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Machine Learning Petroleum Engineer Jobs in Berkeley, CA

Articul8

Machine Learning Engineer

Dublin, CA · On-site

We are seeking machine learning engineers to join our team full-time. As part of your role, you will help us build pipelines of data collection, data extraction, data filtering/synthetic data ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

They are seeking Machine Learning Engineers to build their platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to core technology and product features.

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Latent

Machine Learning Engineer

San Francisco, CA · On-site

$225K - $300K/yr

Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For ...

Gotion, Inc.

Machine Learning Engineer

Fremont, CA · On-site

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

They are seeking Machine Learning Engineers to build their platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to the development of key technologies and ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

The Machine Learning Engineer will play a central role in building the core technology for training, evaluating, and deploying interpretable frontier AI systems, contributing to tools, infrastructure ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

They are seeking a Machine Learning Engineer to contribute to the development of tools and infrastructure for interpretable AI systems, playing a key role in transforming research into usable product ...

Apple

Machine Learning FEA Engineer

San Francisco, CA · On-site

We are committed to pushing the boundaries of innovation and engineering excellence in product designs through machine learning and FEA simulations. We truly believe in the power of predictive ...

Gotion, Inc.

Machine Learning Engineer

Fremont, CA · On-site

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Eve

Machine Learning Engineer

San Francisco, CA

We're hiring an Machine Learning Engineer as the volume and complexity of legal AI workflows in our system scale rapidly. As more firms rely on Eve to automate high-stakes legal work - from intake ...

Canals

Machine Learning Engineer

San Francisco, CA · Remote

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining high quality, owning end-to-end ML pipelines while shaping product features that deliver real-world ...

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Showing results 21-40

All JobsMachine Learning Petroleum Engineer JobsMachine Learning Petroleum Engineer Jobs in Berkeley, CA

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 Sep 2, 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.

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.

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 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 Petroleum Engineer jobs near you

Machine Learning Engineer

Articul8

Dublin, CA • On-site

Full-time

Re-posted 17 days ago

Job description

About us:
At Articul8 AI, we relentlessly pursue excellence and create exceptional AI products that exceed customer expectations. We are a team of dedicated individuals who take pride in our work and strive for greatness in every aspect of our business. We believe in using our advantages to make a positive impact on the world and inspiring others to do the same.
Job Description:
We are seeking machine learning engineers to join our team full-time. As part of your role, you will help us build pipelines of data collection, data extraction, data filtering/synthetic data generation and data analysis. You will own all work related to acquiring high-quality data to power the training of our domain-specific models end to end. You will work closely with other researchers and engineers to empower our next generation of domain-specific models. We value rapid prototyping, iterating, and shipping new systems quickly.
Required Qualifications:
  • BS/MS/PhD in Computer Science or a related field.
  • Proficiency in at least one deep learning framework, such as PyTorch.
  • Experience in machine learning projects in text or vision, e.g., has trained machine learning models to tackle a specific problem.
  • Strong expertise in large stateful distributed systems and data processing.
  • Strong proficiency in building large-scale data processing pipelines, familiar with distributed workload (e.g., multiprocessing, Ray, Docker, Kubernetes).
  • Proficiency in at least one programming language commonly used in machine learning, such as Python and ability to write clean, maintainable code.
  • Excellent problem-solving skills and attention to detail, especially when handling data anomalies and biases to further improve data quality.

Key Competencies
  • Active Github contributions are a big plus.
  • Experience in building large-scale datasets.
  • Familiar with at least one of the following tools for data crawling (e.g. Scrapy), data collection (e.g., VPNs, Selenium), data processing (e.g., Hadoop, Datasketch).
  • Building bespoke data processing libraries from scratch.
  • Keeping up with state-of-the-art techniques for preparing AI training data.
  • Organizing and meticulously bookkeeping data across multiple clouds, of multiple modalities, and from many sources.
  • Multilingual which contributes to enriching the language diversity crucial for robust model training.

Responsibilities:
  • Design and develop data processing pipelines, including data extraction, data filtering, data labeling, etc.
  • Implement machine learning models to improve the quality and diversity of data (especially in the data extraction stage), e.g., quality classifier, document layout model, code verification model, etc.
  • Own and lead engineering projects in the area of data acquisition, including web crawling, data ingestion, and processing.
  • Collaborate with our Applied Research, Technology, and Architecture teams to ensure smooth data flow and system operability.
  • Develop and deploy highly scalable distributed systems capable of handling terrabytes of data.
  • Architect and implement algorithms for data indexing and search capabilities.
  • Build and maintain backend services for data storage, including work with key-value databases and synchronization.
  • Deploy solutions in a Kubernetes Infrastructure-as-Code environment and perform routine system checks.

By joining our team, you become part of a community that embraces diversity, inclusiveness, and lifelong learning. We nurture curiosity and creativity, encouraging exploration beyond conventional wisdom. Through mentorship, knowledge exchange, and constructive feedback, we cultivate an environment that supports both personal and professional development.
Your future experience at Articul8 will include continuous learning and growth opportunities as we embark on an exciting journey to disrupt the status quo. If you're excited about joining a team that's passionate about making a difference, we want to hear from you.
If you're ready to join a team that's changing the game, apply now to become a part of the Articul8 team. Join us on this adventure and help shape the future of Generative AI in the enterprise.

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