Machine Learning Engineer – GeoAI & Computer Vision (Remote)

AceOutsource Solutions; Santa Rosa; Remote; PHP 800,000 - 1,200,000; Full time

Job summary

AceOutsource Solutions is seeking a Machine Learning Engineer specializing in Computer Vision, GeoAI, and Earth Observation to join our technology team in the Philippines. You will design, develop, train, evaluate, and deploy ML/DL solutions for satellite imagery, aerial imagery, remote sensing, and geospatial datasets.

Ideal candidates have strong ML/CV experience and are comfortable with Earth Observation or geospatial data.

Qualifications

• At least 3 years of professional experience in ML, AI, CV, remote sensing, or related field.
• Strong hands-on experience developing and training ML/DL models.
• Strong Python programming skills.
• Experience developing CV or image-based ML applications.
• Experience taking ML models from experimentation toward production use.
• Experience with deep learning frameworks such as PyTorch or TensorFlow.
• Strong analytical, problem-solving, and experimentation skills.

Responsibilities

• Design, develop, train, evaluate, and optimize ML and DL models.
• Develop CV solutions using satellite, aerial, UAV imagery and other geospatial data.
• Build models for object detection, segmentation, classification, anomaly/change detection.
• Design scalable GeoAI pipelines for large-scale geospatial analysis.
• Integrate ML models into cloud-based production platforms; develop scalable data pipelines.
• Collaborate with software engineers, data scientists, GIS specialists, and stakeholders.

Skills

Machine Learning

Computer Vision

Remote Sensing

Geospatial Data Science

Python

Analytical Thinking

Education

Bachelor's degree in Computer Science

Master's degree in AI

Ph.D. in Remote Sensing

Tools

PyTorch

TensorFlow

Geospatial Tools

Job description

JOB OVERVIEW

AceOutsource Solutions is looking for a Machine Learning Engineer specializing in Computer Vision, GeoAI, and Earth Observation to join our growing technology team.

The successful candidate will design, develop, train, evaluate, and deploy machine learning and deep learning solutions for real-world applications involving satellite imagery, aerial/UAV imagery, remote sensing, and geospatial datasets.

Candidates with strong Machine Learning and Computer Vision experience who have limited direct experience in Earth Observation or geospatial technologies are also encouraged to apply.

KEY RESPONSIBILITIES

Machine Learning & Computer Vision

• Design, develop, train, evaluate, and optimize Machine Learning and Deep Learning models.
• Develop Computer Vision solutions using satellite, aerial, UAV, multispectral, hyperspectral, and other imagery.
• Build solutions for object detection, semantic segmentation, instance segmentation, image classification, anomaly detection, and change detection.
• Select appropriate model architectures and techniques based on project requirements.
• Conduct experiments and evaluate model performance using appropriate metrics and validation methods.
• Optimize models for accuracy, efficiency, scalability, and deployment.

GeoAI & Earth Observation

• Develop AI/ML solutions for geospatial and Earth Observation applications.
• Process and analyze optical, SAR, multispectral, hyperspectral, LiDAR, and drone datasets.
• Develop predictive and analytical models for applications such as:
  • Precision agriculture and crop monitoring
  • Crop health and disease detection
  • Irrigation assessment
  • Yield prediction
  • Land suitability analysis
  • Forestry and natural resource management
  • Environmental monitoring
  • Disaster and climate monitoring
• Design scalable GeoAI pipelines for large-scale geospatial analysis.

AI Engineering & Deployment

• Integrate Machine Learning models into cloud-based production platforms.
• Develop scalable data-processing and ML pipelines.
• Work closely with software engineers to deploy AI services and production systems.
• Apply MLOps practices including model versioning, monitoring, testing, and deployment automation.
• Optimize models and pipelines for production performance and scalability.
• Research & Technical Development
• Evaluate emerging technologies in AI, Computer Vision, Remote Sensing, Geospatial Technology, and GeoAI.
• Design technical experiments and proof-of-concept solutions.
• Prepare technical documentation, reports, and project deliverables.
• Support technical presentations, client demonstrations, and proposal development.

Collaboration

• Collaborate with software engineers, data scientists, GIS specialists, and other technical team members.
• Translate business and technical requirements into practical AI/ML solutions.
• Communicate technical findings and recommendations clearly to technical and non-technical stakeholders.
• Take ownership of assigned AI/ML projects and deliverables.

QUALIFICATIONS

• At least 3 years of professional experience in Machine Learning, Artificial Intelligence, Computer Vision, Remote Sensing, Geospatial Data Science, or a closely related field.
• Strong hands-on experience developing and training ML/DL models.
• Strong Python programming skills.
• Experience developing Computer Vision or image-based ML applications.
• Experience taking ML models from experimentation toward practical or production use.
• Experience with deep learning frameworks such as PyTorch, TensorFlow, or similar.
• Strong analytical, problem-solving, and experimentation skills.

• Experience working with large or complex datasets.
• Ability to work independently and collaborate effectively with multidisciplinary technical teams.
• Experience with geospatial, Earth Observation, or remote sensing data is highly desirable but not required.

EDUCATION

• Bachelor's, Master's, or Ph.D. in Computer Science, AI, Data Science, Remote Sensing, GIS/Geoinformatics, Geomatics, Engineering, Mathematics, or a related field.
• Equivalent professional experience may be considered.

IDEAL CANDIDATE

You may be a good fit if you are a:

• Machine Learning Engineer
• Computer Vision Engineer
• AI Engineer
• GeoAI Engineer
• Geospatial Data Scientist
• Remote Sensing Data Scientist
• Earth Observation / ML Engineer.