2024 Summer Intern-Machine Learning Operations (MLOps) - Data Platform
Santa Clara, USA IT development
Job description
The Position
2024 Summer Intern - MLOps Engineer Data Enrichment
Department Summary
You will join a team of 10+ engineers as a Machine Learning Operations (MLOps) Intern in crafting AI based solutions to solve complex healthcare problems in the world of diagnostics today. There are thousands of data points generated in systems that are not only inaccessible but were never designed to be consumed by AI application. You will help create an enterprise-scale ML pipeline, harnessing capabilities of AI to uncover breakthrough insights, devise innovative algorithms and create ML models that will support clinicians to better serve patients. This internship is ideal for someone with a strong interest in both machine learning and software engineering.
This internship position is located inSanta Clara, CA on-site.
Key Responsibilities
Software Development: This is hands-on. You're writing high-quality code for software that will perform at scale, be supportable, and be extensible, kind of role.
Machine Learning: Deploy and evaluate model’s accuracy, performance, and reliability. Build MLOps pipeline for model training, testing and deployment. Support the documentation of MLOps processes and best practices
Leadership: Ensuring we amplify our culture. Embody our value for technical excellence, integrity and support, and compassion for individuals
Program Highlights
Intensive 12-weeks, full time (40 hours per week) paid internship.
Program start dates are in June (Summer)
A stipend, based on location, will be provided to help alleviate costs associated with the internship.
Ownership of challenging and impactful business-critical projects.
Work with some of the most talented people in the biotechnology industry.
Be part of the enthusiastic engineering team
What you will learn:
Hands-on experience in the dynamic field of machine learning operation
Collaborate with data scientists and software engineers to deploy machine learning models into production environments.
Implementation of monitoring and alerting systems to ensure model performance and reliability.
Learn new tools and technologies in the MLOps ecosystem
Experience working on various AWS offerings like S3, SQS, IAM, cloud-formation, and more
Learn about FHIR and other healthcare standards
Who You Are (Required)
Currently enrolled in BS or MS Computer Science, Data Science, or in a related area.
Strong programming skills, preferably in languages such as Python, Java, or similar.
Familiarity with machine learning concepts and frameworks (e.g., TensorFlow, PyTorch).
Basic understanding of software development practices and version control systems (e.g., Git).
Eagerness to learn and adapt to new technologies in the MLOps domain.
Excellent communication and collaboration skills.
Preferred Qualifications
Previous experience with containerization technologies (e.g., Docker, Kubernetes).
Knowledge of continuous integration/continuous deployment (CI/CD) practices.
Exposure to cloud platforms such as AWS, Azure, or Google Cloud.
Familiarity with tools for model monitoring and performance tracking.
Relocation benefits are not available for this job posting.
The expected salary range for this position based on the primary location for this position in California is $21.00 - $50.00 per hour. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. This position also qualifies for paid holiday time off benefits.
#Roche-Commercial-Interns-2024
Who we are
At Roche, more than 100,000 people across 100 countries are pushing back the frontiers of healthcare. Working together, we’ve become one of the world’s leading research-focused healthcare groups. Our success is built on innovation, curiosity and diversity.
Roche is an equal opportunity employer and strictly prohibits unlawful discrimination based upon an individual’s race, color, religion, gender, sexual orientation, gender identity/expression, national origin/ancestry, age, mental/physical disability, medical condition, marital status, veteran status, or any other characteristic protected by law.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.