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Machine Learning Petroleum Engineer Jobs in Decatur, MI

Varsity Tutors

Machine Learning Tutor

Kalamazoo, MI · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Sprinklr

Senior Data Scientist

Three Rivers, MI

They will engineer the underlying data sources, where needed, to support predictive capabilities ... Masters or PhD in a field that is emphasized in building and maintaining machine learning models ...

Varsity Tutors

Data Science Tutor

Kalamazoo, MI · Remote

$40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

SHUR-CO

Sewing Machine Operator I

South Haven, MI · On-site

$14.75 - $17.50/hr

Works closely with engineering for sewing specs. * Comfortable giving direction and or leading ... Shows interest in learning additional skills. * Shows good decision-making skills without ...

Motorola

Director of Voice AI

Three Rivers, MI

Our AI-powered security solutions integrate advanced video analytics, machine learning, and ... Technical Vision, Engineering Leadership, and Execution: Provide executive technical leadership to ...

New

Varsity Tutors

Python Tutor

Kalamazoo, MI · Remote

$40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

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Machine Learning Petroleum Engineer information

See Decatur, MI salary details

$29.1K

$118.8K

$178.6K

How much do machine learning petroleum engineer jobs pay per year?

As of Jun 4, 2026, the average yearly pay for machine learning petroleum engineer in Decatur, MI is $118,831.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,700.00 and $143,000.00 per year, depending on experience, location, and employer.

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.

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 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 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 job categories do people searching Machine Learning Petroleum Engineer jobs in Decatur, MI look for? The top searched job categories for Machine Learning Petroleum Engineer jobs in Decatur, MI are:
What cities near Decatur, MI are hiring for Machine Learning Petroleum Engineer jobs? Cities near Decatur, MI with the most Machine Learning Petroleum Engineer job openings:
Machine Learning Petroleum Engineer jobs near you
Machine Learning, Customer Success Engineer

Machine Learning, Customer Success Engineer

Stryker

Kalamazoo, MI

Full-time

Posted 7 days ago

Job description

First and most importantly: our mission is to bring transparency and clarity to the world's data. Our platform, FiftyOne, is where AI work happens . Our enterprise platform is the mission critical linchpin for managing unstructured data, model development, and AI systems at the world's largest companies.

We believe that open source is the way to lead the data‐centric AI revolution. Our open source version has 4 million downloads to-date. Our software massively impacts AI work across almost every vertical: from self‐driving cars to medical imaging to revolutionizing agriculture , we are at the thrilling center of real‐world AI advancement's next wave.

And we're built on three key tenets: We are all human beings : we strive to be a "human‐first" organization and treat everyone with the respect, care, and flexibility that all people deserve. We are distributed : We believe in the power of community . We are fully remote, hiring for people based in North America (with a preference for candidates on the West Coast for this role) who are prepared to travel to at least 2 in‐person retreats per year, plus travel to various conferences and Meetups.

About your role As a Machine Learning Customer Success Engineer at Voxel51, you'll work directly with our users, helping them identify best practices for their ML workflows using FiftyOne. You'll partner with teams doing incredible things all over the world - from global‐impact Fortune 100 companies to groundbreaking startups - helping them maximize their machine learning capabilities with FiftyOne. Internally, you'll serve as the voice of the customer, a critical role in shaping our product roadmap.

You'll also contribute to a thriving open source ML product and community, and continue to build out our functionality and ecosystem. Every member of our fully‐remote team is empowered to own their work and play an active role in advancing our mission to democratize data‐centric ML. What you will do 80% of your time Work with users to identify best practices to implement their ML workflows Run point on customer implementation, triaging bug reports, and day‐to‐day relationship management with users through channels like Slack, email, and weekly meetings Generate training material and onboarding sessions and deliver them to users Work with our product team to influence the roadmap and be the voice of the user within the organization 20% of your time Contribute ML‐specific features to our product, FiftyOne What you should bring Professional Computer Vision Machine Learning engineering experience (4 year+) Some customer‐facing experience (3 year+) BS or MS in computer science or a related field Proficiency with Python Expertise with machine learning and scientific computing libraries (TensorFlow, PyTorch, NumPy) Familiarity with NoSQL databases (MongoDB, DocumentDB, Elasticsearch) is a plus Experience maintaining or contributing to open source projects Ability to work in a remote‐first, cooperative environment using collaborative development tools (GitHub, Slack) #J-18808-Ljbffr

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