Machine Learning Engineer, MLOps

Embedded in a worldwide network Mercedes-Benz Research & Development North America continuously strives to remain at the forefront of successful automotive research and development. MBRDNA is headquartered in Silicon Valley, California, with key areas of Autonomous Driving, Advanced Interaction Design, Digital User Experience, Machine Learning, Customer Research, and Open Innovation. In Redford, Michigan, the focus is on Powertrain and eDrive technology as well as in Long Beach, where the teams test durability of the latest driver assistant and telematic systems. The Digital Hub in Seattle focusses on developing a cloud architecture and building out the cloud platform for the next generation of connected car services. The Testing and Regulatory Affairs Division in Ann Arbor and the Advanced Vehicle Design in Carlsbad complete the competence center.
The data and AI team is seeking a hands-on machine learning expert to support building a unified MLOps platform in a way that supports a wide range of diverse use cases enabling projects that will shape the future of Mercedes-Benz vehicles. In this role, you will be responsible for developing ML pipelines, tools and features to support experimentation, continuous integration, deployment (CI/CD), verification, validation, and monitoring of ML models in production while addressing the challenges of strong data privacy and responsible AI principles.
You will be working closely with the development team to support the product development to bring next generation infotainment and telematics solutions to Mercedes-Benz products worldwide.

Job Responsibilities:

• Architect a unified MLOps methodology that ML teams can follow to be highly productive and deliver safe AI products
• Define and spread the best MLOps practices of automation, monitoring, scale and safety
• Continuously evaluate the latest packages and frameworks in the ML ecosystem
• Work in an Agile/Scrum environment to deliver high quality software with a measurable customer value
• Lead research topics through multiple phases related to automotive machine learning solutions: experimentation and validation, proof of concept, tuning and constraint adjustment.
• Provide support and insight to development teams responsible for implementation of machine learning techniques in a native head unit environment
• Present and demo research topics to Daimler internal groups, and at external events such as academic conferences and tradeshows 

Minimum Qualifications:

• Minimum level of education required: Bachelors, Computer Science, Electrical Engineering, Math, Statistics, or related fields
• Strong programming and software development skills in Python, Scala or C/C++
• Building end to end data systems as an ML Engineer, Platform Engineer, or equivalent
• Experience with distributed cloud computing platforms, particularly Kubernetes or the Hadoop/Spark ecosystem
• Experience working with cloud data processing technologies
• Experience in ML model serving
• Proficiency with ML modeling frameworks
• Hands-on experience with implementation, analysis and updating machine learning and AI algorithms in real world products
• Good understanding of machine learning fundamentals. Ability to keep up with the bleeding edge of research in the field, understand its ramifications, and immediately apply it to the betterment of our products  
• Strong instincts for efficiency and optimization, with self-motivation to work with colleagues such that only high quality products reach customers' hands. 
• Ability to collaborate effectively and pro-actively in cross functional development teams
• Excellent communication, especially written, and organizational skills
• Desire to lead research topics through a full research pipeline: from concept to proof and validation

Preferred Qualifications:

• Experience in distributed machine learning architectures and/or federated learning
• Experience in one or more of the following areas: Recommendation Systems, Natural Language Processing, Information retrieval and data mining, Bayesian inference and gaussian processes

Why should you apply? Here at MBRDNA, you create digital ecosystems around cars, you design a language between humans and machines, you make a car even more intelligent - you make the new reality for cars. Our benefits include medical, dental and vision insurance, 401k savings plan, tuition and fitness reimbursement programs and much more.  We have an open and flexible environment to allow you to push boundaries, join MBRDNA and design your future. MBRDNA is an equal opportunity employer (EOE) and strongly supports diversity in the workforce. MBRDNA only accepts resumes from approved agencies who have a valid Agency Agreement on file. Please do not forward resumes to our applicant tracking system, MBRDNA employees, or send to any MBRDNA location.  MBRDNA is not responsible for any fees or claims related to receipt of unsolicited resumes.
Thank you for your interest in Mercedes-Benz Research & Development North America. Please be aware the impact of COVID-19 could increase the amount of time it takes our HR and Hiring Team to process your application. We apologize for any inconvenience this may cause. We are dedicated to the health and safety of our employees and candidates. We appreciate your patience during this time.
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