LIME · 2 months ago
Machine Learning Intern (m/w/d) – Mandatory Inernship only
United States
Internship
Remote
InternLIME is a company focused on Digital Health Applications, aiming to enhance therapy time for patients through AI solutions. The Machine Learning Intern will design and implement machine learning pipelines, collaborate with product teams, and work on data extraction and processing for model development.
Health CareMedicalMedical Device
Responsibilities
Design and implement machine learning pipelines with a focus on computer vision and deep learning
Identify, extract and process data from relevant data sources for model development
Create tests and evaluations to assess the application performance of machine learning models
Collaborate closely with our software and product teams
Continuously develop yourself and think outside the box
Qualification
Required
You have significant experience in Python, Java, or a similar high-level programming language
You have experience in one or more of the following areas: machine learning, neural networks, deep learning, computer vision, TensorFlow, PyTorch, Keras, big data management, data pipelines
You have experience working with shared codebases in a professional environment
You have experience in data science or working with large amounts of data
You are familiar with clean coding principles and software testing
You are clever and creative – you question the status quo and contribute your ideas
You need to complete your Mandatory Internship for your studies with us
Benefits
One Team One Dream: Be part of the mission, take on responsibility, and grow with us.
Best Ideas Win: Be part of an inspiring team where arguments count more than positions.
Continuous Growth: Grow beyond yourself through continuous learning with courses, mentoring, and feedback.
Freedom & Responsibility: Decide for yourself when, where, and how you work. In the end, results are what count.
Company
LIME
LIME develops, produces and sells innovative rehabilitation robotics for hand therapy.
Founded in 2016
11-50 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase