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Staff Engineer, Machine Learning Operations Specialist

2 months ago

Detroit, Michigan, United States Canopy Full time
Unlock the Future of Vehicle Security

Canopy, a Ford-backed company, is revolutionizing vehicle security with cutting-edge technology. We're seeking a highly skilled Staff Engineer, Machine Learning Operations to join our team and help us achieve our mission.

About the Role

This is a critical position that requires a strong background in machine learning operations, software engineering, and data engineering. As a Staff Engineer, you will lead the design, development, and implementation of scalable MLOps pipelines and infrastructure. Your expertise will ensure that machine learning models are efficiently deployed, monitored, and maintained in production environments.

Responsibilities
  • Design, implement, and maintain robust MLOps services and pipelines to automate the deployment and monitoring of machine learning models in production.
  • Collaborate with engineers to integrate machine learning models into existing systems and workflows.
  • Develop and enforce best practices for CI/CD in machine learning projects, including version control, automated testing, and continuous integration.
  • Monitor the performance and health of data and models in production, implementing strategies for retraining, versioning, and rollback when necessary.
  • Optimize infrastructure for model training and inference, ensuring scalability, efficiency, and cost-effectiveness.
  • Work closely with DevOps teams to ensure seamless integration of MLOps pipelines with cloud or on-premises infrastructure.
  • Provide mentorship and guidance to junior engineers and contribute to the development of MLOps strategies and standards across the organization.
Requirements
  • Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
  • 8+ years of experience in software engineering, data engineering, or a related field, with at least 3 years specifically in MLOps.
  • Strong programming skills in languages such as Python, Java, or C/C++.
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Proficiency in DevOps tools and practices, including Docker, Kubernetes, and CI/CD pipelines.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Strong understanding of version control systems like Git and experience with infrastructure as code (IaC) tools such as Terraform or CloudFormation.
Preferred Qualifications
  • Reside within the Detroit area or nearby, with the ability to work in a hybrid environment and regularly commute to our Detroit office as needed.
  • Master's degree or Ph.D. in Computer Science, Data Science, Engineering, or a related field.
  • Experience with advanced MLOps practices such as feature stores, model interpretability, and fairness in AI.
  • Familiarity with big data technologies like Apache Spark, Hadoop, or Kafka.
  • Experience with monitoring and observability tools such as Prometheus, Grafana, or ELK stack.
  • Previous experience leading or mentoring a team of engineers in an MLOps or DevOps context.
  • Strong understanding of security best practices in the context of machine learning and AI.
What We Offer

At Canopy, we offer a comprehensive benefits package, including comprehensive medical benefits coverage, dental plans, and vision coverage. We also offer health care and dependent care spending accounts, an Employee and Family Assistance Program (EAP), employee discount programs, a retirement plan with a generous company match, generous Paid Time Off, Sick, and Holidays, Family Leave (Maternity, Paternity), Short- and long-term disability, and Life insurance and accidental death & dismemberment insurance.

Our base salary range is $129,200 - $180,500, and compensation may vary depending on skills and experience.