Machine Learning Engineer Intern Jobs in Orlando, FL

ONLY CONSIDERING CANDIDATES LIVING IN FLORIDA

MUST BE AUTHORIZED TO WORK IN THE US WITHOUT SPONSORSHIP. ONLY US CITIZENS AND PERMANENT RESIDENTS WILL BE CONSIDERED FOR THIS ROLE. NO B2B OR C2C.

As a key member of our team, you will own end‐to‐end modeling and deployment work — from conceptual framing of business problems to data ingestion, model development, and reliable production delivery.

Client drives innovative data‐driven insights and scalable AI solutions across the entertainment ecosystem. The Data Science team partners with data engineering, marketing, product, and executive teams to transform audience data into actionable strategies and operational products. A successful Applied Data Scientist at Client thrives on both analytical creativity and production rigor. Your work will directly shape how Client Solutions delivers value to clients and internal stakeholders.

You will need to travel to Orlando for your first day, and for occasional meetings and trainings.

For this role you will:

• Translate ambiguous business questions into structured analytical and ML solutions.
• Develop, validate, and optimize statistical and machine learning models that impact forecasting, segmentation, personalization, recommendation, or operational efficiency.
• Build production‐ready pipelines using robust MLOps practices (CI/CD, automated testing, monitoring).
• Document all models, pipelines, and deployment processes clearly and comprehensively to ensure maintainability, reproducibility, and knowledge sharing across the team.
• Deploy models into scalable production environments and maintain lifecycle operations.
• Communicate insights and technical decisions clearly to technical and non‐technical audiences.
• Stay ahead of emerging tools, techniques, and frameworks in machine learning/artificial intelligence (ML/AI) and influence best practices across the organization.

Qualifications

• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 5+ years of industry experience (in addition to internships) in data science and machine learning, including production deployments.
• 3+ years of building machine learning models for business applications (outside of academic experience.)
• Strong Python programming skills with hands-on experience building, training, deploying, and monitoring machine learning models.
• Solid experience with SQL (2+ years) for database querying, data preparation, and analysis.
• Experience designing, building, and maintaining end-to-end ML pipelines from data ingestion to production serving.
• Experience in both supervised and unsupervised learning algorithms.
• Familiarity with cloud platforms and deployment environments (e.g., AWS, Azure, GCP).
• Working knowledge of large-scale data warehousing platforms (e.g., Snowflake, SQL Server, Big Query, RedShift).
• Demonstrated ownership of model productization, monitoring, and iterative improvement.
• Proven ability to solve ambiguous problems using data and engineering rigor.
• Excellent cross-functional communication, capable of bridging business requirements and technical design.
• Outstanding analytical and problem-solving skills, able to diagnose and resolve complex system issues.
• Experience managing multiple projects simultaneously and prioritizing tasks effectively.
• You must be able to start in person onsite for this role
• You must be able to travel on occasion to support business needs

What Sets You Apart

• Advanced degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Familiarity with MLOps tooling (e.g., SageMaker, Lambda, Airflow, MLflow) and cloud platforms (AWS, GCP, Azure).
• Experience with generative AI (GenAI) techniques (e.g., LLM) or with GenAI related concepts (language modeling); Bedrock or Hugging Face experience is a plus.
• Hands-on experience designing, building, and deploying recommendation models, including collaborative filtering, content-based, and transformer-based recommendation architectures.
• Experience with data labeling, taxonomy design, and classification frameworks.
• Strong knowledge of statistical analysis, machine learning algorithms, and data visualization using Python packages.
• Ability to guide architectural and strategic decisions for ML infrastructure.
• Industry experience in entertainment or online commerce is a strong plus, including domains such as theme parks, hospitality, live performances, show or sports ticketing, or retail and marketplace platforms.

Additional information

Client offers outstanding benefit options that fit our employee's lifestyles including:

• Medical, Dental & Vision
• 401k Match
• Short Term Disability, Long Term Disability (Company Paid)
• Basic Life and AD&D (Company Paid)
• Additional Voluntary Benefits
• Flexible Work Arrangements
• 3 Weeks of PTO + 5 Personal Days
• Paid Holiday Break from Christmas to New Year
• Paid Holidays
• Fitness Benefit
• Annual Day of Giving
• Company Bonus Program
• Share in the FUN! Client gives $1000 per year in Tickets-At-Work gift cards to full-time employees to experience and enjoy our signature savings marketplace!

Travel & Lodging industry