Machine Learning Intern - Summer 2025

As a Machine Learning Intern at MyFitnessPal, you will be involved in implementing recent advances in deep learning and image recognition. Your core responsibilities will include training image recognition models, evaluating their performance, and curating datasets to enhance model accuracy. You'll be part of a creative team focused on ensuring that our products effectively meet users' needs, providing you with invaluable hands-on experience in machine learning.

To qualify for the Machine Learning Intern role at MyFitnessPal, candidates must be current full-time college students with at least one academic term remaining after the internship. Ideal candidates will have a strong background in Python and experience with PyTorch, as well as familiarity with recommendation systems and large language models. Knowledge of distributed training frameworks and AWS can be beneficial but is not strictly required.

For the Machine Learning Intern position at MyFitnessPal, proficiency in Python and hands-on experience with PyTorch are essential technical skills. Familiarity with large-scale multimodal models, such as vision-language models, as well as knowledge of common recommendation systems, will be advantageous. It is a plus if you have experience with distributed training frameworks like PyTorch Distributed or DeepSpeed.

As a Machine Learning Intern at MyFitnessPal, you can expect to work on impactful projects that focus on deep learning and image recognition. You’ll help train various models and evaluate their effectiveness in real-world applications. These projects aim to enhance our product offerings and directly influence user experiences, providing you with an opportunity to make a tangible impact during your internship.

Machine Learning Interns at MyFitnessPal benefit from a supportive remote work environment and a competitive pay rate of $25.00 per hour. The internship offers opportunities for mentorship and guidance from experienced staff. High-performing interns also have the potential to secure full-time positions upon graduation, with access to various employee benefits, a dynamic work culture, and a chance to contribute to a meaningful mission.

Certainly! When discussing a machine learning project in your interview for the Machine Learning Intern position at MyFitnessPal, focus on your role, the technologies you used, and the impact of the project. Explain the problem you aimed to solve, the approach you took (e.g., model selection, data preparation), and the results you achieved. Highlight any challenges faced and how you overcame them, demonstrating your problem-solving skills and technical knowledge.

Evaluating the performance of a machine learning model typically involves using metrics such as accuracy, precision, recall, and F1-score. During your interview, explain the importance of selecting the right metric based on the problem context. Discuss your experience with cross-validation and how it can help prevent overfitting. Providing specific examples of how you applied these techniques will demonstrate your understanding of the evaluation process.

Data preprocessing is crucial because it directly affects the quality and performance of your machine learning models. In your answer, discuss steps like data cleaning, normalization, feature selection, and their role in improving model accuracy. Providing an example from past projects where preprocessing made a significant difference would showcase your practical knowledge in this area.

Common challenges include dealing with imbalanced datasets, overfitting, underfitting, and ensuring appropriate feature selection. In your interview, elaborate on how you've addressed these challenges in your previous work, such as using techniques like stratified sampling or regularization to improve model performance. Your ability to navigate these issues will reflect your readiness for the role at MyFitnessPal.

Staying updated in the fast-paced field of machine learning is essential. Discuss your strategies, such as reading research papers, attending webinars, subscribing to relevant journals, or participating in online courses. Mention specific sources, like arXiv, Google Scholar, or industry conferences where you gather insights about cutting-edge technologies and trends.

When discussing your Python experience, choose a specific project where you utilized it for data analysis, model implementation, or visualization. Focus on the libraries you used, such as Pandas for data manipulation or Scikit-learn for model building. Detail your contribution and the outcome, reinforcing your programming skills and their application in machine learning.

Using version control systems like Git is vital for managing code and collaborating within a team. Emphasize your experience with Git commands, branching strategies, and collaboration on GitHub or GitLab. Give an example of how Git helped in managing a project, especially in situations involving multiple team members or when needing to roll back changes.

In the context of machine learning, collaboration is key to success. Discuss your preferred methods for maintaining communication, sharing responsibilities, and integrating different perspectives. Share an anecdote about how collaboration led to improved results, emphasizing your interpersonal skills and your alignment with MyFitnessPal's core value of being kind and caring.

Describe a specific project where you implemented deep learning architectures, such as CNNs for image recognition or RNNs for sequential data. Highlight the frameworks you used (like TensorFlow or PyTorch) and the outcomes achieved, discussing how the chosen architecture contributed to the success of the project. This reflects your practical knowledge and hands-on experience.

Express your passion for the mission of MyFitnessPal to empower healthier lifestyles and how machine learning technology plays a significant role in improving user experiences. Share specific aspects of the internship that excite you, such as chance to work on impactful projects, the potential for mentorship, or the company’s core values. This shows your genuine interest in the position and aligns with their culture.