Machine Learning Engineer

Key Skills

Aartificial intelligence, Apache Airflow, Azure, C++, Computer Vision (CV), Data Engineering, Data science techniques, DevOps, Docker, Kubernetes-K8s, Machine learning techniques, MLflow, MLOps tools, Python Programming

Job Description

In our team we are developing the perception of the next generation of automatic parking systems. We are driving the development of the computer vision, ultrasonic sensor perception and creating the necessary Software to turn the sensor raw information into a vector space representation.

This vector space representation is the foundation for industry leading automatic parking functions. With our latest sensor generations, we have successfully introduced machine learning in our products. This was the first step on an exciting journey. There is a lot of opportunity ahead.

• As a MLOps Engineer you will develop and operate machine learning pipelines.
• You will work with structured and unstructured data from our engineering and the customer fleet.
• Your main responsibility is to invent and develop the backbone of ML engineering for automotive applications.
• You will shape the future of automatic parking systems and establishing best practices for embedded AI projects.
• You take responsibility for setting up maintainable and reliable ML pipelines, on which our function developers train the models.
• As part of an agile team your ideas will be heard and impact the decision-making process.
• With our goal to invent for life, you will work on solutions that are both, innovative and ethical.
• You will collaborate with scientists, electrical engineers, machine learning engineers, and data engineers to have real world impact.

Top Skills:

python, C++, machine learning, data acquisition, data science, DevOps, automotive testing, azure, azure automation

Additional Skills & Qualifications:

Education: successfully completed Bachelor's degree in Computer Science or other engineering discipline or foreign equivalent.

3+ years' experience with Linux skills, python, C++ and machine learning principles

3+ years' experience in building and operating ML pipelines and data platforms in production,

3+ years' experience in API design, distributed architectures and orchestration of micro services,

Preferred Qualifications:

Education: successfully completed Master's degree in Computer Science or other engineering discipline or foreign equivalent.

Experience with container-based deployments (e.g. Docker, Kubernetes),

Experience deploying deep networks to a production environment, Model lifecycle management (e.g. MLflow) and workflow automation (e.g. Airflow),

Experience with Cloud and cloud-hybrid solutions (e.g. Azure ML, Azure DevOps)

Experience Level:

Intermediate Level

Diversity, Equity & Inclusion

At Actalent, diversity and inclusion are a bridge towards the equity and success of our people. DE&I are embedded into our culture through:

• Hiring diverse talent
• Maintaining an inclusive environment through persistent self-reflection
• Building a culture of care, engagement, and recognition with clear outcomes
• Ensuring growth opportunities for our people

Actalent is an equal opportunity employer.