ZipRecruiter

Log In

1

Machine Learning Petroleum Engineer Jobs in Brookline, MA

MatrixSpace

Machine Learning Engineer

Burlington, MA · Remote

We're looking for a hands-on Machine Learning Engineer who enjoys turning cutting-edge ML research into production-ready software. You'll partner closely with our Data Scientists, taking new ...

Sierra Ventures

Machine Learning Engineer

Somerville, MA · On-site

$170 - $200/hr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice understanding at Modulate. In this role, you'll design, train, evaluate, and deploy cutting‑edge machine ...

Manulife

Machine Learning Engineer

Boston, MA · Hybrid

$162K/yr

Machine Learning Engineer Job Duties: * Develop, build and maintain scalable data pipelines supporting underwriting, analytics, and machine learning systems; * Develop and deploy backend services and ...

New

SupportFinity™

Machine Learning Engineer

Boston, MA · On-site

$140 - $210/hr

About the Role We are seeking a high-impact Machine Learning Developer/Engineer to join our integrated discovery team. In this role, you will be the algorithmic engine of our programs, developing and ...

ICONSTAFF

Machine Learning Engineer

Cambridge, MA · On-site +1

Machine Learning Engineer - Computer Vision & Robotics Tycho.AI is redefining the future of autonomous intelligence. Spun out of MIT and backed by DoD contracts, we are building breakthrough AI and ...

Capital One

Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

XPO

Machine Learning Engineer - Hybrid

Boston, MA

$100K - $120K/yr

What you'll need to succeed as a Machine Learning Engineer at XPO Minimum qualifications: * Bachelor's degree in Computer Science, Engineering, or related field, or equivalent related work or ...

STR

Machine Learning Engineer

Boston, MA

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

STR

Machine Learning Engineer

Woburn, MA

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

next page

Showing results 1-20

All JobsMachine Learning Petroleum Engineer JobsMachine Learning Petroleum Engineer Jobs in Brookline, MA

Machine Learning Petroleum Engineer information

See Brookline, MA salary details

$34.1K

$139.3K

$209.4K

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

As of Aug 27, 2026, the average yearly pay for machine learning petroleum engineer in Brookline, MA is $139,317.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,800.00 and $167,700.00 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 job categories do people searching Machine Learning Petroleum Engineer jobs in Brookline, MA look for?

The top searched job categories for Machine Learning Petroleum Engineer jobs in Brookline, MA are:

What cities near Brookline, MA are hiring for Machine Learning Petroleum Engineer jobs?

Cities near Brookline, MA with the most Machine Learning Petroleum Engineer job openings:

Machine Learning Petroleum Engineer jobs near you

Machine Learning Engineer

Burlington, MA • Remote

MatrixSpace
Computer Networking • 11 - 50 employees
Learn more about MatrixSpaceexternal

Full-time

Re-posted 20 days ago

Job description

Help us bridge machine learning research and real-world deployment!

MatrixSpace develops AI-enabled radar and sensing systems that help people understand what's happening in the world around them. By combining advanced radar, edge computing, and AI, we deliver situational awareness in environments where traditional sensing solutions struggle.
We're looking for a hands-on Machine Learning Engineer who enjoys turning cutting-edge ML research into production-ready software. You'll partner closely with our Data Scientists, taking new algorithms and implementing them in performant, maintainable, and scalable production systems. You'll also help build the ML infrastructure and tooling that accelerates future research, while ensuring our AI solutions are reliable enough for real-world deployment.

If you're technically curious, highly collaborative, and motivated by solving complex real-world problems, we'd love to talk.

What You'll Do

  • Partner with Data Scientists to transform research algorithms into robust, production-quality software.
  • Implement machine learning algorithms in high-performance C++ and Python with a focus on maintainability, scalability, and real-time performance.
  • Build and improve machine learning infrastructure, tooling, and training pipelines that enable faster experimentation and more efficient model development.
  • Design and implement AI agents, agentic workflows, and LLM-powered applications.
  • Deploy and maintain AI workloads across edge, near-edge, and cloud environments.
  • Collaborate across engineering and research teams to transition prototypes into production systems.

What We're Looking For

This position requires working directly or indirectly with the US Government in restricted environments. Candidates must be legally authorized to work in the United States without employer sponsorship and may be required to obtain and maintain a U.S. government security clearance in the future.'

This is NOT a fully remote position!

Required

  • BS, MS, or PhD in Computer Science, Electrical Engineering, Applied Mathematics, Machine Learning, AI, Robotics, or a related field.
  • Strong hands-on programming experience in C++ and Python.
  • 3-5 years of experience developing and deploying machine learning systems in production environments.
  • Experience building AI agents, LLM-based applications, or intelligent automation systems.
  • Strong problem-solving skills and ability to work across the full development lifecycle.
  • Excellent written and verbal communication and collaboration skills.

Someone Who Will Thrive in This Role

  • Enjoys solving difficult technical challenges that span algorithms, software, and deployment.
  • Enjoys bridging the gap between research and production, finding practical engineering solutions that make advanced ML usable in real-world products.
  • Takes ownership and drives projects from concept through production.
  • Continuously explores new AI, ML, and agentic technologies.
  • Works effectively across multidisciplinary teams.
  • Balances research innovation with practical product delivery.
  • Builds side projects, experiments with emerging AI tools, or enjoys hands-on technical exploration.

Bonus Points

  • Experience with radar, RF sensing, sensor fusion, computer vision, robotics, or autonomous systems.
  • Experience with LangChain, LangGraph, LlamaIndex, AutoGen, Semantic Kernel, or similar frameworks.
  • Experience optimizing models for edge deployment usingTensorRT, ONNX,OpenVINO, TVM, or similar tools.
  • Experience with embedded systems, GPUs, NPUs, FPGAs, or hardware acceleration.
  • Familiarity withMLOps, CI/CD, model monitoring, and large-scale production systems.

At MatrixSpace, Machine Learning Engineering is where advanced AI research becomes real-world capability. This is an engineering-heavy ML role focused on productionizing algorithms created by Data Scientists, with some ownership of the ML infrastructure that helps those Data Scientists move faster.