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Machine Learning Specialist
Tetra Tech
Develop and support AI/ML models for geospatial data analysis, integration, and deployment in a GIS and ESRI-based systems.
22d ago
C$70,000 - C$85,000
Junior (1-3 years), Intermediate (4-7 years)
Full Time
Vancouver, British Columbia, Canada
Hybrid
Company Size
30,000 Employees
Service Specialisms
Engineering
Consulting
Design
Technical Services
Construction
Project Management
Environmental Services
Water Resources
Sector Specialisms
Energy
Defense Services
Disaster and Emergency Management
Marine
Transportation
Government
Water Resources
Utilities
Role
What you would be doing
feature extraction
ai/ml
integration
data preprocessing
model training
client prototypes
- Feature extraction and measurement from geospatial imagery (e.g., vegetation encroachment, asset monitoring).
- 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.
- Conduct activities in line with internal procedures, legislation, and industry standards.
- Develop and support AI/ML models for:
- Work in a safe manner at all times and report all health and safety incidents and concerns.
- Train and evaluate models with a focus on reproducibility, performance, and efficiency.
- 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).
- Support knowledge transfer and grow into more independent applied AI responsibilities.
- Optimize models for deployment, including ONNX export, GPU memory management, and real-time inference.
- Contribute to MLOps practices: model versioning, deployment pipelines, and cloud scaling.
What you bring
geospatial data
linux
deployment
master's degree
cloud platforms
problem-solving
- Applied experience with geospatial or remote sensing data is a strong asset.
- Ability to communicate technical insights to technical and non-technical audiences.
- Experience with Linux environments, scripting, and running ML workflows on servers or cloud platforms.
- Experience with rapid prototyping and visualization tools (Streamlit, Dash, Jupyter).
- Semantic and instance segmentation (e.g., crack detection, erosion, pavement wear, infrastructure conditions).
- Familiarity with ONNX Runtime, TorchServe or TensorFlow Serving for deployment.
- Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow).
- Exposure to hybrid ML approaches (e.g., XGBoost for tabular features combined with deep learning outputs).
- Master’s degree in Computer Science, Data Science, Engineering, or related field. Bachelor’s degree with equivalent applied experience will also be considered.
- Eagerness to learn and grow into a specialized AI/ML career.
- Understanding of ESRI ecosystem or GIS APIs will be considered an asset.
- 1–4 years of hands-on experience with machine learning or computer vision (internships and applied academic projects count).
- Knowledge of cloud platforms (Azure, AWS, GCP) and APIs (Azure AI, OpenAI).
- Experience with computer vision models: CNNs and segmentation models.
- Image classification and object detection (e.g., tree hazards, traffic signs, vegetation, utilities).
- Experience with end-to-end ML workflows: dataset preparation, training, evaluation, and deployment.
- Strong problem-solving skills and ability to work in collaborative, cross-disciplinary teams.
- Strong understanding of data preprocessing and augmentation for imagery and LiDAR.
- Familiarity with geospatial formats (GeoTIFF, SHP, GeoJSON, LAS/LAZ).
- Learning and development opportunities for ongoing professional growth.
- Collaborative team atmosphere that values the contributions of all employees.
- Mentorship with world leading experts in your field.
- Comprehensive and market-competitive benefits, available on day one of employment.
- Overtime is calculated at 1.5 times.
- We have embraced a hybrid culture. We will provide you the tools to work almost anywhere.
- Flexibility and company-wide commitment to work/life balance.
Information not given or found
Interview process
Information not given or found
Visa SponsorshipInformation not given or found
Security clearance- safety and health incident reporting, maintaining professional discipline knowledge, and ensuring compliance with industry standards.
Company
Overview
$5B
Annual Revenue
The company generates approximately $5 billion in revenue each year.
1966
Year Founded
Established in 1966 in Pasadena, the company has grown globally over the decades.
110,000
Annual Projects
It executes approximately 110,000 projects annually across various sectors.
Top ENR
Industry Rankings
The company is highly ranked in ENR for water treatment, wind power, and hydroelectric plant engineering.
- Leveraging a signature science-driven approach, it tackles complex problems in water, environmental restoration and sustainable infrastructure.
- It organizes itself into government and commercial/international groups, enabling tailored expertise across public and private sectors.
- Its Digital Systems division develops advanced analytics and visualization tools (like FusionMap®), supporting clients in grid reliability and AI infrastructure.
- Unusual among engineering firms, it bridges traditional civil projects with cutting-edge digital and AI-enabled infrastructure solutions.
- Service
- Value
- Excellence
- Opportunity
- Improving lives around the world by Leading with Science®
- Our workforce is diverse and includes leading experts in our fields
- Encouraging our associates to explore new technologies, ideas, and business trends
$1B Credit Facility
Sustainability-linked financial initiative
A $1 billion credit facility tied to greenhouse gas reduction and improving lives metrics.
78% Emissions Reduction
Greenhouse gas reduction from operations
Achieved a 78% reduction in greenhouse gas emissions from operations, aligning with carbon negative targets.
100% Solar Energy
Net zero energy target achieved
Achieved net zero energy target via a LEED Platinum certified project with 100% solar energy and energy use intensity ≤ 30 kBtu/sf/year.
36% Emissions Reduction
GHG reduction per employee
Reduced greenhouse gas emissions per employee by 36% for Scope 1 and 2 compared to 2021 baseline.
- Carbon negative target with UN Global Compact and SBTi alignment.
- Independent verification of science-based targets in line with 1.5 °C Paris goal.
- Reporting Scope 1, 2, and 3 emissions.
- 60% of vendor spend to commit to SBTi by 2027.
- 24% of business holds ISO 14001 certification for environmental management.
- Net zero energy target achieved via LEED Platinum California DGS Natural Resources Headquarters project.
- Sustainability-linked $1 billion credit facility tied to GHG reduction and improving lives metrics.
20,400 people
STEM program engagement
The company's STEM program has engaged over 20,400 individuals, focusing on promoting participation and inclusivity in science, technology, engineering, and mathematics.
TRIR 0.37 and LWDIR 0.12
Safety performance metrics
The company achieved a Total Recordable Incident Rate (TRIR) of 0.37 and a Lost Workday Injury Rate (LWDIR) of 0.12 in 2024, representing a 54% and 60% improvement over industry averages, respectively.
- Strive for achievement: committed to high performance and delivering on promises
- Be open and transparent: foster a culture where people can share openly and say what they mean
- Listen to and respect people: value people, listen deeply, and ensure all voices are heard and respected
- Pursue curiosity and have a passion for learning: constantly aim to learn and grow through research, feedback, and reflection
- Embrace diversity and collaboration: work as one team that embraces diversity and actively invites different perspectives
- Indigenous engagement commitments: respect land tenure and property rights; maximize meaningful employment and business opportunities for Indigenous Peoples; engage Indigenous suppliers; provide training and youth/elder opportunities
- Women’s representation: supports the Australian Human Rights Commission’s Wiyi Yani U Thangani Report; targeting structural change for First Nations women and girls
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