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Machine Learning Petroleum Engineer Jobs in Ohio

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team. The Hartford is developing industryleading ...

Machine Learning Tutor

Akron, OH · Remote

$18 - $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 ...

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

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

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

Machine Learning Engineer, Perception

Columbus, OH · On-site +1

$100K - $138K/yr

... learning, and Python programming to tackle challenges in our field alongside our talented teams. What You'll Do Experienced: * Implement, validate, and iterate on machine learning algorithms for weld ...

Statistics, Analytics, Data Science, Engineering, Operations Research, Economics, Mathematics, Machine Learning, Artificial Intelligence, and related disciplines. * 2+ years of experience leading AI ...

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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 Ohio are hiring for Machine Learning Petroleum Engineer jobs? Cities in Ohio with the most Machine Learning Petroleum Engineer job openings:
Machine Learning Engineer, Robot Learning

Machine Learning Engineer, Robot Learning

Path Robotics

Columbus, OH

Other

Medical, Dental, Vision, Retirement, PTO

Posted 7 days ago


Job description

Build the Path Forward

At Path Robotics, we're building the future of embodied intelligence. Our AI-driven systems enable robots to adapt, learn, and perform in the real world closing the skilled labor gap and transforming industries. We go beyond traditional methods, combining perception, reasoning, and control to deliver field-ready AI that is risk-aware, reliable, and continuously improving through real-world use.

Big, hard problems are our everyday work, and our team of intelligent, humble, and driven people make the impossible possible together.

We are seeking a skilled and motivated Machine Learning Engineer with expertise in modern robotics and manipulation to join our Robot Learning team to build agentic AI systems for industrial applications. The ideal candidate will have experience in robotics, with a focus on developing and implementing advanced manipulation techniques, motion control systems, and planning algorithms for autonomous robots. This role involves working closely with cross-functional teams to design, test, and deploy innovative solutions that improve the performance and capabilities of our robotic systems.

What You'll Do
  • Work on the development and deployment of behavioral cloning (BC), reinforcement learning (RL), and diffusion models to solve complex robotic tasks.
  • Leverage multi-modal data, including image-based data, force, and torque to enhance robotic manipulation and control.
  • Design and implement vision-language-action (VLA) models for more intelligent and responsive robotic systems.
  • Craft strategies for the entire solution's lifecycle, including data collection, fleet learning, and continuous learning.
  • Develop, optimize, and deploy learning-based methods for robot control and object manipulation algorithms on a fleet of industrial robotic cells.
  • Collaborate with hardware and software teams to integrate manipulation, control, and planning algorithms into robotic platforms.
  • Stay updated with the latest advancements in robotics, control theory, and planning algorithms.
Who You Are
  • Ph.D. or Master's degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field.
  • Proven track record in publishing at top conferences (e.g., NeurIPS, ICLR, ICML, CoRL, RLC).
  • Experience with robotic simulation tools (e.g., Isaac Sim, MuJoCo).
  • Experience with machine learning techniques applied to robot manipulation.
  • Experience building models from scratch and deploying them in real-world applications.
  • Experience with pose estimation, segmentation, active perception, and affordance-based bin picking.
  • Strong programming skills in languages such as C++ or Python.
  • Experience with robotic simulation tools (e.g., Isaac Sim, MuJoCo).
  • Proven track record of deploying scalable solutions for autonomous robotic systems.
  • Strong communication skills, with the ability to convey complex technical concepts to a diverse audience.
Why You'll Love It Here
  • Daily free lunch to keep you fueled and connected with the team
  • Flexible PTO so you can take the time you need, when you need it
  • Comprehensive medical, dental, and vision coverage
  • 6 weeks fully paid parental leave, plus an additional 6-8 weeks for birthing parents (12-14 weeks total)
  • 401(k) retirement plan through Empower
  • Generous employee referral bonuses-help us grow our team!
Who We Are

At Path Robotics we love coming to work to solve interesting and tough challenges but also because our ideas are welcomed and valued. We encourage unique thinking and are dedicated to creating a diverse and inclusive environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

If you require a reasonable accommodation to participate in the application process or any part of the hiring process, please contact HR@path-robotics.com. We are committed to providing equal access and will work with qualified individuals to ensure a fair and accessible hiring experience. We will respond to your request within 48 hours.