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Ml Platform Engineer Jobs in Colorado (NOW HIRING)

Senior AI/ML Platform Engineer

Denver, CO · On-site

$107K - $147K/yr

The Senior AI/ML Platform Engineer will help build and operate the technical foundation required to move AI/ML capabilities from project-based implementations into governed, observable, production ...

The Senior AI/ML Platform Engineer will help build and operate the technical foundation required to move AI/ML capabilities from project-based implementations into governed, observable, production ...

As a Machine Learning Platform Engineer, you will work closely with AI/ML engineers to rapidly build, deploy, and iterate high-quality ML/AI infrastructure solutions at scale, ensuring both ...

Software Engineer, ML Platform

Denver, CO · On-site +1

$190K - $240K/yr

As a Machine Learning Platform Engineer, you will work closely with AI/ML engineers to rapidly build, deploy, and iterate high-quality ML/AI infrastructure solutions at scale, ensuring both ...

... a Platform Engineer to design, build, and maintain the AWS infrastructure that underpins the IIA ... Preferred: familiarity with AI or ML infrastructure such as model serving, compute, and artifact ...

... a Platform Engineer to design, build, and maintain the AWS infrastructure that underpins the IIA ... Preferred: familiarity with AI or ML infrastructure such as model serving, compute, and artifact ...

Platform Engineering & Infrastructure * Augment existing infrastructure with with integrated ... Experience with AI/ML model deployment and monitoring in production environments Leadership ...

Senior Platform Engineer

Denver, CO · On-site

$130K - $180K/yr

Platform Engineering & Infrastructure * Augment existing infrastructure with with integrated ... Experience with AI/ML model deployment and monitoring in production environments Leadership ...

Senior Platform Engineer, AI

Denver, CO · On-site

$107K - $147K/yr

As a Senior AI Platform Engineer, you will be one of the first hires to build the infrastructure ... Experience deploying AI or ML systems in government, defense, or regulated environments with ...

... AI/ML Infrastructure Intelligence and Analytics (IIA) team builds and operates the data platform ... The Platform Engineer VI serves as the offshore lead for IIA platform engineering, responsible for ...

Senior Agentic AI Engineer

Englewood, CO · On-site

$116K - $158K/yr

This is a hands-on role, not a management position, that requires deep Databricks platform expertise, production data engineering skill, and practical AI and ML platform knowledge. What Success Looks ...

As a Staff AI Platform Engineer, you will be one of the first hires to build the infrastructure ... Experience deploying AI or ML systems in government, defense, or regulated environments with ...

Senior Agentic AI Engineer

Englewood, CO · On-site

$116K - $158K/yr

This is a hands-on role, not a management position, that requires deep Databricks platform expertise, production data engineering skill, and practical AI and ML platform knowledge. What Success Looks ...

This is a hands-on role, not a management position, that requires deep Databricks platform expertise, production data engineering skill, and practical AI and ML platform knowledge. What Success Looks ...

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Ml Platform Engineer information

See Colorado salary details

$34

$67

$99

How much do ml platform engineer jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for ml platform engineer in Colorado is $67.25, according to ZipRecruiter salary data. Most workers in this role earn between $53.08 and $77.60 per hour, depending on experience, location, and employer.

What is an ML Platform Engineer?

ML Platform Engineers are specialized software engineers who design, build, and maintain the infrastructure and tools needed to support the development, deployment, and scaling of machine learning models. They bridge the gap between data science and production engineering by automating model training, monitoring, versioning, and serving. Their work enables data scientists to focus on modeling while ensuring that ML solutions are reliable, reproducible, and scalable in real-world environments.

What skills and qualifications are needed to thrive as an ML Platform Engineer?

To thrive as an ML Platform Engineer, you need a strong background in computer science, software engineering, and machine learning concepts, often supported by a degree in a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), containerization (Docker, Kubernetes), CI/CD pipelines, and knowledge of ML frameworks (TensorFlow, PyTorch) are commonly required. Collaboration, problem-solving, and strong communication skills help you work efficiently with data scientists, engineers, and stakeholders. These skills ensure the development, scalability, and reliability of robust ML infrastructure that empowers teams to deploy and manage models effectively.

How does an ML Platform Engineer typically collaborate with data scientists and software engineers within a company?

ML Platform Engineers work closely with both data scientists and software engineers to streamline the process of developing, deploying, and maintaining machine learning models. They provide the infrastructure and tools necessary for data scientists to build and experiment with models efficiently, while ensuring seamless integration with production systems managed by software engineers. Regular communication, participation in cross-functional meetings, and shared project management tools are common ways teams collaborate. This close collaboration helps to bridge the gap between research and production, ensuring robust, scalable, and reliable ML solutions.

What is the difference between Ml Platform Engineer vs Data Scientist?

AspectML Platform EngineerData Scientist
Required credentialsBachelor's/Master's in CS, Engineering, or related; experience with cloud platformsBachelor's/Master's in Statistics, Math, or CS; strong programming skills
Work environmentBuilds and maintains ML infrastructure, collaborates with engineering teamsAnalyzes data, develops models, and interprets results
Industry usageTech companies, AI startups, enterprises deploying ML systemsResearch institutions, tech firms, data-driven organizations

ML Platform Engineers focus on developing and maintaining the infrastructure that supports machine learning models, while Data Scientists primarily analyze data and build models. Both roles often collaborate but serve different functions within the AI and data ecosystem.

What are popular job titles related to Ml Platform Engineer jobs in Colorado?

For Ml Platform Engineer jobs in Colorado, the most frequently searched job titles are:

What cities in Colorado are hiring for Ml Platform Engineer jobs?

Cities in Colorado with the most Ml Platform Engineer job openings:

Senior AI/ML Platform Engineer

bp

Denver, CO • On-site

$107K - $147K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 11 days ago


BP rating

5.5

Company rating: 5.5 out of 10

Based on 192 frontline employees who took The Breakroom Quiz

74th of 87 rated oil and gas companies


Job description

Job Family Group:
IT&S Group
Job Description:
bpx energy, a major oil and gas producer in the United States, demonstrates its expertise in unconventional gas, including shale, to deliver hydrocarbon production and technical knowledge worldwide. With operations in Texas and Louisiana, our US onshore business has become both a best-in-class oil and gas producer and a leader in reducing methane emissions. As part of BP, a global industry leader, we champion a high-energy, high-intensity environment built on accountability, collegiality, and empowerment.
Role Overview
bpx energy is building an enterprise AI capability that can scale safely and deliver real operational value. The Senior AI/ML Platform Engineer will help build and operate the technical foundation required to move AI/ML capabilities from project-based implementations into governed, observable, production-grade enterprise capabilities.
This is a hands-on platform engineering role focused on the systems, patterns, environments, controls, and automation required for production AI/ML delivery. The role will work across Palantir, Snowflake, Databricks, AWS, and related AI/ML services to create the "paved roads" that allow teams to be versatile and quick-moving.
This role will not focus on building one-off AI use cases. It is focused on making AI/ML engineering repeatable, reliable, secure, and scalable across the enterprise.
What You'll Do
Build, operate, and evolve AI/ML platform capabilities across Palantir, Databricks, AWS, MLflow, model registries, model serving, feature management, vector stores, and related services.
  • Create reusable platform patterns for model development, deployment, serving, monitoring, access controls, and production support.
  • Implement CI/CD, infrastructure automation, environment management, secrets management, access controls, and deployment templates for AI/ML workloads.
  • Partner with security, infrastructure, data, and enterprise architecture teams to ensure AI/ML platforms are secure, observable, auditable, and operationally reliable.
  • Support batch, real-time, streaming, and API-based model deployment patterns.
  • Establish standard engineering patterns for experiments, notebooks, jobs, pipelines, model serving, and production promotion.
  • Help define platform usage standards, tiered access models, cost controls, observability requirements, and operational support patterns.
  • Ensure AI/ML workloads are designed for reliability, scalability, performance, maintainability, and governance.
  • Support future federated AI/ML engineering by creating reusable templates, reference architectures, and enablement materials for domain teams.

Minimum Requirements
  • Bachelor's degree in engineering, computer science, information systems, or related field, or equivalent work experience.
  • Proven experience building, operating, or enabling production AI/ML engineering platforms in a cloud environment.
  • Hands-on experience with at least one modern AI/ML platform such as Databricks, AWS SageMaker, MLflow, Azure ML, Vertex AI, or equivalent.
  • Practical experience with CI/CD, infrastructure automation, environment management, secrets management, access controls, and production deployment patterns.
  • Experience supporting model development and deployment workflows beyond experimentation or notebooks.
  • Strong understanding of cloud-native architecture, APIs, containers, compute patterns, storage patterns, and runtime observability.
  • Ability to build reusable engineering patterns, templates, reference architectures, and platform "paved roads."
  • Experience partnering with data engineering, security, infrastructure, and architecture teams to move AI/ML workloads into governed production environments.
  • Proven track record to troubleshoot platform, deployment, performance, integration, or reliability issues in sophisticated technical environments.

Strongly Preferred
  • Databricks platform engineering experience, including workspaces, clusters/serverless, Unity Catalog, MLflow, model serving, jobs/workflows, permissions, and cost controls.
  • AWS experience with IAM, networking, security groups, S3, Lambda, ECS/EKS, API Gateway, Bedrock, SageMaker, or related services.
  • Experience supporting regulated, safety-sensitive, industrial, energy, financial, healthcare, or other high-consequence operating environments.
  • Experience with platform cost management and workload optimization.
  • Experience creating reusable platform enablement materials for engineers, data scientists, or domain technical teams.

Additional Role Scope Information
This is not a traditional software engineering, application development, BI, or data engineering role. It is also not a notebook-only experimentation role.
This role is not a fit for candidates whose experience is primarily:
  • Traditional application/software engineering without hands-on AI/ML platform, MLOps, or ModelOps experience.
  • Generic cloud or DevOps engineering without production AI/ML deployment or platform experience.
  • Data science experimentation without responsibility for production deployment patterns.
  • Data pipeline engineering without exposure to model development, model serving, or AI/ML lifecycle operations.
  • Single-use-case delivery without experience creating reusable platform capabilities.

Adjacent backgrounds are welcome when the candidate can demonstrate direct experience helping AI/ML workloads move into governed, observable, production-grade environments.
Salary and Benefits
We offer a reward and wellbeing package to enable your work to fit with your life. These can include, but not limited to, access to health, vision and dental insurance, flexible working schedule, paid time off policy, discretionary annual bonus program, long-term incentive program, and a generous 401K matching program. How much do we pay (Base)? $135,000 - $175,000
*Note that the pay range listed for this position is a good faith and reasonable estimate of the range of possible base compensation at the time of posting.
Travel Requirement:
Negligible travel should be expected with this role
Relocation Assistance:
Relocation may be negotiable for this role
Remote Type:
This position is a hybrid of office/remote working
Skills:
Cloud Platforms, Cloud Platforms, Collaboration, Communication, Configuration management and release, Continuous deployment and release, Creating a high performing team, Database Design, Digital Project Management, Documentation and knowledge sharing, Emerging technology monitoring, Facilitation, Information Security, Mentoring, Metrics definition and instrumentation, NoSql data modelling, Problem Solving, Relational Data Modelling, Risk Management, Scripting, Secure development, Service operations and resiliency, Software Design and Development, Solution Architecture, Source control and code management {+ 5 more}
Legal Disclaimer:
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, socioeconomic status, neurodiversity/neurocognitive functioning, veteran status or disability status. Individuals with an accessibility need may request an adjustment/accommodation related to bp's recruiting process (e.g., accessing the job application, completing required assessments, participating in telephone screenings or interviews, etc.). If you would like to request an adjustment/accommodation related to the recruitment process, please contact us.
If you are selected for a position and depending upon your role, your employment may be contingent upon adherence to local policy. This may include pre-placement drug screening, medical review of physical fitness for the role, and background checks.

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