Senior Software Developer, AI
New
S
SyndioTechnology
Remote-First with opportunities for local meet-ups in Calgary #LI-RemoteFull-TimeSenior
Salary153000 - 180000 CAD per year
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Job Details
- Required Skills
- PythonGCPMachine LearningFirebaseBigQuery
Requirements
- Proficiency developing clean modular and efficient code with Python
- Track record building and deploying AI systems within Google Cloud Platform
- Familiarity with BigQuery, Firebase, and Vertex AI
- Working knowledge of Google Gemini, OpenAI, and Anthropic APIs
- Familiarity with evaluation methodologies for assessing LLM accuracy, hallucinations, and task-specific performance
- Exposure to or strong interest in vector databases, semantic search, agent frameworks, and protocols like MCP
- Fluent with AI-assisted development tools (Cursor, Claude Code, GitHub CoPilot)
- Foundational knowledge of machine learning concepts, model architectures, and LLM capabilities and constraints
- Natural curiosity and passion for staying current with rapidly evolving AI technologies
- Ability to balance innovation with practical business requirements
- Adaptable when navigating ambiguity and rapidly shifting priorities
- Comfortable communicating technical concepts and trade-offs to non-technical stakeholders
- Bachelor's degree in Computer Science, Machine Learning, Mathematics, Statistics, Data Science, or quantitative field OR equivalent hands-on experience in a related professional industry
Responsibilities
- Design, develop, and deploy production AI/ML systems that deliver business impact to our customers.
- Build and maintain LLM-based applications leveraging context engineering techniques and toolsets.
- Collaborate with data scientists to transition approved proof of concepts from a research environment into production.
- Integrate AI capabilities into existing products and services through APIs and microservices.
- Design and implement evaluation frameworks to assess model accuracy, reliability, and task-specific performance.
- Monitor production performance and implement optimizations based on evaluation metrics and real-world usage patterns.
- Stay up-to-date with the rapid changes in the AI landscape (e.g., new foundation models, quantization techniques) and prototype new ideas quickly.
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