, scoping, and estimating) Depth in one or more ML domains — e.g., NLP, computer vision, time-series forecasting, or recommender systems Research or open-source signal in ML — publications, patents, notable contributions, or competition results Bachelor's or Master's degree in Computer Science, Machine Learning, or equivalent practical experience Additional Information Est. Salary Range (Colorado Only): $140,000-$170,000* *Disclaimer: In accordance with Colorado’s Equal Pay for Equal Work Act, effective January 1, 2021, a good faith hourly or base salary range must be posted for all positions where the work may be performed in the state of Colorado. Therefore, this good faith salary range will only apply where this described position will be performed in the state, and should not be considered the compensation range in other locations or for other positions. DevIQ Benefits Include: Competitive financial compensation and utilization bonus plans Medical, Dental, Vision Insurance 401k, With 4% Matching Paid Time Off Health Savings Account (HSA)/Flexible Spending Account (FSA) Short-Term/Long-Term Disability Insurance Business funded Life Insurance Plan Dynamic yet relaxed work atmosphere Wide Variety of Growth Opportunities Compensation: USD 140000 - USD 170000 - yearly

Responsibilities

Design, build, and deploy end-to-end AI and machine learning solutions to solve business problems for clients. Act as a technical advisor, translating ambiguous business needs into scoped technical solutions and mentoring team members.