Machine Learning DevOps Engineer

5 days ago

Old Toronto, Ontario, Canada MCIS Language Solutions Full time
About MCIS Language Solutions

MCIS Language Solutions is a non-profit social enterprise that provides high-quality translation and interpretation services. We are committed to leveraging cutting-edge technology to enhance our service delivery and are embarking on an ambitious plan to adopt AI and other automation technologies.

Job Summary

We are seeking a skilled and passionate Machine Learning DevOps Engineer to lead our efforts in building pre-trained large language models using Azure OpenAI and developing custom automation routines. The successful candidate will be responsible for designing, building, and deploying scalable AI and ML models and solutions, collaborating with cross-functional teams, and ensuring the solutions meet our business needs and enhance our service capabilities.

Key Responsibilities
  • Model Design, Build & Deployment:
    • Design, build, and deploy scalable AI and ML models and solutions, with a focus on generative AI technologies.
    • Deploy AI/ML models to cloud or on-premises environments, ensuring scalability and reliability.
  • Collaboration & Integration:
    • Collaborate with data scientists and engineers to translate prototypes into production-level applications.
    • Work closely with cross-functional teams, including data scientists, product managers, and software engineers, to align AI/ML solutions with business goals.
    • Integrate AI/ML solutions with existing systems and workflows.
  • Front-End & Back-End Development:
    • Develop front-end applications to support AI/ML solutions, ensuring seamless user experiences.
    • Implement back-end services, APIs, and data pipelines to support AI/ML model integration and deployment.
  • Monitoring & Maintenance:
    • Monitor and maintain deployed models, optimizing performance and managing updates as needed.
  • Automation:
    • Automate deployment pipelines using CI/CD tools to ensure rapid and reliable delivery of AI/ML solutions.
    • Assist MCIS with the implementation of automation routines on top of our existing solutions as required.
  • Security & Compliance:
    • Implement security measures to protect sensitive data and ensure compliance with data privacy regulations.
  • Continuous Learning & Advancement:
    • Stay updated with the latest advancements in AI/ML and generative AI technologies.
Requirements
  • Core Competencies:
    • Communication: The ability to effectively convey and exchange information, ideas, and thoughts to others through various channels in a clear, concise, and appropriate manner, while also actively listening and seeking understanding.
    • Innovation: The ability to identify new ideas, solutions, and approaches to address challenges, improve processes, and create value.
    • Integrity: The ability to consistently adhere to ethical principles, moral values, and professional standards in all actions and decisions.
    • Collaboration: The ability to work effectively and harmoniously with others to achieve common goals.
    • Quality: The ability to consistently deliver work, products, and services that meet or exceed established standards, resulting in value, reliability, and customer satisfaction.
    • Advocacy: The ability to effectively promote and support a cause, idea, or policy in order to bring about positive change, raise awareness, and influence decision-making at various levels.
  • Education & Experience:
    • The Machine Learning DevOps Engineer holds a bachelor's or master's degree in Quantitative Analytics, Statistics, Mathematics, Engineering, Computer Science, or a similar discipline in a related field.
    • The Machine Learning DevOps Engineer possesses 5+ years of experience in designing, building, and deploying AI/ML models in production environments, and 3+ years of experience with CI/CD tools and processes, such as Jenkins, GitLab CI, or Circle CI.
    • The ML DevOps Engineer has experience in working with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization (e.g., Docker, Kubernetes).
    • Proficiency in C# and the.NET framework, including ASP.NET Core.
    • Strong knowledge of front-end technologies (e.g., React, Angular) and back-end technologies (e.g., Django, Flask).
    • Knowledge and experience in Azure are highly preferred.
    • Working knowledge and experience working with AutoHotkey or other automation solutions.
    • Strong problem-solving skills and the ability to troubleshoot issues related to AI/ML models and applications.
    • Familiarity with generative AI models (e.g., GPT, GANs) and their applications.
    • Ability to work independently in a self-directed manner and collaboratively as a team member.
    • Expertise and knowledge in the Localization and Language Services industry are highly desirable but not mandatory.

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