Machine Learning Engineer

NI’s Optimal+ platform is playing in the field of Industrial IoT and is the only Big Data analytics platform that provides an end-to-end product analytics solution for automotive, semiconductors and electronics companies. 

The data science group is led from the Israel R&D site. This group is responsible for both customer engagement and company level machine learning strategy, infrastructure, and roadmap. 

As leaders in the field, we have an important role in bringing the full AI potential to manufacturing, we are working closely with our customers delivering the right platform for machine learning together with the right solutions, infrastructures, and methodologies to handle the full life cycle of machine learning in production.

Description:

The Senior ML Engineer will be responsible for demonstrating made valuable contributions of the NI Optimal+ SW solution through usage of advanced machine learning methods and development of robust machine learning solutions and applications using innovative techniques. 

As part of the company AI roadmap, the senior ML engineer will be responsible for evaluating different ML frameworks, algorithms, methodologies and tools, build generic machine learning applications (from use case initiation to actual deployment) and initiate improvements of internal and external (customers) methods and practices.

The Industrial domain is very challenging as it comes to machine learning implementation and deployment due to the high cost of escapes/model inaccuracy, business workflow complications, IT restrictions and regulation. 

If you are very skilled in ML, motivated by challenges and want to take a leading part in bringing the AI revolution to Industrial IoT – this may be the right position for you.

In this Role, Your Responsibilities Will Be: 

• Collaborate with data scientists, SW architects, developers, and product managers to solve complex customer problems, and highlight opportunities on top of the NI Optimal+ solution using advanced machine learning methods
• Develop and communicate predictive and prescriptive insights/algorithms, and models
• Design, and implement automated classification and prediction solutions using big data analytics and machine learning techniques 
• Use machine learning and statistical modeling techniques to develop and evaluate algorithms for improving customers’ process and product quality
• Help design and implement infrastructures for robust and scalable machine learning life cycle support

Who You Are:

You provide direct and actionable feedback and show personal commitment and take action to continuously improve. You push yourself and help others achieve results.

For This Role, You Will Need:

• Relevant education or equivalent experience
• Strong analytical skills
• Validated experience with machine learning and deep learning techniques in production 
• Proficiency in Python and machine learning tools
• Industrial experience– a big advantage
• In depth knowledge of statistical methods along with experience in data analysis and data mining
• Customer facing and presentation skills 

Preferred Qualifications that Set You Apart:

• Creative personality who thinks in an unexpected way

Our Offer To You:

We understand the importance of work-life balance and are dedicated to supporting our employees' personal and professional needs. From competitive benefits plans and comprehensive medical care to equitable opportunities for growth and development we strive to create a workplace that is supportive and rewarding. 

Depending on location, our flexible work from home policy allows you to make the best of your time, by combining quiet home office days with collaborative experiences in the office so that you can personalize your work-life mix. 

Moreover, our global volunteer employee resource groups will empower you to connect with peers that share the same interest, promote diversity and inclusion and positively contribute to communities around us. 

All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, or national origin.