Machine Learning Operations Intern - Summer 2023

Are you looking for a hybrid or remote work opportunity? Are you interested in a workplace that allows for flexibility in your day? Are you ready for a workplace that provides benefits that suit your needs?
As the Machine Learning Operations intern you will join our Research team and collaborate cross-functionally to help build a research infrastructure for the AI Researchers.

As the MLOps Intern you will:

• Work with AI Researchers to build a research infrastructure to facilitate experimentation process.
• Implement various AI research tools, role-based access controls mechanism and secure data access mechanisms.
• Be involved in environmental security hardening.
• Identify, document, automate, and engineer processes for repeated tasks.
• Run machine learning tests and experiments.
• Collaborate with cross-functional teams

Qualifications

• Completion of 3 years of undergraduate studies in Computer Science or equivalent related fields.
• Demonstrated industry experience in internships and/or research projects
• Strong computer science fundamentals in algorithms, data structures and complexity analysis.
• Strong analytical and problem-solving skills
• Proficiency in at least one modern programming language like Python
• Proficiency in working with Linux based systems.
• Ability to consistently deliver elegant, modular and scalable solutions in a timely manner 

Bonus Qualifications

• Experience in cloud platforms like Azure, GCP, AWS, etc.
• Experience with machine learning platforms like Databricks, MLFlow, etc.

Relativity is a diverse workplace with different skills and life experiences—and we love and celebrate those differences. We believe that employees are happiest when they're empowered to be their full, authentic selves, regardless how you identify.
Benefit Highlights:Comprehensive health, dental, and vision plans Parental leave for primary and secondary caregivers Flexible work arrangements Two, week-long company breaks per yearUnlimited time off Long-term incentive program Training investment program
Transparency in Coverage InformationThe Transparency in Coverage Final Rule requires disclosure of the negotiated rates with in-network providers and the historic allowed amounts paid to out-of-network providers, for all health plans available to employers. Files containing this information for the plans covered are published on this page.Link: https://www.bcbsil.com/asomrf?EIN=123456789
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.