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Machine Learning Petroleum Engineer Jobs in Berkeley, CA

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift: N/A Location: San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role Visa ...

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only h1 candidate About the Role: Our direct client is hiring a Machine Learning Engineer for their ...

Machine Learning Engineer Location: Fremont, CA once the documents are verified, a Codility assessment will be shared with the candidate, where they need to score a minimum of 70% and post that, a ...

About the Role We're looking for a Machine Learning Engineer to design, build, and deploy production-grade ML systems that power the next generation of Plenful's AI platform. You'll own the end-to ...

New

Job Title Machine Learning Engineer Job ID 20985 Location Work Mode Onsite About the Team Our ML Platform team builds intelligent systems that power recommendations, forecasting, ranking ...

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions for quality assurance and process monitoring in additive manufacturing. Working closely with process ...

We're looking for an exceptional Machine Learning Engineer to help build the systems that make this possible. In this role, you'll develop models, signals and evaluation frameworks that power ...

Machine Learning Engineer

San Francisco, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply ...

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Showing results 1-20

Machine Learning Petroleum Engineer information

See Berkeley, CA salary details

$38.6K

$157.7K

$236.9K

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

As of Aug 9, 2026, the average yearly pay for machine learning petroleum engineer in Berkeley, CA is $157,670.00, according to ZipRecruiter salary data. Most workers in this role earn between $124,300.00 and $189,800.00 per year, depending on experience, location, and employer.

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?

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 Berkeley, CA? For Machine Learning Petroleum Engineer jobs in Berkeley, CA, the most frequently searched job titles are:
What cities near Berkeley, CA are hiring for Machine Learning Petroleum Engineer jobs? Cities near Berkeley, CA with the most Machine Learning Petroleum Engineer job openings:

Machine Learning Engineer

Recruiting from Scratch

San Francisco, CA • On-site

Full-time

Re-posted 22 days ago


Job description

Job Summary:
Recruiting from Scratch represents a dynamic and innovative company in the healthcare AI sector that is on a mission to transform healthcare operations through advanced machine learning. The Machine Learning Engineer will develop and optimize machine learning models to enhance healthcare operations and collaborate with cross-functional teams to integrate solutions into existing workflows.
Responsibilities:
• Develop and optimize machine learning models using Python, PyTorch, and TensorFlow to enhance healthcare operations.
• Collaborate with cross-functional teams to integrate machine learning solutions into existing workflows and systems.
• Conduct experiments and analyze data to improve model performance and accuracy.
• Implement best practices in machine learning and software engineering to ensure high-quality deliverables.
• Participate in code reviews and contribute to a culture of continuous improvement and innovation.
Qualifications:
Required:
• 3+ years of experience in machine learning engineering or a related field.
• Proficient in Python and experienced with frameworks such as PyTorch and TensorFlow.
• Strong understanding of machine learning algorithms and their applications in real-world scenarios.
• Experience in developing and deploying scalable machine learning models.
Preferred:
• Familiarity with healthcare data and understanding of industry-specific challenges.
• Experience with cloud platforms and deployment of machine learning solutions in production environments.
• Knowledge of data preprocessing and feature engineering techniques.
Company:
A recruiting agency working with technology companies to help them hire software engineers, data roles, product managers, and hardware. Founded in 2021, the company is headquartered in Albany, USA, with a team of 11-50 employees. The company is currently Early Stage.

Recruiting from Scratch logo

About Recruiting from Scratch

Sourced by ZipRecruiter

Recruiting from Scratch is a premier talent firm that focuses on placing the best product managers, software, and hardware talent at innovative companies. Our team is 100% remote and we work with teams across the United States to help them hire. We work with companies funded by the best investors including Sequoia Capital, Lightspeed Ventures, Tiger Global Management, A16Z, Accel, DFJ, and more.

Industry

Recruiting and staffing services

Company size

11 - 50 Employees

Headquarters location

New York, NY, US

Year founded

2021

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