Case worker Jobs in Richmond, BC

Vaisala is a global leader in measurement instruments and intelligence helping industries, nations, people, and the planet to thrive. From predicting hurricanes to optimizing renewable energy production, our technology is used where it matters the most – from data centers, windfarms and laboratories to airports, the Arctic and even the surface of Mars. Our team of over 2,300 experts and 59 nationalities around the world is committed to taking every measure for the planet. Driven by our shared purpose, curiosity, and pioneering spirit, we stay ahead and make a difference. At Vaisala, you don't have to fit in to belong.

AI Agent for Automated Analysis of viewLinc Enterprise Server Debug Logs

Host: Vaisala - Product Development, North America

Location: Surrey, BC (Hybrid — two days per week in the office)

Supervisor: Chad Hagberg, Head of Product Development, North America

Title: Thesis Worker

Time in role: full-time, temporary position, targeting May to August / September 2026

Paid Opportunity: $31-37 CAD hourly (dependent on education level).

Project Overview

Vaisala’s viewLinc Enterprise Server (viewLinc ES) generates extensive debug logs that contain detailed information about system behavior, event sequences, alarms, performance characteristics, and component interactions. Today, interpreting these logs requires deep product expertise and significant engineering time.

We are seeking a Master’s student to design and develop an AI‑powered diagnostic agent that can automatically analyze these debug logs to detect issues, correlate events across the system, identify likely sources of problems, and recommend potential corrective actions. This work directly supports Vaisala’s ongoing initiatives around intelligent automation and improved product observability.

Project Goals

The selected student will design and implement an AI‑driven tool that can:

1. Ingest and Understand Raw Debug Logs

• Parse large, multi‑component debug log files
• Normalize inconsistent formatting and message patterns
• Handle info, warnings, errors, stack traces, timestamps, subsystem identifiers, and more

2. Detect Anomalies and System Issues

• Identify unusual behavior patterns or recurring faults
• Highlight deviations from normal system operations
• Surface emerging or hidden problems automatically

3. Correlate Activities Across Components

• Link related events across time and subsystems
• Map interactions between server components and processes
• Construct timelines that reveal root‑cause chains

4. Recommend Likely Root Causes & Fixes

• Match patterns against historical issues, known failures, or log signatures
• Provide suggestions or remediation options based on context
• Output structured insights for engineering, support, and QA teams

5. Integrate Known Issues from Jira and the Knowledge Base

• Cross‑reference detected log patterns with existing Jira ECRs, bug records, and internal knowledge base articles
• Automatically flag when a detected pattern aligns with a documented known issue
• Generate enhanced communication summaries for Tech Support
• Help streamline support workflows by reducing duplicate investigations

6. Deliver a Fully Functioning AI Agent

• The end result should be a complete, operational AI agent, not just a prototype
• Must perform log ingestion, analysis, correlation, and recommendation autonomously
• Should be modular and maintainable for future enhancements
• Emphasis on usability, explainability, reliability, and readiness for internal adoption

Suggested Technical Approaches (Flexible)

Machine Learning / AI

• Transformer‑based NLP models
• Sequence modeling (e.g., LSTM) for event chains
• Unsupervised anomaly detection
• Few‑shot classification for rare error patterns

Rule‑Based or Hybrid Intelligence

• Log parsing combined with heuristics
• Statistical pattern mining
• Hybrid expert‑system plus ML detection

System/Prototype Design

• Log ingestion pipeline
• Preprocessing and enrichment layers
• Visualization or explanation layer to communicate insights

Expected Outcomes

• A fully functioning AI agent capable of analyzing viewLinc ES debug logs end‑to‑end
• Documentation of the analysis pipeline and model approach
• A thesis or final report presenting the methodology, experiments, and evaluation
• Recommendations for future integration into Vaisala systems

Ready to take every measure for the planet? apply by April 15th, 2026, and include your resume. We’d also love to hear what inspired you to apply for this role and to Vaisala in a brief cover letter. Please note that applications sent via email cannot be processed due to privacy reasons. We are not able to provide support in relocation or work permit-related matters for this temporary position.

Our Vaisala solutions contribute to societies and people’s lives in over 150 countries – and can even be found in space. With our technological innovations for measuring weather, environmental and industrial conditions, we have a key role in solving the grand social and environmental challenges of our time. We offer you a career with a clear purpose and a chance to create observations for a better world. We take pride in being pioneers who strive to bring about positive changes in both the society and environment, and our work is not done yet. Take advantage of this opportunity and join our team to make a difference!

Reasonable Accommodation Notice

Federal law requires employers to provide reasonable accommodation to qualified individuals with disabilities. Examples of reasonable accommodation include making a change to the application process or work procedures, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. As a government contractor, Vaisala complies with Section 503 of the Rehabilitation Act of 1973 (the Act), which is a law that prohibits federal contractors and subcontractors from discriminating in employment against individuals with disabilities and requires employers take affirmative action to recruit, hire, promote, and retain these individuals.

Recruiter: Erin Hanson
Job Family: Administration

Job Grade: JG_V