Software Engineer, Machine Learning

4 weeks ago

Toronto ON, Canada ALTEN Canada - Toronto division Full time

Software Engineer, Machine Learning

Toronto, ON

This is positioned to be a unique data-driven team, with expertise in AI platforms, data engineering, ML operations, data science, computational biology, strategy, and beyond. We are working as one to identify, design, and scale state-of-the-art AI capabilities targeted to truly transform how we research biologics.

Who You Are:

You are comfortable working in large teams with disparate stakeholders where you can lead and champion technical decisions. You have experience deploying AI/ML solutions with technically robust lifecycle management (e.g., new releases, change management, monitoring and troubleshooting) and infrastructural support. You have a keen eye for improvement opportunities and a demonstrated ability to deliver using software engineering and ML software integration skills while working across the full stack and moving fluidly between programming languages and technologies.

Job Highlights:

• Work in agile pods to design and build cloud hosted, ML products with automated pipelines that run, monitor, and retrain ML Models

• Design AI/ML apps and implement automated model and pipeline adaption and validation working closely with data scientists and data engineers

• Support the full MLOps life cycle of new and existing ML applications (e.g., new releases, change management, monitoring and troubleshooting).

• Work as ML systems architecture design SME (e.g., develop and maintain enterprise standards, user guides, release notes, FAQs)

• Build processes supporting seamless ML integrations (e.g., app monitoring, troubleshooting, life cycle management and customer support)

• Maintain effective relationships with application userbase to develop education and communication content as per life cycle events

• Research and gain expertise on emerging tools and technologies. An enthusiasm to ask questions and try and learn new things is essential.

Key Functional Requirements & Qualifications:

• Experience in data science, statistics, software engineering, modular design and design thinking.

• Experience developing CI/CD pipelines for AI/ML development, deploying models to production, and managing the lifecycle in a regulated environment.

• Experience building and deploying data science apps with large scale data and ML pipelines and architectures.

• Experience working in an agile pod supporting and working with cross-functional teams.

• Good understanding of ML and AI concepts and hands-on experience in development, deployment and agile life cycle management of data science apps.

• Ability to assess new technologies and compile architecture decision records (ADRs).

• Excellent communication skills in English, both verbal and in writing.

Key Technical Requirements & Qualifications:

• Graduate degree in Computer Science, Information Systems, Software Engineering or another quantitative field

• Ability to work across the full stack and move fluidly between programming languages (e.g.: Python, SQL, Spark) and ML frameworks (e.g.: Airflow, MLFlow, Argo)

• Experience in cloud and high-performance computing environments

• Experience in AWS (e.g.: S3, Lambda, SageMaker, EKS, CloudWatch)

• Knowledge of relational and non-relational databases

• Nice to have knowledge of visualization technologies (e.g.: Tableau, PowerBI)

• Experience in development, deployment and operations of AI/ML modelling of complex datasets

• Experience in developing and maintaining APIs (e.g.: REST, gRPC)

• Experience specifying infrastructure and Infrastructure as a code (e.g.: Docker, Kubernetes, EKS, Terraform)

• Mentoring and/or technology evangelism/advocacy experience preferred

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