Intern – AI/ ML Data Engineer Research – Cambridge, MA – Summer 2024

Key Skills

3D data processing, Aartificial intelligence, Apache Airflow, Data Engineering, Data science techniques, Deep Learning, Effective communication skills, Machine learning techniques, NumPy, Pandas, Python Programming, SciPy, SPARK Programming, Writing

Job Description

Are you interested in an Internship opportunity with Philips? We welcome individuals who are currently pursuing an undergraduate (BS) and/or graduate (MS) degree to participate in paid intern opportunities. Through this role you will gain meaningful, hands-on experience working for a HealthTech company.

Your role:

• Collaborate with a team of scientists and engineers on a challenging project aimed at solving real-world healthcare problems.
• Develop advanced data automation and visualization pipelines to manage, curate, and analyze large-scale patient medical images and annotations collected from multi-center clinical studies.
• Streamline and accelerate the development of artificial intelligence / deep learning models that will be deployed on state-of-the-art ultrasound imaging platforms to improve patient outcomes.
• Contribute to invention disclosures and publications where possible.

You are a part of:

• A leading research team that is part of Philips’ Global Ultrasound Research organization based in our Cambridge, MA hub, specializing in medical ultrasound imaging and machine learning.
• In this internship, you will apply your data science / engineering background to develop advanced automation / visualization pipeline to manage and analyze large-scale patient imaging data.

You're the right fit if: 

• S. or M.S. in a biomedical data-related discipline, including Computer Science / Electrical Engineering / Biomedical Engineering, or Physical Sciences.
• Experience working with large-scale medical imaging and annotation datasets.
• Strong Python programming skills for data processing (Pandas, SciPy, NumPy) and data visualization (Matplotlib, ggplot) are required.
• Proficiency with Python-based open-source data processing, workflow, and analytics tools (Apache Airflow, Apache Spark, Databricks, etc.) is preferred.
• Familiarity with machine / deep learning model training (including Pytorch) is preferred.
• Ability to communicate effectively, both written and verbal.
• You must be able to successfully perform the following minimum Physical, Cognitive and Environmental job requirements with or without accommodation for this Office/Remote position.

About Philips

We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help improve the lives of others. 

• Learn more about our business.
• Discover our rich and exciting history.
• Learn more about our purpose.
• Read more about our employee benefits.

If you’re interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our commitment to diversity and inclusion here.

Philips Transparency Details 

The hourly pay range for this position is $28.00-46.00 plus overtime eligible. The actual base pay offered may vary depending on multiple factors including, job-related knowledge/skills, experience, business needs, geographical location, and internal equity.

Details about our benefits can be found here.

At Philips, it is not typical for an individual to be hired at or near the top end of the range for their role and compensation decisions are dependent upon the facts and circumstances of each case.

Additional Information

US work authorization is a precondition of employment. The company will not consider candidates who require sponsorship for a work-authorized visa, now or in the future.

Company relocation benefits will not be provided for this position. For this position, you must reside in or within commuting distance to the job posting location.