Lincoln Electric

Lincoln Electric is the world leader in the engineering, design, and manufacturing of advanced arc welding solutions, automated joining, assembly and cutting systems, plasma and oxy-fuel cutting equipment, and has a leading global position in brazing and soldering alloys. Lincoln is recognized as the Welding Expert™ for its leading materials science, software development, automation engineering, and application expertise, which advance customers' fabrication capabilities to help them build a better world. Headquartered in Cleveland, Ohio, Lincoln Electric is a $4.2B publicly traded company (NASDAQ:LECO) with over 12,000 employees around the world, with operations in 71 manufacturing and automation system integration locations across 21 countries and maintains a worldwide network of distributors and sales offices serving customers in over 160 countries.

Location: Euclid - 22801

Employment Status: Salary Full-Time

Function: Engineering

Req ID: 26915

Summary

Lincoln Electric has an outstanding opportunity for a Machine Learning Engineer based at our Euclid, Ohio manufatcuring headquarters. As a Machine Learning Engineer (ML Engineer), you will be responsible for designing, developing, and implementing deep learning models to address various challenges in developing vision-based tools. You will work closely with cross-functional teams to integrate these models into our products and services, ensuring they meet performance and scalability requirements.

In addition to competitive pay, Lincoln Electric offers a lucrative profit-sharing plan, student loan repayment program PLUS tuition reimbursement, medical/dental/vision, 401(k) with company match, paid time off and many more outstanding benefits!

• This position has flexibility for hybrid work to be determined as approiate depending on business needs. Candidate must be able to work on-site in Euclid, OH as needed.**

What You Will Do

As an ML Engineer, you will play a key role in a new data science position to help us identify, diagnose, and cure production inefficiencies using data. Specific responsibilities include:

• Model Development: Design and develop deep learning models using frameworks such as TensorFlow, PyTorch, and Keras for specific applications in the manufacturing domain.
• Training and Evaluation: Train models on large datasets, evaluate their performance, and fine-tune hyperparameters to optimize results.
• Deployment: Implement and deploy models in production environments (including cloud-based deployments), ensuring they are scalable and efficient.
• Collaboration: Work with data scientists, software engineers, and product managers to integrate models into applications and services.
• Research: Stay up to date with the latest advancements in deep learning, transformers and graph neural networks and apply new techniques to new applications.
• Documentation: Maintain thorough documentation of model architecture, training processes, and evaluation metrics using ML Flow or equivalent.

Education & Experience Requirements

• Education: Bachelor's or Master’s degree in computer science, Electrical Engineering, or a related field. PhD is a plus.
• Experience: Proven experience (7+ years) in developing and deploying deep learning models. Experience with large-scale datasets and cloud platforms is preferred.
• Skills:
  • Proficiency in deep learning frameworks and ability to design boutique neural networks with data augmentation and attention mechanisms.
  • Ability to write professional software using SOLID programming principles and writing testing protocols for ML code.
  • Working knowledge of using version control tools and principles to collaborate with other team members.
  • Deep knowledge of partial differential equations, scientific computing and statistical methods.
• Soft Skills: Excellent problem-solving abilities, strong communication skills, and the ability to work collaboratively in a team environment.

Lincoln Electric is an Equal Opportunity Employer. We are committed to promoting equal employment opportunity for applicants, without regard to their race, color, national origin, religion, sex (including pregnancy, childbirth, or related medical conditions, including, but not limited to, lactation), sexual orientation, gender identity, age, veteran status, disability, genetic information, and any other category protected by federal, state, or local law.