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Machine Learning Petroleum Engineer Jobs in Idaho

SwiftCruit

Machine Learning Engineer

Boise, ID · On-site

$110 - $150/hr

  • Medical

  • Retirement

  • PTO

As a Machine Learning Engineer in the Identity and Fraud business at Equifax, you will solve challenging technology problems and build architecturally sound, high-quality software that moves data ...

Micron Technology

Staff Machine Learning Engineer

Boise, ID · On-site

$120 - $150/hr

  • Medical

  • Dental

  • Vision

  • PTO

JR101366 Staff Machine Learning Engineer Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage ...

Micron Technology

Staff Machine Learning Engineer

Boise, ID · On-site

  • Medical

  • Dental

  • Vision

  • PTO

The Smart Manufacturing and AI team at Micron Technology is looking for an ambitious Machine Learning Engineer. Are you curious, high velocity, and ready to solve complex problems? Do you dream in ...

Micron

Principal Machine Learning Engineer

Boise, ID · On-site

  • Medical

  • Dental

  • Vision

  • PTO

As a Principal Machine Learning Engineer, willhave experiencein a variety of dataand cloudtechnologies and have extensive practice modeling data, querying, anddeployingscalable pipelinestoexecute ...

Micron

Staff Machine Learning Engineer

Boise, ID

  • Medical

  • Dental

  • Vision

  • PTO

... DevOps tools (GCP, AWS, Azure, Docker, Kubernetes), combined with strong analytical, communication, and collaboration skills. Preferred Qualifications: * Strong foundation in machine learning and ...

Bespoke Labs

Machine Learning Engineer

Rexburg, ID · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Meridian, ID · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Boise, ID · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Pocatello, ID · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

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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 Idaho?

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

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

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

Machine Learning Petroleum Engineer jobs near you

Machine Learning Engineer

SwiftCruit

Boise, ID • On-site

$110 - $150/hr

Other

Medical, Retirement, PTO

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds, and make a meaningful impact, we want to hear from you.

This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support.

As a Machine Learning Engineer in the Identity and Fraud business at Equifax, you will solve challenging technology problems and build architecturally sound, high-quality software that moves data through models to make automated decisions. You will achieve success through communicating, collaborating, and developing creative and performant solutions to help Equifax provide certainty in every digital transaction for our customers. You should be a creative, driven, motivated engineer that can think outside the box, have the ability to learn quickly, and can deliver high-quality working solutions that are both maintainable and scalable. You will work with data scientists to develop requirements for novel algorithms, and with operations and other developers to bring data transformation pipelines and machine learning models to practice.

What you’ll do
  • Design platforms and pipelines for researching, developing, and running machine learning models
  • Productionize machine learning models by building performant data transformations, storage, and pipelines
  • Develop and maintain microservices that serve data, model features, and scores to other internal services, as well as external customers
  • Demonstrate effective, respectful, and honest communication when collaborating with colleagues including a cross‑functional team consisting of Data Science, Operations, and Engineering
  • Apply development and testing best practices (including unit, service, and integration tests) and demonstrate excellent software craftsmanship to produce maintainable, scalable, and quality solutions.
  • Contribute to all phases of product development and delivery from Analysis & Design all the way through to successful Deployment.
  • Deliver on company initiatives and projects prioritized for your team and support long term technical vision.
  • Collaborate with the product team, architects, and others to document features and changes.
  • Identify gaps and iterative improvements to legacy model platforms, frameworks, or governance stacks
  • Adhere to and influence best practices (i.e. security, architecture, platform, etc.)
  • Participate in peer design and code reviews
  • Participate in on-call rotation with other engineers
What experience you need
  • BS in Computer Science, Engineering, or equivalent experience.
  • 3+ years of strong software engineering and software architecture background using languages such as Golang, Python, and SQL.
  • 3+ years of experience building RESTful APIs and/or gRPC within a distributed microservice architecture.
  • 2+ years of experience implementing Amazon Web Services (e.g., IAM, Lambda, EKS, Neptune, DynamoDB, RDS).
  • 2+ years of experience using IaC tooling such as Terraform
  • Experience working with machine learning frameworks such as SparkMLlib, Scikit-Learn, MLflow, or TensorFlow.
  • Experience serving ML model inference at scale in low‑latency (<30ms) environments.
  • Experience with metrics, logging, and evaluating model performance (e.g., DataDog, evaluation latency, and ROC curves).
What could set you apart
  • Experience with Snowflake
  • Experience with AWS EMR
  • Experience deploying diverse model architectures into production using portable formats like ONNX or MLeap.

We offer comprehensive compensation and healthcare packages, 401k matching, paid time off, and organizational growth potential through our online learning platform with guided career tracks.

Are you ready to power your possible? Apply today, and get started on a path toward an exciting new career at Equifax, where you can make a difference!

Primary Location:

USA-ID-Boise

Function:

Function - Tech Dev and Client Services

Schedule:

Full time

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