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Machine Learning Petroleum Engineer Jobs in Illinois

Machine Learning Engineer

Chicago, IL ยท On-site

$80 - $120/hr

Preferred Qualifications PhD in Mathematics, Engineering, Physics or related field; 4-8 years experience working in Machine Learning; Experience with deep learning frameworks like TensorFlow or ...

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 ...

Machine Learning Engineer

Chicago, IL ยท On-site +1

$95 - $105/hr

... Machine Learning Engineer to help build the algorithmic assets and features that Hyatt guests, members, customers and internal users leverage to transform the guest experience and drive efficiencies ...

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 ...

Our machine learning engineering team is responsible for developing infrastructure and tooling to help enable data driven decisions and insights at scale for millions of Paylocity users. As a Staff ...

Senior Machine Learning Engineer

Schaumburg, IL ยท On-site

$120K - $159K/yr

Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing ...

Senior Machine Learning Engineer

Schaumburg, IL ยท On-site

$120K - $159K/yr

Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing ...

Machine Learning Engineer

Chicago, IL ยท Remote

$95 - $105/hr

TEKsystems is seeking a Machine Learning Engineer to support one of our major customers that sits in Chicago. THIS IS 100% REMOTE and LONG TERM. Top 3-5 Skills - Strong engineering foundation ...

Machine Learning Engineer

Chicago, IL ยท On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

Machine Learning Engineer

Chicago, IL ยท On-site

$62 - $100/hr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

Senior Machine Learning Engineer

Chicago, IL ยท On-site

$107K - $147K/yr

Hyatt seeks an extraordinary Machine Learning Engineer to help build the algorithmic assets and features that Hyatt guests, members, customers and internal users leverage to transform the guest ...

As an AI & Machine Learning Engineer, you will design, build, and deploy the intelligent systems that make LightSpeed's construction robots smarter, faster, and more autonomous. You will develop ...

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Machine Learning Petroleum Engineer information

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 Illinois?

For Machine Learning Petroleum Engineer jobs in Illinois, the most frequently searched job titles are:

What job categories do people searching Machine Learning Petroleum Engineer jobs in Illinois look for?

The top searched job categories for Machine Learning Petroleum Engineer jobs in Illinois are:

What cities in Illinois are hiring for Machine Learning Petroleum Engineer jobs?

Cities in Illinois with the most Machine Learning Petroleum Engineer job openings:

Machine Learning Engineer

Qfanalytics

Chicago, IL โ€ข On-site

$80 - $120/hr

Other

Posted 18 days ago


Job description

QF Analytics LLC is a fintech company that develops and supports one of the worldโ€™s fastest-growing online trading platforms with a monthly trading volume in excess of $11 billion dollars. We are expanding our team aggressively and looking ideally for individuals with trading domain knowledge, who can help develop and support a robust financial trading infrastructure.

The Machine Learning Researcher should be interested in Financial Markets, and will be directly involved in advancing the companyโ€™s Data Analysis and Machine Learning capabilities. Theyโ€™ll be working on cutting edge Quantitative Data Analysis and Machine Learning challenges. Our environment is fast paced and constantly changing; the right candidate must be able to demonstrate strong communication skills, creative solutions, and results-driven behavior in time-sensitive situations.

This opportunity presents an exciting chance for individuals seeking a dynamic work environment. The successful candidate will have the option to work in a hybrid capacity, commuting to offices in Miami, Chicago, Atlanta, Toronto (Canada) or Nassau (Bahamas), fostering a collaborative and engaging atmosphere. Join our team and experience the synergy that comes from working together in person, while also enjoying the flexibility and convenience of working from home a couple days a week.

Responsibilities

Apply strong data modelling and statistical skills to develop and implement data-driven solutions.

Curate and prepare data for supervised and unsupervised machine learning projects, ensuring data quality and compatibility.

Manipulate and analyze large datasets, including numerical and categorical data, using appropriate techniques and tools.

Utilize knowledge of classical machine learning and deep learning algorithms to address specific problem domains.

Apply ML/AI tools like TensorFlow/PyTorch to build and train models for various applications.

Interface with databases to gather relevant information for analysis and modeling.

Fuse and correlate different data feeds to gain insights and enhance predictive capabilities.

Stay updated with the latest advancements in the field of machine learning and artificial intelligence, including tools, conferences, and industry blogs.

Possess a solid understanding of capital markets concepts and quantitative financial methods to effectively apply machine learning techniques in finance-related projects.

Required Qualifications

Masterโ€™s Degree in Mathematics, Engineering, Physics or related field;

Proficiency in Python;

Strong understanding of SQL for data manipulation and extraction;

Solid knowledge of probability and statistics to effectively analyze and interpret data;

Knowledge of applied mathematics, including convex optimization, quadratic programming, and partial differential equations;

Proficiency in analyzing and interpreting data, along with the ability to question it and draw meaningful conclusions;

Handsโ€‘on approach and flexibility to apply various methods and techniques to generate actionable ideas;

Proactive, selfโ€‘motivated, and teamโ€‘oriented mindset, demonstrating strong analytical thinking;

Strong conceptualization, innovation, and problemโ€‘solving skills;

Ability to communicate effectively through verbal and written presentations;

Preferred Qualifications

PhD in Mathematics, Engineering, Physics or related field;

4-8 years experience working in Machine Learning;

Experience with deep learning frameworks like TensorFlow or PyTorch;

Familiarity with C# and .NET framework;

Familiarity with Azure Environments; specifically Azure Data Functions;

Familiarity with Docker initialization and environment management.

What We Have To Offer

Flexible work arrangements when in office (including working from home periodically);

Competitive salaries, often better than industry, for comparable roles;

Daily premium lunch catering, and keeping the office stacked with fruits and snacks;

Arcade, foosball, snooker, pingpong, and fully equipped game room with latest generation gaming consoles on site;

Comprehensive health benefits plan that kicks in after 90 days of successful employment, including access to exclusive employee discounts;

Bonus and incentive programs.

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