ZipRecruiter

Log In

1

Machine Learning Petroleum Engineer Jobs in Michigan

Eccalon LLC

Machine Learning Engineer

Detroit, MI · On-site

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Stefanini

Machine Learning Engineer

Dearborn, MI

Stefanini is looking for a Machine Learning Engineer, Dearborn, MI (Onsite) For quick apply, please reach out Saurabh Kapoor at / You will be responsible for designing, building, deploying, and ...

Indeed

Machine Learning Engineer

Detroit, MI

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

Stefanini

Machine Learning Engineer

Dearborn, MI

$105K - $126K/yr

Stefanini is looking for a Machine Learning Engineer (Dearborn, MI) For quick apply, please reach out to Adil Khan at / We are seeking a Machine Learning who can build scalable and robust ML data ...

Ascentt

Senior Machine Learning Engineer

Ann Arbor, MI

$102K - $140K/yr

Senior Machine Learning Engineer Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions ...

FastTek

Machine Learning Engineer

Dearborn, MI

$105K - $126K/yr

Machine Learning Engineer #1054987 * Employees in this job function are responsible for designing, building, deploying, and scaling complex self-running ML solutions -- including Generative AI and ...

next page

Showing results 1-20

All JobsMachine Learning Petroleum Engineer JobsMachine Learning Petroleum Engineer Jobs in Michigan

Machine Learning Petroleum Engineer information

How does a Machine Learning Petroleum Engineer typically collaborate with geoscientists and drilling teams to optimize oil and gas production?

A Machine Learning Petroleum Engineer works closely with geoscientists and drilling teams by integrating data-driven models into exploration and production workflows. They analyze geological, seismic, and operational data to develop predictive algorithms that identify optimal drilling locations, forecast reservoir performance, and improve recovery rates. Regular collaboration involves translating complex data insights into actionable recommendations that guide drilling strategies and inform real-time decisions, ensuring all teams are aligned to maximize efficiency and safety. This multidisciplinary approach fosters continuous learning and innovation across teams.

What is the difference between Machine Learning Petroleum Engineer vs Reservoir Engineer?

AspectMachine Learning Petroleum EngineerReservoir Engineer
Required CredentialsBachelor's/Master's in Petroleum Engineering, Data Science, or related fields; knowledge of machine learningBachelor's/Master's in Petroleum Engineering or Geosciences; strong understanding of reservoir simulation
Work EnvironmentData analysis, modeling, software development in oil & gas companiesReservoir modeling, field development planning in oil & gas operations
Industry UsageApplying machine learning to optimize extraction, predict reservoir behaviorEstimating reservoir properties, managing production strategies

The Machine Learning Petroleum Engineer focuses on integrating data science and machine learning techniques to optimize oil extraction processes, while the Reservoir Engineer specializes in modeling and managing subsurface reservoirs to maximize recovery. Both roles are vital in the oil & gas industry but differ in their core skills and daily tasks.

What is a Machine Learning Petroleum Engineer?

A Machine Learning Petroleum Engineer is a specialist who combines expertise in petroleum engineering with machine learning and data science techniques. They use advanced algorithms and data analytics to optimize oil and gas exploration, drilling, production, and reservoir management. Their work helps improve decision-making, reduce operational costs, and increase efficiency by analyzing large datasets from various sources such as sensors, seismic data, and production logs. These professionals often work closely with geoscientists, data engineers, and other stakeholders in the energy sector.

What are the key skills and qualifications needed to thrive as a Machine Learning Petroleum Engineer, and why are they important?

To thrive as a Machine Learning Petroleum Engineer, you need a strong background in petroleum engineering, programming (such as Python or R), and applied machine learning, usually supported by a relevant engineering degree. Familiarity with data analysis platforms, machine learning frameworks (like TensorFlow or Scikit-learn), and petroleum industry software (such as Petrel or Eclipse) is essential. Strong analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for integrating technical insights with business goals. These competencies enable the effective application of data-driven solutions to optimize exploration, production, and operational efficiency in the energy sector.
What are popular job titles related to Machine Learning Petroleum Engineer jobs in Michigan? For Machine Learning Petroleum Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Machine Learning Petroleum Engineer jobs in Michigan look for? The top searched job categories for Machine Learning Petroleum Engineer jobs in Michigan are:
What cities in Michigan are hiring for Machine Learning Petroleum Engineer jobs? Cities in Michigan with the most Machine Learning Petroleum Engineer job openings:
Machine Learning Petroleum Engineer jobs near you
Machine Learning Engineer

Machine Learning Engineer

HTC Global Services

Dearborn, MI • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 22 days ago

Job description

Job Title
Machine Learning Engineer
Overview / Summary
We are seeking an experienced Machine Learning Engineer to design, implement, and maintain scalable machine learning and analytics pipeline solutions. The ideal candidate will have expertise in machine learning engineering, cloud platforms, DevSecOps practices, and data engineering technologies. This role involves building and optimizing ML infrastructure, deploying production-grade machine learning solutions, and collaborating with cross-functional teams to improve processes and business outcomes.
Key Responsibilities
  • Collaborate with business and technology stakeholders to understand current and future machine learning requirements.
  • Design and develop machine learning models and software algorithms to solve complex business problems in structured and unstructured environments.
  • Design, build, maintain, and optimize scalable machine learning pipelines, architectures, and infrastructure.
  • Apply machine learning techniques in areas such as computer vision, perception, localization, virtual reality, augmented reality, object detection, tracking, classification, and terrain mapping.
  • Deploy machine learning models and algorithms into production environments and conduct simulations for testing and validation.
  • Automate model deployment, training, and retraining using CI/CD/CT methodologies and MLOps practices.
  • Implement model management processes, including versioning and traceability across environments.
  • Develop, build, and maintain machine learning infrastructure, including data pipelines, deployment platforms, and monitoring solutions.
  • Develop and maintain tools and libraries that support machine learning development and deployment.
  • Automate machine learning workflows using DevSecOps principles and practices.
  • Collaborate with development and operations teams to improve system integration and automate ML pipelines.
  • Design, develop, and manage data flows and APIs between systems and applications.
  • Troubleshoot and resolve issues related to system communication, data flow, and data quality.
  • Collaborate with technical and non-technical stakeholders to gather requirements and ensure successful deployment of data solutions.
  • Create and maintain technical documentation for software components.
  • Ensure systems comply with evolving business needs, data governance policies, and security requirements.
  • Implement and maintain high standards of data quality and integrity.
  • Manage deliverables through project management tools.

Required Qualifications
  • Bachelor's degree in Computer Science, Information Systems, or a related field.
  • 3+ years of experience developing and deploying machine learning models in production environments.
  • 3+ years of Python programming experience.
  • 2+ years of hands-on experience with Google Cloud Platform (GCP), including services such as BigQuery, Google Cloud Storage, Cloud Composer, and/or Cloud Run.
  • Experience using version control systems such as GitHub.
  • 2+ years of experience with code quality and security scanning tools such as SonarQube, Cycode, or FOSSA.
  • 3+ years of experience with data engineering technologies such as Kubernetes, Container-as-a-Service (CaaS) platforms, OpenShift, DataProc, Spark (PySpark), or Airflow.
  • Experience with CI/CD tools and practices, including Tekton or Terraform.
  • Experience with containerization technologies such as Docker and Kubernetes.
  • Strong analytical, troubleshooting, and problem-solving skills.
  • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Familiarity with Atlassian tools such as Jira and Confluence.
  • Experience working in Agile environments.

Preferred Qualifications
  • Master's degree in Computer Science, Data Science, Engineering, or a related field.
  • Experience with machine learning libraries such as TensorFlow, PyTorch, or Scikit-learn.
  • Experience with MLOps tools and platforms.
  • Experience working in fast-paced environments with multiple priorities.
  • Demonstrated commitment to continuous learning and professional development.
  • Strong problem-solving skills and passion for technical excellence and innovation.

What Makes HTC A Great Place To Build Your Future
HTC Global Services wants you to join our team. Come build new things with us and advance your career. At HTC Global, you'll collaborate with experts, work alongside clients, and be part of high-performing teams driving success together. You'll have long-term opportunities to grow your career and develop skills in the latest emerging technologies.
At HTC Global Services, our employees have access to a comprehensive benefits package. Benefits can include Group Health (Medical, Dental, and Vision), Paid Time Off, Paid Holidays, 401(k) matching, Group Life and Disability insurance, Professional Development opportunities, Wellness programs, and a variety of other perks.
Our success as a company is built on inclusion and diversity. HTC Global Services is committed to providing a workplace free from discrimination and harassment, where every employee is treated with dignity and respect. We celebrate differences and believe that diverse cultures, perspectives, and skills drive innovation and success. HTC is an Equal Opportunity Employer and a proud National Minority Supplier. We seek to empower each individual, fostering an environment where everyone feels valued, included, and respected.
#LI-Hybrid #LI-SK8

Apply