ZipRecruiter

Log In

1

Machine Learning Petroleum Engineer Jobs in Toronto, ON

NTENT

Machine Learning Engineer

Toronto, ON · Remote

Machine Learning Engineer Position: Full time Location: Toronto, Ontario (Initially Remote) About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize ...

Quincus

Machine Learning Engineer

Toronto, ON · On-site

As a machine learning engineer, you will be responsible for designing and implementing scalable systems for serving models, optimizing inference performance, and managing production workflows.

Manulife

Machine Learning Engineer

Toronto, ON

As a Machine Learning Engineer, you will design, build, and operate the platforms, pipelines, and reusable patterns that take models from experimentation to production at scale. You will work with ...

Td

Machine Learning Engineer

Toronto, ON

CA$120K - CA$250K/yr

As a Machine Learning Engineer, you will: * Join a world-class team of AI developers with an extensive track record of shipping solutions at the cutting-edge * Architect scalable machine learning and ...

Clio

Machine Learning Engineer

Toronto, ON · Hybrid

CA$129K - CA$174K/yr

We are currently seeking a Machine Learning Engineer to join our rapidly growing engineering team. This role is for someone who is passionate about building innovative solutions and being exposed to ...

Bmo

Machine Learning Engineer

Toronto, ON · On-site

CA$82K - CA$154K/yr

Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models. * Continuous Integration and Continuous Delivery/Deployment. * ML algorithm. * Typically between 5 - 7 ...

Vancity

Machine Learning Engineer Lead

Toronto, ON · Remote

As a Machine Learning Engineer Lead, you will join our Data Science & AI Pod, focused on designing, building, and deploying enterprise-wide AI and machine learning solutions that support business ...

BMO Capital Markets

Machine Learning Engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models. * Continuous Integration and Continuous Delivery/Deployment. * ML algorithm. * Verbal & written ...

BMO Capital Markets

Machine Learning Engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models. * Continuous Integration and Continuous Delivery/Deployment. * ML algorithm. * Verbal & written ...

BMO Capital Markets

Machine Learning Engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models. * Continuous Integration and Continuous Delivery/Deployment. * ML algorithm. * Verbal & written ...

BMO Capital Markets

Machine Learning Engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models. * Continuous Integration and Continuous Delivery/Deployment. * ML algorithm. * Verbal & written ...

BMO Capital Markets

Machine Learning engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models. * Continuous Integration and Continuous Delivery/Deployment. * ML algorithm. * Verbal & written ...

BDO Canada

Senior Machine Learning Engineer

Toronto, ON · On-site

CA$84K - CA$128K/yr

Advanced programming skills in Python, with practical experience using popular machine learning libraries such as scikit-learn, TensorFlow, and/or PyTorch. Capable of building, tuning, and deploying ...

BDO Canada

Senior Machine Learning Engineer

Oakville, ON · On-site

CA$84K - CA$128K/yr

Advanced programming skills in Python, with practical experience using popular machine learning libraries such as scikit-learn, TensorFlow, and/or PyTorch. Capable of building, tuning, and deploying ...

next page

Showing results 1-20

All JobsMachine Learning Petroleum Engineer JobsMachine Learning Petroleum Engineer Jobs in Toronto, ON

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 Toronto, ON?

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

What job categories do people searching Machine Learning Petroleum Engineer jobs in Toronto, ON look for?

The top searched job categories for Machine Learning Petroleum Engineer jobs in Toronto, ON are:

Machine Learning Petroleum Engineer jobs near you
Infographic showing various Machine Learning Petroleum Engineer job openings in Toronto, ON as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Machine Learning Engineer

Toronto, ON • Remote

NTENT
See more jobs at NTENTexternal

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 3 days ago

Job description

Machine Learning Engineer
Position: Full time
Location: Toronto, Ontario (Initially Remote)
About Us:
NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search technologies directly into their business-to-consumer offerings. We are a unique group of brilliant minds intent on discovering, learning and building. We work in a vibrant atmosphere, with an emphasis on personal and professional development. This is an opportunity to tackle complex problems usually reserved for a handful of large companies in the search industry.
About the Opportunity:
We are looking for a talented Machine Learning Engineer to join our team and deliver machine learning-driven products. The right candidate will work on development, deployment, and lifecycle management of machine learning models for various large-scale applications (natural language understanding, web search and ranking, recommendation, personalization, dialog/conversation management).
Keywords:
Machine learning, natural language processing, learning-to-rank, online learning, deep learning, interactive machine learning, machine teaching, conversational agents, human computer interaction
Duties and Responsibilities:
  • Design, implement, and deploy machine learning algorithms.
  • Manage machine learning algorithm lifecycle.
  • Coordinate data collection and annotation efforts.
  • Work with real-time data and content coming from various data sources.
  • Manage machine learning data pipelines.
  • Design tests for machine learning algorithm effectiveness and performance monitoring.
  • Design tools and interfaces for interactive machine learning and teaching.
  • Research and development on cutting-edge machine learning technologies.
Qualifications and Skills:
  • Graduate degree in Computer Science with a strong background in machine learning required.
  • Strong problem-solving abilities, solid background in algorithms and data structures required.
  • Strong programming skills in Python and Scala required. Experience in other programming languages (eg. Java, R, Haskell) a plus.
  • Solid knowledge of machine learning tools (eg. scikit-learn, tensorflow, keras, pytorch, Spark MLlib) required.
  • Experience with distributed and streaming data technologies (eg. Hadoop, Spark, Kafka) required.
  • Experience with building and deploying API's with Docker and Kubernetes required.
  • Experience with natural processing tasks (eg. named entity recognition, language modeling, vector representations) required.
  • Experience with Elastic Search, Lucene a plus but not required.
  • Experience with ranking algorithms a plus but not required.
  • Experience with interactive machine learning (eg. active learning, reinforcement learning, machine teaching) a plus but not required.
The ideal candidate will be self-motivated, possess excellent communication skills (both oral and written) and be able to work independently. A keen interest in various aspects of natural language processing is essential in our multi-disciplinary team.
We offer a full comprehensive benefits package including medical, dental and vision. Employees receive a generous time off (PTO) plan and 13 holidays per year. We also offer 401(k) benefits, long term disability benefits and life.

Apply