Staff Software Developer, AI
New
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SyndioHR Tech, AI
AZ, CA, CO, CT, DC, FL, GA, ID, IL, IA, MD, MA, MN, NE, NJ, NY, OH, OR, PA, RI, SC, SD, TX, UT, VT, VA, WA, and WIFull-TimeStaff
Salary205,000 - 244,000 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
Responsibilities
- Design, develop, and deploy production AI/ML systems that deliver business impact to 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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