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    Canada-ABAP Developer IV - Toronto, Canada - TalentBurst, Inc.

    TalentBurst, Inc.
    TalentBurst, Inc. Toronto, Canada

    1 week ago

    Default job background
    Contract
    Description

    Job Title:
    Software Engineer, Machine Learning – Digital R&D Large Molecule Research Team

    Location:
    Toronto, ON M5V 1V6

    Duration: 06 Months

    Description

    You are a seasoned Software Engineer interested in leveraging large scale Client systems to augment the drug discovery process while also scaling up AI solutions for the patients of tomorrow.

    You are comfortable working in large teams with disparate stakeholders where you can lead and champion technical decisions.

    You have experience deploying AI/Client 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 Client 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, Client products with automated pipelines that run, monitor, and retrain Client Models
    Design AI/Client 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 Client applications (e.g., new releases, change management, monitoring and troubleshooting).

    Work as Client systems architecture design SME (e.g., develop and maintain enterprise standards, user guides, release notes, FAQs)
    Build processes supporting seamless Client 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/Client 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 Client pipelines and architectures.
    Experience working in an agile pod supporting and working with cross-functional teams.

    Good understanding of Client 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 Client 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/Client 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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