Machine Learning Engineer

About Mettler Toledo

METTLER TOLEDO is a global leader in precision instruments and services. We are renowned for innovation and quality across laboratory, process analytics, industrial, product inspection, and retailing applications. Our sales and service network is one of the most extensive in the industry. Our products are sold in more than 140 countries, and we have a direct presence in approximately 40 countries. For more information, please visit www.mt.com.

Our Opening and Your Responsibilities

* Join the Global Finance Carbonation team to design, implement, and maintain classical machine learning models that drive process and system improvements.

* Improve processes/systems with diagnostic analytics, data mining, process mining.

* Execute data analytics, predictive analytics, AI/ML projects.

What You Need to Succeed

Education Qualification:

* B.E., B.Tech., BSc. (Comps/IT), MSc. (Comps/IT)

Technical Skills:

* Python programming

* Classical ML techniques: regression, decision trees, clustering, ensembles, time series forecasting

* Large datasets handling & end-to-end ML pipelines

* Data collection, cleaning, preprocessing

* Feature engineering

* Model validation & statistical assessment

* Interpretation & communication of model insights

Our Offer to You

* "One Team" that thrives on collaboration and innovation.

* Opportunities to work with Global teams.

* An open, fair and inclusive environment

* Multitude of learning and growth opportunities

* Medical insurance for you & your family, with access to Telemedicine application

* A brand name that is identified worldwide with precision, quality, and innovation.

Equal Opportunity Employment

We promote equal opportunity worldwide and value diversity in our teams in terms of business background, area of expertise, gender and ethnicity. For more information on our commitment to Sustainability, Diversity and Equal Opportunity please visit us [1] here.

References

Visible links

1. https://www.mt.com/us/en/home/microsites/sustainability/reporting.html