Machine Learning Specialist

The Opportunity:

Tetra Tech is adding a Machine Learning Specialist to our Digital and Geospatial team based in Vancouver, BC. 

Why Tetra Tech:

At Tetra Tech, we are Leading with Science™ to solve the world’s most complex challenges. Our industry-leading experts in engineering and consulting are committed to driving positive change in communities around the world. For over 50 years, we have been at the forefront of innovation and sustainability. Today we stand as a market leader, offering cutting-edge solutions in water, environment, energy, and international development. Our work has improved more than 500 million lives around the world.

Your Impact:

Join Tetra Tech to make a real difference. Our work leverages cutting-edge technologies, advanced analytics, and the expertise of world-class scientists and engineers to create meaningful change around the world. Discover your full potential – join us to advance your career while leaving a lasting legacy.

The salary range for this position is $75,000 - $90,000 per annum. Please note that Tetra Tech considers various factors in determining pay, including but not limited to: education, relevant and demonstrated work experience in the role, skills, geographic location, qualifications, certifications, and other competencies relevant to the needs of the business.

Please note: We plan to begin interviews in early January; we thank you for your patience.
 

Your Role:

• Develop and support AI/ML models for:
  • Image classification and object detection (e.g., tree hazards, traffic signs, vegetation, utilities).
  • Semantic and instance segmentation (e.g., crack detection, erosion, pavement wear, infrastructure conditions).
  • Feature extraction and measurement from geospatial imagery (e.g., vegetation encroachment, asset monitoring).
  • Integration of computer vision outputs into hybrid models with tabular ML (e.g., XGBoost-based risk prediction).
  • Curate, preprocess, and augment large geospatial datasets (LiDAR, UAV imagery, GeoTIFFs).
• Train and evaluate models with a focus on reproducibility, performance, and efficiency.
• Optimize models for deployment, including ONNX export, GPU memory management, and real-time inference.
• Collaborate with software engineers to integrate AI outputs into GIS and ESRI-based systems.
• Create interactive client-facing prototypes and demos using tools such as Streamlit or Dash.
• Contribute to MLOps practices: model versioning, deployment pipelines, and cloud scaling.
• Support knowledge transfer and grow into more independent applied AI responsibilities.
• Conduct activities in line with internal procedures, legislation, and industry standards.
• Pursue continuous professional development and maintain a high degree of discipline knowledge and awareness.
• Work in a safe manner at all times and report all health and safety incidents and concerns.
• Additional duties as required.

Qualifications:

• Master’s degree in Computer Science, Data Science, Engineering, or related field. Bachelor’s degree with equivalent applied experience will also be considered.
• 1–4 years of hands-on experience with machine learning or computer vision (internships and applied academic projects count).
• Experience with end-to-end ML workflows: dataset preparation, training, evaluation, and deployment.
• Applied experience with geospatial or remote sensing data is a strong asset.
• Experience with Linux environments, scripting, and running ML workflows on servers or cloud platforms.
• Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow).
• Familiarity with ONNX Runtime, TorchServe or TensorFlow Serving for deployment.
• Experience with computer vision models: CNNs and segmentation models.
• Exposure to hybrid ML approaches (e.g., XGBoost for tabular features combined with deep learning outputs).
• Strong understanding of data preprocessing and augmentation for imagery and LiDAR.
• Familiarity with geospatial formats (GeoTIFF, SHP, GeoJSON, LAS/LAZ).
• Experience with rapid prototyping and visualization tools (Streamlit, Dash, Jupyter).
• Knowledge of cloud platforms (Azure, AWS, GCP) and APIs (Azure AI, OpenAI).
• Understanding of ESRI ecosystem or GIS APIs will be considered an asset.
• Eagerness to learn and grow into a specialized AI/ML career.
• Strong problem-solving skills and ability to work in collaborative, cross-disciplinary teams.

• Ability to communicate technical insights to technical and non-technical audiences.

   

Salary : $75,000 - $90,000