Job Location : Boston,MA, USA
Are you a problem solver looking for a hands-on internship position with a market-leading company that will help develop your career and reward you intellectually and professionally?
Analog Devices, Inc. is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world.
At ADI, you will learn from the brightest minds who are here to help you grow and succeed. During your internship, you will make an impact through work on meaningful projects alongside a team of experts. Collaborating with colleagues in an environment of respect and responsibility, you will create connections that will become a part of your professional network.
ADI's culture values aligned goals, work-life balance, continuous and life-long learning opportunities, and shared rewards. The internship program features various lunch-and-learn topics and social events with other interns and full-time employees.
At ADI, our goal is to develop our interns so they are the first to be considered for full-time roles.
Apply now for the opportunity to grow your career and help innovate ahead of what's possible.
Job DescriptionAs a Machine Learning Engineering Intern, you will work with the engineering team to gain hands-on experience in developing machine learning models and improving product performance. You will assist in the design and implementation of algorithms, helping to structure, analyze, and leverage data for various applications. This internship provides an opportunity to learn about machine learning methodologies, programming, and data management in real-world projects.
Key ResponsibilitiesAnalog Devices is an equal opportunity employer. We foster a culture where everyone has an opportunity to succeed regardless of their race, color, religion, age, ancestry, national origin, social or ethnic origin, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, parental status, disability, medical condition, genetic information, military or veteran status, union membership, and political affiliation, or any other legally protected group.