6 дней назад
Senior Software Engineer (AI/ML)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Software Engineer (AI/ML): Building user interfaces, RESTful APIs, and internal tooling that bring AI-powered capabilities and ML models to an enterprise intelligence platform with an accent on end-to-end feature ownership, API design, and scalable software delivery. Focus on integrating complex model outputs, optimizing ML platform architecture and performance, and designing tooling for deploying, testing, monitoring, and operating ML pipelines.
Location: Remote within Canada; preference given to candidates in New Brunswick or Nova Scotia.
Company
provides an AI-powered B2B Relationship Intelligence platform that helps organizations turn relationship data into actionable insights.
What you will do
- Extend enterprise applications with user interfaces and RESTful APIs that expose AI-powered capabilities.
- Collaborate with ML engineers, UX designers, and product managers to turn model outputs and user requirements into production-ready features.
- Own features end to end, including database and API design, front-end implementation, and deployment.
- Improve architecture, performance, scalability, and reliability across the ML platform.
- Build internal tooling for deploying, testing, monitoring, and operating ML models and pipelines.
- Contribute to code reviews, testing strategies, documentation, mentorship, and technical roadmap discussions.
Requirements
- University degree or equivalent in Computer Science, Software Engineering, or a related field.
- 7+ years of professional software development experience.
- Strong proficiency in at least one back-end language, with experience designing, building, and consuming RESTful APIs.
- Proficiency with modern front-end frameworks such as React, Vue, or Angular.
- Strong SQL skills and experience with relational databases.
- Experience with Git, branching, pull requests, code reviews, and Agile development.
Nice to have
- Experience with ML workflows, LLM-based systems, or ML frameworks.
- Familiarity with the Model Context Protocol.
- Experience with Snowflake, dbt, AWS, Docker, Kubernetes, CI/CD, or DevOps practices.
Culture & Benefits
- Outcome-focused environment that values results over hours.
- Collaborative culture built around trust, empowerment, curiosity, and mutual support.
- Opportunities for professional growth with tools and support for effective engineering work.
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