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Machine Learning Petroleum Engineer Jobs in Minnesota

Machine Learning Engineer

Golden Valley, MN · On-site

$119K - $122K/yr

Tennant Company seeks a full-time Machine Learning Engineer based in Golden Valley, MN. Responsible for utilizing experience in emerging technologies such as Cloud computing, Big Data, Deep Machine ...

Machine Learning Engineer

Golden Valley, MN · Hybrid

$119K - $122K/yr

Tennant Company seeks a full-time Machine Learning Engineer based in Golden Valley, MN. Responsible for utilizing experience in emerging technologies such as Cloud computing, Big Data, Deep Machine ...

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

Machine Learning Engineer

Golden Valley, MN · Hybrid

$119K - $122K/yr

Tennant Company seeks a full-time Machine Learning Engineer based in Golden Valley, MN. Responsible for utilizing experience in emerging technologies such as Cloud computing, Big Data, Deep Machine ...

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Senior Machine Learning Engineer

Minneapolis, MN · On-site

$109K - $149K/yr

As a Senior Machine Learning Engineer, you will design, develop, test, document, deploy, and maintain production machine learning and statistical modeled software to automate processes and streamline ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

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Machine Learning Petroleum Engineer information

Will AI take over petroleum engineering jobs?

AI can automate certain tasks in petroleum engineering, such as data analysis and reservoir modeling, but it is unlikely to fully replace engineers. Human expertise remains essential for decision-making, problem-solving, and overseeing complex operations. Petroleum engineers will need to adapt by developing skills in AI tools and data management.

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.

Do ML engineers get paid well?

Machine Learning engineers typically earn high salaries due to their specialized skills in AI, data analysis, and programming. Salaries vary based on experience, location, and industry, but they are generally above average compared to other engineering roles.

What engineers make $500,000 a year?

Highly experienced senior engineers in specialized fields such as petroleum engineering, software engineering, or data science can earn $500,000 or more annually, especially with bonuses, stock options, or in leadership roles. Achieving this level typically requires advanced skills, extensive experience, and working in high-paying industries or companies.

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 engineers make $300,000 a year?

Senior petroleum engineers, especially those with extensive experience, specialized skills, and leadership roles, can earn $300,000 or more annually. Machine learning petroleum engineers working in the oil and gas industry with advanced expertise and in high-paying companies may also reach this salary level, often supplemented by bonuses and profit sharing.

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 cities in Minnesota are hiring for Machine Learning Petroleum Engineer jobs? Cities in Minnesota with the most Machine Learning Petroleum Engineer job openings:
Machine Learning Engineer

Machine Learning Engineer

Solution Design Group

Minneapolis, MN • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 19 days ago


Job description

SDG is a high-performance software community. We are a team of collaborative and creative consultants who build and deliver custom software for some of the most recognizable local and national brands. In this role, you will be asked to leverage your current skills while also learning new ones. Working in over 500 different technologies and continually learning together, you can expect a one-of-a-kind and award-winning work experience. Our team at SDG has exceptional integrity and the desire to create the best possible customer solutions. We are proud to partner with our customers to consistently provide a successful working relationship as a high-performance team.
We are adding a Machine Learning Engineer to our team! This person will play a key role in designing, implementing, and deploying machine learning models to solve complex problems and enhance our customer's products and services. You will be a part of a tight-knit technical community, giving you the opportunity to constantly grow your development amongst top technical talent. You will work closely with a cross-functional team of data scientists, software engineers, and domain experts to drive the development and deployment of machine learning solutions. SDG is looking for a hard worker with a team-oriented mindset, that has at least 3 years of experience and an in-depth understanding of machine learning and cloud data tools. A successful Machine Learning Engineer at SDG is a lifelong learner who is motivated to continually improve their craft and thrives amongst their fellow employee-owners.
SDG's Machine Learning Engineer's have proven experience with the following responsibilities. If you do too, we want to hear from you:
  • Design, implement, and optimize machine learning algorithms and models to address specific business challenges.
  • Collaborate with data engineers to preprocess and transform raw data into a format suitable for machine learning models. Conduct feature engineering to extract relevant information for model training.
  • Train, validate, and fine-tune machine learning models using state-of-the-art techniques. Evaluate model performance and iterate on models to improve accuracy and efficiency.
  • Deploy machine learning models into production environments and integrate them into existing systems. Collaborate with software engineers to ensure seamless integration with our products.
  • Stay abreast of the latest developments in machine learning and related fields. Proactively identify opportunities to enhance existing models and propose new approaches to solve business problems.

Requirements:
  • 3+ years of hands-on, professional machine learning development experience, delivering solutions in a large scale enterprise environment
  • Experience with Public Cloud Providers such as AWS and Microsoft Azure
  • Experience with AWS and/or Azure data tools and services
  • Demonstrated experience using AI-assisted development tools (e.g., Claude Code, Codex, GitHub Copilot) to increase development velocity, improve code quality, and support complex problem-solving
  • Strong understanding of data processing, data engineering, and data visualization.
  • Experience with SQL and NoSQL databases
  • Proficient in programming languages such as Python and R
  • Familiarity with big data technologies such as Apache Spark
  • Experience with Machine Learning frameworks such as TensorFlow or PyTorch
  • Ability to work effectively in a collaborative, cross-functional team environment. Excellent communication skills and the ability to explain complex concepts to both technical and non-technical stakeholders.
  • Strong analytical and problem-solving skills. Proven ability to tackle complex problems and deliver robust machine learning solutions.
  • Prior consulting or professional services experience is a bonus
  • Education degree or certification in Computer Science, or the equivalent related work experience

What's in it for you?
  • Full-time salaried consultant position
  • A true stake in success. SDG is an ESOP - 100% employee owned
  • Star Tribune Top Workplace winner the last 7 consecutive years
  • National Top Workplace in 2023, 2024 & 2025
  • Engaged teammates who care about quality solutions
  • Challenging and rewarding work with great customers
  • Various opportunities to give back to the community
  • Be amongst some of the best technologists in the industry
  • Dedicated to our core values of superior customer service, exceptional employee experience, and responsible corporate citizenship
  • Opportunities to connect with other SDGer's via internal communities, committees, and events - virtually and in person

SDG is proud to offer an array of benefits for our employees including but not limited to medical, dental, and vision insurance benefits, paid time off, paid holidays, short and long-term disability, life insurance options, a monthly technology reimbursement allowance, 401k, birth and non-birth parent leave, ESOP, trainings and certifications, and company-owned cabins. Fair and equitable compensation is important to us. The salary range for this opportunity is $130,000 - $170,000. The offer may fall outside this range given factors such as skills and experience. The salary range is subject to change and may be modified at any time.
Applicants must be authorized to work for ANY employer in the United States. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.