Applied ML Engineering Student

Key Skills

3D data processing, AWS, Azure, Data science techniques, Docker, Google Cloud Platform (GCP), Kubernetes-K8s, Machine learning techniques, Python Programming, PyTorch, Scikit-learn, TensorFlow

Job Description

NVIDIA is looking for a Machine Learning Engineer Intern to join our team. As a Machine Learning Engineer Intern, you will collaborate closely with Data Scientists and ML Researchers to develop innovative ML solutions and proof-of-concepts. This position allows you to make a real impact in a dynamic, technology-focused company by building user-friendly web interfaces for ML applications, managing cloud-based infrastructure, and ensuring the performance and accuracy of ML models in production.

What you'll be doing:

• Collaborating with Data Scientists and ML Researchers to understand project requirements and objectives.

• Designing and implementing web interfaces for ML applications using frameworks like Streamlit.

• Developing and maintaining backend services in Python for data processing, model inference, and integration into application workflows.

• Setting up and managing cloud-based infrastructure for ML models, including scheduling automated inference and retraining jobs.

• Implementing performance monitoring systems for ML models in production.

• Documenting the development process, system architecture, and user guides for technical teams and end-users.

• Participating in team meetings and brainstorming sessions to improve project outcomes.

What we need to see:

• Enrollment in a Bachelor’s or Master’s program in Computer Science, Engineering, Data Science, Machine Learning, or a related field.

• Strong programming skills in Python, with experience in web development frameworks preferred.

• Familiarity with ML concepts and experience using ML libraries like scikit-learn, TensorFlow, PyTorch.

• Experience with cloud computing services (AWS, Google Cloud, Azure) and knowledge of Docker, Kubernetes is a plus.

• Ability to work effectively in a team, with strong communication skills and a commitment to achieving project goals.

• Self-motivated learner with a passion for technology.

Ways to stand out from the crowd:

• Demonstrated experience in developing and deploying ML applications.

• Knowledge of advanced ML techniques and algorithms.

• Experience with performance optimization of ML models in a cloud environment.

NVIDIA has some of the most forward-thinking and hardworking people in the world working for us. Are you creative and autonomous? Do you love the challenge of applying your academic knowledge to real-world problems and gaining valuable experience in ML engineering? If so, we want to hear from you. Join our team and help us develop cutting-edge machine learning projects from conceptualization to deployment in this exciting and quickly evolving field.