Senior Data Science Developer JP244
- Toronto, ON, Canada
Full-time
Applications open in a new tab.
Job details
- Job type
- Full-time
- Apply by
- Posting language
- English
- Posted
Original job description
The Senior Data Science Developer will design, develop, and implement enterprise AI solutions, including Generative AI applications, intelligent agents, and reusable AI components. The role will accelerate delivery of priority AI use cases and establish reusable capabilities that reduce reliance on one-off solutions and external resources.
Key Responsibilities
- Design, develop, test, and implement GenAI applications, intelligent agents, and AI-enabled solutions for priority business use cases.
- Build reusable AI components, services, APIs, and solution patterns that can be leveraged across multiple business areas.
- Develop solutions using large language models (LLMs), retrieval-augmented generation (RAG), agentic AI, machine learning, and related AI techniques.
- Integrate AI solutions with enterprise data sources, applications, APIs, and business workflows.
- Develop prototypes and proofs of concept and evolve successful solutions toward secure, scalable, production-ready implementations.
- Partner with Product Managers, Data Scientists, Data Engineers, Data Architects, and business teams to translate requirements into working AI solutions.
- Apply software engineering practices including version control, testing, documentation, CI/CD, monitoring, and performance optimization.
- Evaluate AI solution performance, reliability, accuracy, and scalability and continuously improve implemented solutions.
- Incorporate Responsible AI, privacy, security, and data governance requirements into solution design and development.
- Contribute to reusable enterprise AI patterns, development standards, technical documentation, and knowledge transfer to strengthen internal AI capability.
More about this job
Responsibilities
The Senior Data Science Developer at Pathlion will build generative AI applications and reusable AI tools for business teams. They will also connect these solutions to company data and systems and work with product and data teams to deliver them.
Requirements
Candidates need hands-on experience building AI solutions with large language models, retrieval-augmented generation and machine learning. They also need solid software engineering practice, including testing, CI/CD, version control and monitoring.
Skills
- Generative AI
- Large language models (LLM)
- Retrieval-augmented generation (RAG)
- Agentic AI
- Machine learning
- AI solution design
- API development
- Software engineering
- Version control
- Automated testing
- CI/CD
- Monitoring and performance optimization
- Data integration
- Technical documentation
- Responsible AI
- Data privacy and security
- Prototyping
- Stakeholder collaboration
- Knowledge transfer
Categories
- Data & Analytics
- Software
- Technology
Keywords
- Generative AI
- LLM
- large language models
- retrieval-augmented generation
- RAG
- agentic AI
- intelligent agents
- machine learning
- AI APIs
- MLOps
- CI/CD
- version control
- data science
- software development
- enterprise AI
- Responsible AI
- data governance
- AI prototyping
- AI engineering
- data integration
Seniority
Senior
Languages
- English