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Machine Learning Petroleum Engineer Jobs in Riverside, CA

Data Scientist II

Irvine, CA · On-site +1

$82K - $127K/yr

Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field; Master's preferred * 2-5+ years of experience in data science, machine learning, or ...

Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field; Master's preferred * 2-5+ years of experience in data science, machine learning, or ...

Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field; Master's preferred * 2-5+ years of experience in data science, machine learning, or ...

This KPI-driven team leverages Machine Learning (ML) to deliver personalized experiences. The role involves building end-to-end solutions, collaborating with data scientists and engineers, and ...

We are looking for an AI-Powered Software Engineer who treats AI agents as a primary development ... Stay updated with the latest advancements in AI and machine learning and continuously improve AI ...

AI-First Software Engineer

Irvine, CA · On-site

$150K - $250K/yr

We are looking for an AI-Powered Software Engineer who treats AI agents as a primary development ... Stay updated with the latest advancements in AI and machine learning and continuously improve AI ...

AI-First Software Engineer

Irvine, CA · On-site

$150K - $250K/yr

We are looking for an AI-Powered Software Engineer who treats AI agents as a primary development ... Continuous Improvement : Stay updated with the latest advancements in AI and machine learning and ...

LHH is seeking a Director of Engineering, AI/ML, in a full-time capacity. In this role, you'll lead ... You will oversee the entire machine learning lifecycle, from concept to deployment, with strategic ...

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Showing results 1-20

Machine Learning Petroleum Engineer information

See Riverside, CA salary details

$32.9K

$134.3K

$201.9K

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

As of Jun 27, 2026, the average yearly pay for machine learning petroleum engineer in Riverside, CA is $134,341.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,900.00 and $161,700.00 per year, depending on experience, location, and employer.

Is ML a high paying job?

Machine Learning Petroleum Engineers typically earn high salaries due to their specialized skills in data analysis, modeling, and the oil and gas industry. Compensation varies based on experience, location, and certifications, but overall, it is considered a well-paying role within engineering fields.

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 engineers make $500,000?

Senior petroleum engineers, especially those with extensive experience, advanced technical skills, and leadership roles, can earn salaries of $500,000 or more annually. High compensation is often associated with working in major oil and gas companies, offshore environments, or in executive positions that require specialized expertise and certifications.

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 machine learning petroleum engineers with extensive experience, advanced skills in data analysis and modeling, and often working in leadership roles or specialized environments can earn $300,000 or more annually. High compensation typically involves working for major energy companies, possessing relevant certifications, and contributing to complex projects that impact production and exploration strategies.

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.

Will AI take over petroleum engineering?

AI can assist petroleum engineers by improving data analysis, reservoir modeling, and automation of routine tasks. However, the role of a petroleum engineer involves complex decision-making, field supervision, and problem-solving that require human expertise, making complete automation unlikely in the near future.
What are popular job titles related to Machine Learning Petroleum Engineer jobs in Riverside, CA? For Machine Learning Petroleum Engineer jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Petroleum Engineer jobs in Riverside, CA look for? The top searched job categories for Machine Learning Petroleum Engineer jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Machine Learning Petroleum Engineer jobs? Cities near Riverside, CA with the most Machine Learning Petroleum Engineer job openings:
Senior Staff Algorithm Engineer

Senior Staff Algorithm Engineer

Becton, Dickinson and Company

Irvine, CA • On-site

$112K - $154K/yr

Full-time

Posted 17 days ago


BD rating

7.2

Company rating: 7.2 out of 10

Based on 136 frontline employees who took The Breakroom Quiz

268th of 419 rated machine equipment manufacturers


Job description

We are the people who give possibilities purpose
BD is one of the largest global medical technology companies in the world. Advancing the world of health™ is our Purpose, and it's no small feat. It takes the imagination and passion of all of us-from design and engineering to the manufacturing and marketing of our billions of MedTech products per year-to look at the impossible and find transformative solutions that turn dreams into possibilities.
Job Description
Summary:
We are seeking a highly experienced Senior Staff Algorithm Engineer with deep expertise in physiological signal processing, biomedical sensor data, and classical machine learning to help develop next-generation medical technologies for continuous patient monitoring, disease detection, and predictive clinical insights.
In this role, you will design, develop, validate, and deploy algorithms that extract meaningful physiological parameters and clinical insights from complex, noisy, real-world sensor data. You will work with multi-modal data streams from monitoring sensors, bedside devices, wearable systems, electronic health records, and clinical datasets, with a primary focus on signal processing, statistical modeling, feature engineering, and interpretable machine learning approaches.
This role is ideal for an experienced engineer who understands both the physics of sensing and the physiology behind the signals, and who can translate raw waveform data into reliable, clinically useful metrics for regulated medical technology products.
Key Responsibilities
  • Lead the design, development, validation, and deployment of algorithms forcontinuous physiological monitoring, new monitoring parameters and derived vital signs, signal quality assessment, artifact detection and rejection, multi-parameter trend analysis.
  • Develop robust algorithms using physiological waveform and sensor data.
  • Apply advanced signal processing techniques such as filtering and denoising, adaptive filtering, spectral analysis, time-frequency analysis, wavelet analysis, etc.
  • Build classical machine learning and statistical models for clinically relevant algorithm outputs, including, logistic regression, support vector machines, random forests, gradient boosting methods, probabilistic models, clustering and anomaly detection, time-series forecasting models.
  • Translate physiological and clinical understanding into meaningful algorithm features, performance requirements, model constraints, and interpretable outputs.
  • Develop end-to-end algorithm pipelines for data ingestion, synchronization, waveform preprocessing, segmentation, signal quality assessment, feature extraction, model training, validation, performance characterization, and robustness testing.
  • Work closely with clinical, systems engineering, software, embedded engineering, data science, regulatory, and quality teams to ensure algorithms are clinically meaningful, technically feasible, and suitable for regulated product development.
  • Optimize algorithms for edge and embedded medical devices with constraints on latency, memory, compute, battery life, and real-time performance, as well as for cloud-based platforms supporting scalable analytics and retrospective evaluation.
  • Support verification, validation, documentation, risk analysis, design controls, and clinical performance evaluation for regulated medical technology products.
  • Conduct root-cause analysis of algorithm performance issues using real-world clinical data and field data.
  • Contribute to intellectual property, technical strategy, algorithm roadmaps, scientific publications, and external technical engagement.
  • Mentor junior engineers and help establish best practices for physiological signal processing and algorithm development.

Minimum Required:
  • Bachelors degree in Electrical Engineering, Biomedical Engineering, Signal Processing, Computer Engineering, Applied Mathematics, Statistics, Physics, or a related quantitative or engineering discipline.
  • 10+ years of industry experience in signal processing, algorithm development, biomedical engineering, medical devices, physiological monitoring, or related technical areas.
  • Deep expertise in digital signal processing and algorithm development for real-world sensor data.
  • Strong hands-on experience with physiological waveforms and biomedical signals such as ECG, PPG, respiration, blood pressure, capnography, or other patient monitoring signals.
  • Strong understanding of human physiology, particularly as it relates to cardiopulmonary function, hemodynamics, respiratory physiology, patient monitoring, and acute care.
  • Demonstrated experience developing algorithms from feasibility through productization, clinical validation, or deployment.
  • Experience designing robust signal processing pipelines for noisy, artifact-prone, real-world physiological data.
  • Strong background in feature engineering, statistical modeling, and classical machine learning.
  • Experience evaluating algorithm performance using clinically relevant metrics such as sensitivity, specificity, positive predictive value, negative predictive value, AUROC, calibration, false alarm burden, limits of agreement, and robustness across subgroups and use conditions.
  • Strong programming skills in Python, MATLAB, C, or C++.

Preferred Qualifications:
  • Master's or PhD degree in a related quantitative or engineering discipline.
  • Experience developing algorithms for regulated medical devices, patient monitoring systems, digital health products, or clinical decision support tools.
  • Experience with medical device development practices, including design controls, requirements definition, risk management, verification and validation, clinical performance testing, usability and human factors considerations, and regulatory documentation.
  • Familiarity with relevant medical device standards and regulatory expectations such as FDA guidance for medical device software, HIPAA, and healthcare data privacy/security requirements.
  • Experience with sensor fusion across multiple physiological modalities.
  • Experience with signal quality indices, artifact detection, missing-data handling, outlier detection, and robust estimation methods.
  • Experience with embedded implementation constraints, including fixed-point arithmetic, memory optimization, computational complexity, real-time processing, and power consumption.
  • Exposure to modern AI/deep learning methods
  • Experience implementing or optimizing algorithms for embedded systems, edge devices, or real-time medical device platforms.
  • Ability to clearly communicate algorithm design, assumptions, limitations, and performance results to engineering, clinical, regulatory, and business stakeholders.

At BD, we prioritize on-site collaboration because we believe it fosters creativity, innovation, and effective problem-solving, which are essential in the fast-paced healthcare industry. For most roles, we require a minimum of 4 days of in-office presence per week to maintain our culture of excellence and ensure smooth operations, while also recognizing the importance of flexibility and work-life balance. Remote or field-based positions will have different workplace arrangements which will be indicated in the job posting.
For certain roles at BD, employment is contingent upon the Company's receipt of sufficient proof that you are fully vaccinated against COVID-19. In some locations, testing for COVID-19 may be available and/or required. Consistent with BD's Workplace Accommodations Policy, requests for accommodation will be considered pursuant to applicable law.
Why Join Us?
To find purpose in the possibilities, we need people who can see the bigger picture, who understand the human story that underpins everything we do. We welcome people with the imagination and drive to help us reinvent the future of healthcare. At BD, you'll discover a culture in which you can learn, grow and thrive.
We believe that when people connect in person, we learn faster, collaborate more deeply, and build a stronger culture. Join us and enjoy a culture where face-to-face collaboration supports your learning, your progress, and your success.
To learn more about BD visit https://bd.com/careers.
Becton, Dickinson, and Company is an Equal Opportunity Employer. We evaluate applicants without regard to race, color, religion, age, sex, creed, national origin, ancestry, citizenship status, marital or domestic or civil union status, familial status, affectional or sexual orientation, gender identity or expression, genetics, disability, military eligibility or veteran status, and other legally protected characteristics.
Required Skills
Optional Skills
Primary Work Location
USA CA - Irvine Laguna Canyon
Additional Locations
Work Shift
At BD, we reward, support and develop our associates through our comprehensive Total Rewards program. We are committed to attracting and retaining high quality talent by providing reward and recognition opportunities that promote a performance-based culture, as well as a competitive package of compensation and benefits programs. You can learn more on our career site under "Our Commitment to You."
Our salary or hourly rate ranges reward associates fairly and competitively. We regularly review these ranges and factors, such as location, contribute to the range displayed.
Our pay is based on the role and the necessary skills and education to perform it successfully. The salary or hourly rate offered is determined by the role's specific requirements, including any applicable step rate pay system at the work location. Salary or hourly pay ranges are influenced by labor laws and Collective Bargaining Agreement (CBA) requirements applicable to the work location which may also affect the workplace arrangement of the role.
Salary Range Information
$146,000.00 - $233,600.00 USD Annual

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About BD

Sourced by ZipRecruiter

BD is one of the largest global medical technology companies in the world and is advancing the world of health by improving medical discovery, diagnostics and the delivery of care. We have over 65,000 employees and a presence in virtually every country around the world to address some of the most challenging global health issues.

Industry

Medical equipment and supplies manufacturing and manufacturing

Company size

10,000+ Employees

Headquarters location

Franklin Lakes, NJ, US

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