Machine Learning DevOps Engineer

  • 2555 Smallman Street, Pittsburgh, PA, United States
  • Employees can work remotely
  • Full-time
  • Legal Entity: Bosch Security Systems Inc.

Company Description

Bosch Building Technology

At Bosch, we are shaping the future with high-quality technologies and services touching everyday life. We are working in the fast-paced field of Internet of Things and Services - an exciting combination of business, technology, software, design and user experience that is driven by the rapid development of connectivity, computing and Big Data analytics. A day at Bosch is full of innovations and teamwork.

We are currently growing our team and searching for a high-potential Machine Learning (ML) DevOps Engineer to create Bosch's next-generation of cloud-based software products for intelligent traffic systems. The team delivers analytic products to our customers via online channels and smart connected devices.

Job Description


  • Build end-to-end scalable data processing pipelines to support model-training, deployment and monitoring in production
  • Apply ML techniques to solve challenging data driven problems
  • Apply your skills to solve real-world challenges, and influence product development for the future
  • Contribute to the development and deployment of next generation algorithms to support behavioural classification, forecasting and prediction, data fusion, or in general improving our current algorithms using advanced data driven models
  • Support end-to-end data analytics and ML products with strong knowledge of operations, software engineering and architecture, and understanding of algorithm design, ML and software stack

Your Responsibilities:

  • Develop next generation data driven models and algorithms for intelligent transportation use-cases

  • Move developed models to production for model serving at scale, and own model lifecycle by monitoring and maintaining model performance (MLOps)

  • Architect and deploy robust data infrastructure to support ML model training, evaluation and deployment (e.g., MLflow, Airflow, Luigi, Metaflow, BentoML)

  • Maintain and monitor the overall health of data infrastructure once they are live.

  • Support tooling for data persistence, transformation, exploration and visualization (e.g., Spark, Hive, Django, Dash, Streamlit)

  • Build and deploy data infrastructure on cloud (e.g., AWS, Azure)


Basic Qualifications:

  • MS in Computer Science, Electrical Engineering, Applied Mathematics or related fields
  • 2+ years of work experience in deploying and maintaining data infrastructure in production environment
  • 2+ years of work experience with Machine Learning techniques (e.g., Deep Learning, SVM, clustering, prediction, time series analysis) and its applications to solve challenging problems in a product development environment
  • 3+ years programming experience, in particular Python

Preferred Qualifications:

  • Industry experience deploying and maintaining ML models at scale
  • Statistical background in Big Data analysis
  • Familiar with Agile development processes
  • Knowledge and experience with: 
    • Linux
    • Networking
    • AWS services, e.g., EC2, S3, Lambda, or similar services from other cloud providers
    • Configuration management or provisioning tools, e.g., Ansible, Terraform, CloudFormation
    • Container and Kubernetes

Additional Information

By choice, we are committed to a diverse workforce - EOE/Protected Veteran/Disabled.

BOSCH is a proud supporter of STEM (Science,Technology, Engineering & Mathematics) Initiatives

  • FIRST Robotics (For Inspiration and Recognition of Science and Technology)

  • AWIM (A World In Motion)

Privacy PolicyImprint