Staff Engineer, Machine Learning Operations

2 days ago

Detroit, Michigan, United States Canopy Full time
Job Overview

Canopy, a Ford-backed company, is seeking a highly skilled Staff Engineer, Machine Learning Operations to join its team. As a key member of the engineering team, you will be responsible for designing, developing, and implementing scalable machine learning operations (MLOps) pipelines and infrastructure.

The ideal candidate will have a strong background in software engineering, data engineering, or a related field, with at least 3 years of experience in MLOps. They will be proficient in programming languages such as Python, Java, or C/C++, and have experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.

The Staff Engineer, Machine Learning Operations will work closely with machine learning engineers, data scientists/engineers, and platform/SRE engineers to streamline and automate data ingestion, model deployment, and ensure high availability, reliability, and performance of AI-driven solutions.

Key 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 like TensorFlow, PyTorch, or Scikit-learn.
  • Proficiency in DevOps tools and practices, including Docker, Kubernetes, and CI/CD pipelines.
  • Experience with cloud platforms like AWS, Azure, or Google Cloud Platform.
  • Strong understanding of version control systems like Git and experience with infrastructure as code (IaC) tools like Terraform or CloudFormation.
  • Excellent problem-solving skills, with the ability to troubleshoot complex production issues.

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 like 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 like 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.

Benefits:

  • Comprehensive medical benefits coverage, dental plans, and vision coverage.
  • Health care and dependent care spending accounts.
  • Employee and Family Assistance Program (EAP).
  • Employee discount programs.
  • Retirement plan with a generous company match.
  • Generous Paid Time Off, Sick, and Holidays.
  • Family Leave (Maternity, Paternity).
  • Short- and long-term disability.
  • Life insurance and accidental death & dismemberment insurance.

Base Salary Range: $129,200 - $180,500

Compensation may vary depending on skills and experience.

Diversity, Equity, and Inclusion: At Canopy, we prioritize individuals and stay attuned to the evolving needs of our people, users, and industry trends. We foster a workplace culture that embraces diversity and authenticity, enabling us to flourish as a team of exceptional individuals working towards a common purpose.

Equal Opportunity: Canopy does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity, or any other reason prohibited by law in provision of employment opportunities and benefits.

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