Machine Learning Engineer Intern Jobs in Florida

THE OPPORTUNITY

As a machine learning engineer, you will have the opportunity to learn and apply RMS' methodologies to solve analytical problems critical to driving high-end business value to our clients. This position requires basic knowledge of Data Science methods and a strong, applied knowledge of Python and SQL. Experience deploying models in cloud-based environments is desired.

RIGHT TO WORK

Candidates must have the legal right to work in the country the position is based. The employer does not provide sponsorship for work authorization for this role.

WHO YOU'LL WORK WITH

You'll work with as part of our Research & Development team, reporting to the Senior Director of AI and Machine Learning. We take pride in encouraging each other's career ambitions and you'll find opportunities for personal development throughout our company. This is a hybrid position, working in the office 3 days a week.

WHAT YOU'LL DO

• Monitor model performance both pre- and post-deployment
• Develop pipelines to collect, transform, and aggregate data
• Work with CI/CD pipelines to create and deploy artifacts
• Refactor code to perform efficiently in scaled environments
• Creatively design solutions to analytical problems using quantitative and qualitative approaches to drive high-end business value
• Develop and maintain documentation articulating methodology and architecture, as well as data dictionaries
• Effectively and concisely articulate processes to internal parties

SKILLS AND QUALIFICATIONS

• Strong knowledge with Python, including experience building custom packages
• Experience with Scala or Spark will be considered an asset
• Some cloud-based experience; Azure preferred
• Ability to manage multiple projects independently
• Working knowledge of statistics, machine learning and deep-learning algorithms
• 2+ Years Experience
• Bachelor's degree in Mathematics, Statistics, Engineering, Computer Science, or a field with a quantitative and technical emphasis required

PREFERRED

• Graduate degree, or supplementary courses in Data Science, Data Engineering or Machine Learning

BENEFITS

as a full-time RMS Employee, you will be eligible for:

• 100% employer paid HSA medical insurance, or 80% employer paid medical insurance for HMO and PPO plans for employees and qualifying dependents
• Dental and vision insurance (80% employer paid)
• Basic Life and AD&D insurance (100% employer paid)
• Telemedicine (100% employer paid)
• 401k plan with company matching contribution of 4% of annual gross salary with immediate vesting
• Tuition assistance is available to support continuous education efforts
• 15 business days paid vacation for the first year based on your hire date (pro rata), 15 days thereafter; 20 days after two years, and 25 days after ten years
• Eight paid holidays + 1 personal floating holiday
• Paid parking and health club membership
• Paid parental leave

WHO WE ARE

Now more than ever, Revenue Management Solutions (RMS) is committed to supporting restaurants through these ever-changing times. Today, more than 50 major brands in over 40 countries trust RMS for data-driven analytics and tech-enabled solutions to optimize sales, menus and a brand's financial health. Six of the top 10 US fast food brands and 16 of the top 30 global restaurant brands (equaling more than 100,000 restaurants) rely on RMS' software solutions and actionable insights to make informed business decisions that drive profitability and combat inflation and increasing wages. The company holds five US patents on menu pricing and customer segmentation and supports ongoing academic research efforts. For more information on how RMS helps its clients, visit revenuemanage.com.

WHAT WE BELIEVE

Our goal at RMS is to create a positive change in the communities we inhabit. With over 20 countries represented throughout our offices, we respect and embrace different cultures, interests, and actions. The acknowledgment of our unique identities is something that connects us across continents to uphold our values of diversity, respect, and responsibility.