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Form of workGroup Description
We are committed to quality and continuous improvement because our products impact millions of people every day. But we’re more than what we make. We are a group of entrepreneurial-minded people whose collective expertise gives us a competitive advantage. World Class Manufacturing is a journey and it’s our talented people who lead us on this journey.
Role Summary
Magna New Mobility is a startup inside Magna International, a mobility technology company and one of the largest automotive suppliers in the world. The New Mobility team is building a suite of products and services all about moving things and people at scale, closely integrated with software to achieve our unique and ambitious hardware visions. So far we have developed and partnered on products in the micromobility market (Yulu, Yuma, Cartken, among others) and have other projects and target markets that are still in stealth mode. MNM is seeking a Senior Machine Learning Operations Engineer to join our Software Platform team. In this role you will critically impact the successful creation of our PaaS infrastructure. ML Ops Engineer candidates need to have deep knowledge of infrastructure, coding, cloud platforms, containers, Kubernetes, and building data engineering pipelines for ML. This role will be hybrid in our Lowell, MA office. #LI-Hybrid
Key Responsibilities
- As the Senior MLOps Engineer, you will lead the design, implementation, and operation of a platform to enable the training, validation, serving, and monitoring of ML models.
- Support team in building training, model management/deployment tools, and modeling libraries
- Working with tools such as Kafka, AWS (s3, Sagemaker, etc), glue, athena, Git
- Design, construct, and sustain ML Ops pipelines and infrastructure on AWS.
- Establish continuous integration/continuous deployment (CI/CD) workflows for software and machine learning models.
- Work in close collaboration with data scientists, engineers, and other stakeholders to transition software and ML models into a production environment.
- Monitor the performance metrics of software and ML models and resolve any issues that may occur.
Key Qualifications/Requirements
- Bachelor's Degree or Equivalent Experience in Computer Science, Engineering, or other relevant studies
- Demonstrable experience in MLOps, preferably within an AWS setting.
- Experience in building automation tools and scripts, using coding languages such as Python.
- Familiarity with configuration management tools like Ansible.
- Experience with Kubernetes container orchestration, microservices and cloud platforms
- Strong knowledge of MLOps practices, CI/CD pipelines, and infrastructure as code
