Lead Machine Learning Engineer job in Denver, CO
Are you an experienced machine learning professional ready to lead breakthrough innovations in artificial intelligence? We are seeking a Lead Machine Learning Engineer to join a high-performing tech team in Denver, CO. This is a unique opportunity to build intelligent systems that power real-world applications across diverse industries. If you’re passionate about solving complex problems, mentoring top engineering talent, and deploying scalable ML solutions, this role is your next big career move.
Shape the Future of AI in a Dynamic Denver Tech Environment
A leading technology company based in Denver, CO is looking for a Lead Machine Learning Engineer to architect, implement, and scale cutting-edge ML models and data pipelines. The ideal candidate brings deep expertise in machine learning, strong coding and algorithmic skills, and a track record of driving innovation from research to production. If you’re ready to make a lasting impact in a fast-growing company that values creativity and performance, this role is for you.
Key Responsibilities of the Lead Machine Learning Engineer – Denver, CO
ML Strategy & Vision:
Design and drive the strategic direction of machine learning initiatives aligned with business goals. Stay ahead of emerging AI/ML trends, champion best practices, and guide long-term roadmap development for scalable ML-driven solutions.
Model Development & Deployment:
Lead the end-to-end lifecycle of machine learning models—from data collection and preprocessing to training, validation, deployment, and monitoring. Ensure models are robust, explainable, and production-ready for real-time and batch inference environments.
Technical Leadership & Innovation:
Set technical standards and mentor a team of ML engineers and data scientists. Foster a culture of innovation, experimentation, and continuous learning to solve complex business problems with cutting-edge algorithms and techniques.
Cross-Functional Collaboration:
Work closely with product managers, data engineers, software developers, and business stakeholders to integrate ML capabilities into products and services. Translate business requirements into actionable machine learning tasks with measurable impact.
Scalability & Performance Optimization:
Design and implement scalable ML systems using cloud-native architectures and distributed computing frameworks. Optimize model performance and resource usage to meet latency and throughput requirements.
Data Strategy & Governance:
Oversee data acquisition, feature engineering, labeling, and quality assurance processes. Ensure the integrity, security, and ethical use of data across machine learning pipelines.
Experimentation & Evaluation:
Conduct rigorous A/B testing and model evaluation using statistical methods and real-world validation. Develop feedback loops and monitoring tools to track model performance and trigger retraining when necessary.
Documentation & Knowledge Sharing:
Maintain thorough documentation of ML experiments, model assumptions, and deployment processes. Promote knowledge sharing through internal workshops, code reviews, and technical write-ups.
Compliance & Responsible AI:
Ensure adherence to data privacy laws, ethical AI principles, and regulatory guidelines. Implement fairness, accountability, and transparency in model development and usage.
What the Client is Looking for in You
As the Lead Machine Learning Engineer, the client is seeking a highly skilled technical leader with a deep understanding of machine learning systems and a passion for solving complex challenges. You should be a hands-on engineer and a strategic thinker, capable of bridging the gap between research and production while inspiring a team of developers and data scientists to push the boundaries of innovation.
Proven Experience in Machine Learning Engineering
The ideal candidate brings several years of experience building, training, and deploying machine learning models at scale. You should be well-versed in supervised, unsupervised, and deep learning methods, and have a track record of implementing ML solutions that drive measurable business outcomes. Experience with cloud-based platforms, data pipelines, and MLOps best practices is essential.
Strategic Thinker with a Product-Focused Mindset
The client is looking for someone who not only understands machine learning at a technical level but can also think strategically about how it integrates with the product and business. You should be comfortable setting long-term technical direction, identifying opportunities for innovation, and aligning your team’s work with broader company goals.
Strong Coding, Architecture, and System Design Skills
You should demonstrate strong programming skills (in Python, Java, or similar languages) and familiarity with ML frameworks like TensorFlow, PyTorch, or Scikit-learn. The client values engineers who can architect scalable ML systems, optimize model performance, and ensure high reliability in production environments.
Leadership and Team Mentorship
The role requires someone who can lead by example—mentoring junior engineers, promoting collaboration across teams, and establishing a high-performance, inclusive engineering culture. Experience in team building, peer review, and driving technical excellence across projects will set you apart.
Data-Driven Decision Maker
You must be adept at using experimentation, statistical analysis, and A/B testing to validate your approaches and guide engineering decisions. The client is looking for someone who prioritizes measurable impact, iterative improvement, and actionable insights from data.
Strong Communication and Cross-Functional Skills
Collaboration is key. You’ll need to communicate complex technical concepts to non-technical stakeholders and work closely with product managers, analysts, and business leaders. The ability to translate business problems into ML tasks and communicate results effectively is a vital part of this role.
Commitment to Responsible AI and Compliance
The client places high importance on fairness, transparency, and compliance with data privacy standards. You should have a strong understanding of ethical AI principles and be committed to building trustworthy, bias-aware machine learning systems.
FAQs About the Role – Lead Machine Learning Engineer – Denver, CO
1. What are the key responsibilities of the Lead Machine Learning Engineer in this role?
As the Lead Machine Learning Engineer, you will be responsible for designing and implementing machine learning solutions, leading model development, and overseeing deployment into production systems. You will mentor a team of engineers, collaborate cross-functionally with product and data teams, and ensure scalability, performance, and reliability of ML pipelines. You will also play a strategic role in shaping the AI/ML roadmap for the company.
2. What qualifications and experience are required for this position?
The ideal candidate should have 5+ years of experience in machine learning or data science roles, with a solid background in computer science, statistics, or a related field. Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn is essential. Experience with cloud platforms (AWS, GCP, or Azure), MLOps practices, and leading machine learning projects from concept to production is highly preferred. A Master’s or Ph.D. in a related field is advantageous but not mandatory.
3. What leadership qualities are essential for this role?
The client is looking for a proactive and collaborative technical leader with strong problem-solving skills and a growth mindset. You should have the ability to mentor team members, communicate technical concepts to non-technical stakeholders, and align engineering initiatives with broader business goals. Initiative, curiosity, and a passion for innovation are highly valued.
4. What challenges can I expect in this role?
You may face challenges such as scaling models for high-volume data, optimizing latency and model accuracy, integrating ML solutions into legacy systems, and balancing technical complexity with business impact. Staying current with evolving ML technologies and ensuring ethical AI practices will also be ongoing priorities.
5. What is the expected impact of this role on the company’s technology and growth?
As the Lead Machine Learning Engineer, your work will directly influence product capabilities, customer experience, and operational efficiency. Your contributions to AI strategy, model innovation, and engineering best practices will help position the company as a technology leader and support long-term business growth.
6. What is the company’s culture and work environment like?
The company fosters a collaborative, data-driven, and innovation-oriented environment. Teams are encouraged to experiment, iterate, and share knowledge freely. You’ll join a passionate group of engineers and product thinkers who value autonomy, impact, and continuous learning.
What Remuneration Can You Expect from This Job?
As a Lead Machine Learning Engineer based in Denver, CO, you can expect a highly competitive compensation package reflective of your expertise, leadership, and contributions to high-impact machine learning initiatives. The remuneration for this role typically includes:
1. Base Salary
Lead Machine Learning Engineers in Denver typically command an annual base salary ranging from $150,000 to $200,000, depending on years of experience, technical depth, and company size. Top-tier firms or high-growth startups may offer salaries at the higher end of the spectrum or beyond.
2. Performance-Based Bonuses
In addition to a base salary, many companies offer annual performance bonuses tied to individual and company-wide goals such as model performance, system scalability, project delivery, and business impact. These bonuses usually range from 10% to 25% of the base salary and may increase with tenure and proven performance.
3. Equity & Stock Options
For companies with a growth-focused or startup mindset, equity compensation is a key part of the total package. This may include stock options or Restricted Stock Units (RSUs) that grow in value as the company scales. Equity aligns your contributions with long-term company success and offers the potential for substantial financial upside.
4. Long-Term Incentive Plans (LTIPs)
Some employers offer Long-Term Incentive Plans to reward sustained innovation and leadership in the AI/ML domain. These may be in the form of equity refreshers, bonus accelerators, or multi-year performance payouts, incentivizing retention and forward-thinking contributions.
5. Benefits & Perks
You can expect a robust benefits package that typically includes:
Comprehensive health, dental, and vision insurance
401(k) retirement plan with company matching
Paid time off (PTO), holidays, and sick leave
Remote or hybrid work flexibility
Professional development budgets for conferences, certifications, or training
Wellness programs, gym reimbursements, or mental health support
Commuter benefits or transportation allowances (where applicable)
6. Signing Bonus & Relocation Assistance
For top candidates, companies may provide a signing bonus or relocation assistance to ease your transition. Signing bonuses can range from $10,000 to $30,000, while relocation support may include housing assistance, travel reimbursement, or temporary lodging coverage.
Total Compensation Potential
When combining base salary, bonuses, equity, and additional incentives, the total compensation for a Lead Machine Learning Engineer can range from $175,000 to $300,000+ annually, with even higher upside in fast-growing or publicly traded organizations.
How to Apply
If you are an experienced and forward-thinking machine learning professional ready to lead innovative AI initiatives, we invite you to apply for the Lead Machine Learning Engineer role based in Denver, CO. This is a high-impact opportunity to drive cutting-edge ML solutions, shape data strategy, and contribute to scalable, real-world applications in a tech-driven environment.
To apply, please submit your updated resume and a cover letter outlining your experience in machine learning model development, deployment, team leadership, and collaboration with cross-functional teams. Be sure to highlight your expertise in model optimization, MLOps, cloud technologies, and your contributions to impactful ML projects in production environments.
This role offers a rewarding career path for engineers who thrive in innovative environments and want to lead AI strategies that make a difference. Apply today to advance your career as a Lead Machine Learning Engineer in Denver, CO!
For more information or to explore related opportunities, visit our Machine Learning Engineer Recruiters Page.
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Lead Machine Learning Engineer | AI Engineer Jobs | Machine Learning Careers | Data Science Leadership | ML Ops | AI Strategy | Python & TensorFlow | Model Deployment | AI Innovation | Tech Jobs Denver | Cloud-Based Machine Learning
