As a Machine Learning Engineer, you are responsible for growing our Machine Learning portfolio, with a specific focus to bring scalable multi-modal sensing solution to life.
You aim at a highly technical role and you thrive in a dynamic environment that requires a unique blend of innovation, risk taking and speed of execution. You combine excellent oral and written communication skills and an ability to autonomously plan and organize your work assignments based on high-level team goals. You will be working with the team of experts in several areas. You join a group of engineers with a very diverse skillset, but united by their passion for innovation and the excitement of turning wildly disruptive ideas into products that impact the industry at large. You will join our effort in building our next-generation machine learning platform.
We love building products that change the consumer and automotive industries by combining edge computing and AI. Our technology stack includes the latest innovations both supervised and unsupervised learning, including the latest deep learning algorithms and machine learning frameworks such as TensorFlow, Caffe, Keras, FastAI, Spark and Go
- Agile, pragmatic, hardworking and a “can do” mentality. You also love to interact with data scientists, machine learning engineers, software engineers and domain experts in order to develop pipelines that process seamlessly large amounts of data. You love technology, innovation and building products with scalability in mind.
- You hold a degree in computer science or a related field and you can demonstrate a consistent track record in the following areas:
- Several years of experience architecting, building, developing and scaling ML systems. Having implemented and deployed a variety of machine learning pipelines production environments would be a strong plus.
- Excellent software development and scripting skills c/c++, Java and Python
- Real-time processing of image and/or large amounts of sensor data
- Hands-on experience, micro-service architectures (e.g., Docker, Kubernetes), and ML libraries (e.g., Scikit-Learn, TensorFlow, Keras)
- Excellent English spoken and written skills
- Experience with scalable cloud infrastructures such as AWS and Azure
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