Staff Machine Learning Engineer

Key Skills

Aartificial intelligence, Algorithms, Analytical and Problem solving, C++, Data Analytics, Data science techniques, Machine learning techniques, Planning and organization, Python Programming, PyTorch, TensorFlow

Job Description

Job Responsibilities:

• 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 Mercedes-Benz internal groups, and at external events such as academic conferences and tradeshows
• Define, interface and manage relationships with other teams within MBRDNA and Mercedes-Benz organizations
• Work closely with a proactive, highly motivated engineering team to bring next generation infotainment and telematics solutions to Mercedes-Benz products worldwide
• Work in an Agile/Scrum environment to deliver high quality software with a measurable customer value

Minimum Qualifications:

• Master’s, Computer Science, Electrical Engineering, Math, Statistics, or related fields
• 4-6 years of experience
• Strong programming and software development skills (Python/C++)
• Hands-on experience with implementation, analysis and updating machine learning and AI algorithms in real world products
• Deep 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
• Ability to quickly and effectively diagnose issues, evaluate fixes, and propose solutions for statistical data analysis and machine learning techniques (including Regression, Classification, Clustering, Time series, Deep learning)
• Strong instincts for efficiency and optimization, with self-motivation to work with colleagues such that only high quality products reach customers' hands.
• Extensive experience with ML frameworks such a PyTorch and Tensorflow
• Excellent understanding of ML workflow: preparing the data, implementing and training ML models, evaluating results, deploying inference on different platforms
• Ability to collaborate effectively and pro-actively in cross functional development teams
• Experience leading research topics through a full research pipeline: from concept to proof and validation
• Very strong interest and passion in machine learning, data science and related fields
• Excellent communication, especially written, and organizational skills, with both technical and non-technical audiences
• Excellent critical thinking, problem solving and analytical skills
• Valid CA Driver’s License

Preferred Qualifications:

• Experience in one or more of the following areas: Recommendation Systems, Bayesian inference and Gaussian processes, Time series, GNNs, Information retrieval and Data mining, Natural Language Processing
• Distributed data processing in Hadoop, Spark, BigQuery, or Apache Beam
• Distributed training

The successful candidate’s starting pay will be determined based on a wide range of factors, including, but not limited to, job-related education, skills, and experience, geographic location, and market conditions. The current salary range for this position is as follows and may be modified in the future: $152,300 - $194,100.