Job Description :
Drive development of artificial intelligence solutions for a broad range of application fields : automotive functions, robotics, predictive maintenance, IoT, Industry 4.
0 and cognitive process automation.
Promote adoption of state-of-art and novel machine learning technologies, especially in the field of deep learning for data analytics, time series analytics, sensors and IoT data analytics, behavior modeling and prediction, anomaly detection.
Innovate and execute on foundational ML algorithms that spans Deep Learning and data-efficient learning techniques such as Transfer Learning (i.
e. applying learning from one task to another), Single- / Zero-Shot learning (i.e. learning from a small number of labeled samples), and Unsupervised Learning.
Develop novel application concepts using artificial intelligence to enhance company’s products and internal processes and operation (Sales, Marketing, HR, Engineering, Quality etc.)
Act as a technical lead for small research teams and mentor other researchers and engineers.
Initiate and lead innovation projects and oversee modeling research and development efforts.
Provide architectural guidance on transitioning prototypes to high-performance production models.
Proactively identify interesting areas for deep dive investigations and future product development.
Design and execute experiments, and analyze results in collaboration with Product Managers, Business Analysts and other specialists.
Leverage and promote industry best practices to establish repeatable applied science practices, principles & processes.
Work with Continental partners in Industry, Academia and Research Institutes.
Monitor technologies, open source frameworks, commercial tools this field.
Contribute in shaping Continental's Artificial Intelligence and Machine Learning strategy.
Graduate degree (MS or PhD) in (Business) Informatics, Computer Science, Mathematics, Engineering, Computational Neuroscience or Physics with specialization in machine learning.
Strong experience in fundamental ML and Deep Learning models.
Track record of developing novel learning algorithms and / or systems.
3+ years (with PhD) or 5+ years of professional or academic experience in related fields.
Expertise in one or more focus areas : online learning, sequential prediction, graphical models, structured prediction, sequential models, reinforcement learning, imitation learning, planning under uncertainty, Bayesian inference, model compression, multi-
task learning, forecasting etc.
Experience with large datasets and hands-on experience with distributed systems is a plus.
Knowledge in one or more machine learning frameworks (Tensorflow, Caffe, Theano / Keras, Scikit-Learn, Spark / Mlib, R etc.)
Practical experience with data visualization libraries and tools (like Bokeh, Seaborn, D3.js, Tableau etc.)
Familiarity with programming languages such as C / C++, Python, Java or Perl.
Excellent communication skills and capability to present technological concepts coherently to the business and innovation process.
Team player with inter-cultural competencies.
Strong skills in solving analytical problems.
Willingness to Travel.