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AI/ML Engineer

Pay
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Work setting
Remote — work setting source
This is a remote position. About Us:
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Employment
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Employment type in the employer’s posting: Contract
From the employer’s posting

What you’ll work on

Full posting
  • Design, develop and implement ML models and AI algorithms for industry use cases

  • Work on predictive analytics, NLP and computer vision models

  • Build and maintain data pipelines with data engineers for model training

From the employer’s posting
Design, develop, and implement machine learning models and AI algorithms tailored to industry-specific use cases
particularly in predictive analytics, natural language processing, and computer vision
Collaborate with data engineers to build and maintain robust data pipelines, ensuring high-quality data is available for model training and deployment.

What you’ll bring

All qualifications

Core experience

  • Strong background in machine learning algorithms
  • Software engineering skills
  • Data processing experience

Preferred experience

  • Familiarity with big data technologies such as Hadoop, Spark, or Kafka is a plus.
  • Experience with natural language processing (NLP) and computer vision.
  • Experience with real-time data processing and streaming analytics.
  • Familiarity with ethical AI practices and the ability to implement AI models responsibly.
Qualification wording
The ideal candidate will have a strong background in machine learning algorithms, data processing, and software engineering
Familiarity with big data technologies such as Hadoop, Spark, or Kafka is a plus.
Experience with natural language processing (NLP) and computer vision.
Experience with real-time data processing and streaming analytics.
Familiarity with ethical AI practices and the ability to implement AI models responsibly.
Education & alternatives
Qualifications: - Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. A Ph.D. is a plus. - Experience: 3+ years of experience in AI/ML engineering, with a proven track record of developing and deploying machine learning models in a production environment.

About WiselyWise

WiselyWise is a leading innovator in AI-driven technology.

In the employer’s words · Read in context

Apply at WiselyWise

Posting record

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Open 5 monthsWe first saw this posting 154 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jun 2, 2026154 days ago
Recorded sightings
131
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 154

Up longer than most. Similar jobs usually come down between day 6 and day 69.

From 4,301 similar postings that came down. Coming down is not always a hire.

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Java
  • Python
  • R
  • AWS
  • Azure
  • Docker
  • Hadoop
  • Kafka
  • Kubernetes
  • Spark
  • PyTorch
  • scikit-learn
  • TensorFlow
  • GCP
Where the posting names them
- Technical Skills: - Proficiency in programming languages such as Python, R, or Java. - Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Strong understanding of data structures, algorithms, and software design principles. - Experience with cloud platforms like AWS, Azure, or Google Cloud for deploying AI models. - Familiarity with big data technologies such as Hadoop, Spark, or Kafka is a plus.
- Familiarity with big data technologies such as Hadoop, Spark, or Kafka is a plus. - Experience with containerization and orchestration tools like Docker and Kubernetes. - Analytical Skills: Strong problem-solving skills with the ability to analyze complex datasets and develop innovative AI solutions.
- Experience with cloud platforms like AWS, Azure, or Google Cloud for deploying AI models. - Familiarity with big data technologies such as Hadoop, Spark, or Kafka is a plus. - Experience with containerization and orchestration tools like Docker and Kubernetes.
- Proficiency in programming languages such as Python, R, or Java. - Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. - Strong understanding of data structures, algorithms, and software design principles.

Your next step

Complete your application on wiselywise.zohorecruit.com. The employer’s form will show what is required.

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

This is a remote position.

About Us:

​
WiselyWise is a leading innovator in AI-driven technology. 

We are seeking a highly skilled AI/ML Engineer to join our team and drive the development and deployment of advanced machine learning models and AI-driven solutions. The ideal candidate will have a strong background in machine learning algorithms, data processing, and software engineering, with a passion for solving complex problems in a dynamic environment. 

This role will play a critical part in the implementation of AI technologies within the upstream Oil & Gas sector, helping to optimize exploration, drilling, and production processes.


Job Overview:

We are seeking a highly skilled AI/ML Engineer to join our team and drive the development and deployment of advanced machine learning models and AI-driven solutions. The ideal candidate will have a strong background in machine learning algorithms, data processing, and software engineering, with a passion for solving complex problems in a dynamic environment. This role will play a critical part in the implementation of AI technologies within the upstream Oil & Gas sector, helping to optimize exploration, drilling, and production processes.


Requirements

Key Responsibilities:


  • Model Development: Design, develop, and implement machine learning models and AI algorithms tailored to industry-specific use cases, particularly in predictive analytics, natural language processing, and computer vision.

  • Data Processing: Collaborate with data engineers to build and maintain robust data pipelines, ensuring high-quality data is available for model training and deployment.

  • Algorithm Optimization: Optimize machine learning models for performance, scalability, and accuracy, employing techniques such as hyperparameter tuning, model selection, and feature engineering.

  • Collaboration: Work closely with data scientists, domain experts, and software developers to integrate AI models into production systems and create end-to-end solutions that meet business objectives.

  • Model Deployment: Deploy machine learning models into production environments using industry-standard tools and frameworks, ensuring reliability and scalability.

  • Continuous Improvement: Monitor the performance of AI models post-deployment, making iterative improvements based on feedback and changing business needs.

  • Innovation: Stay up-to-date with the latest advancements in AI/ML technologies and best practices, and apply this knowledge to drive continuous innovation within the team.

  • Documentation: Create comprehensive documentation for developed models, algorithms, and processes to ensure knowledge sharing and maintainability.

Qualifications:


  • Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. A Ph.D. is a plus.

  • Experience: 3+ years of experience in AI/ML engineering, with a proven track record of developing and deploying machine learning models in a production environment.

  • Technical Skills:

    • Proficiency in programming languages such as Python, R, or Java.

    • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.

    • Strong understanding of data structures, algorithms, and software design principles.

    • Experience with cloud platforms like AWS, Azure, or Google Cloud for deploying AI models.

    • Familiarity with big data technologies such as Hadoop, Spark, or Kafka is a plus.

    • Experience with containerization and orchestration tools like Docker and Kubernetes.

  • Analytical Skills: Strong problem-solving skills with the ability to analyze complex datasets and develop innovative AI solutions.

  • Communication: Excellent verbal and written communication skills, with the ability to collaborate effectively across multidisciplinary teams.

Industry Knowledge: Experience in the Oil & Gas sector is a plus but not required.

Preferred Qualifications:


  • Experience with natural language processing (NLP) and computer vision.

  • Experience with real-time data processing and streaming analytics.

  • Familiarity with ethical AI practices and the ability to implement AI models responsibly.


Benefits

Why Join Us:


  • Opportunity to work on cutting-edge AI projects that have a tangible impact on critical industries.

  • Collaborative and innovative work environment.

  • Competitive compensation and benefits package.

  • Opportunities for professional growth and continuous learning.


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