AIML Engineer Intern

Make an Impact with AI/ML Engineering

Bring your curiosity engineering skills and bold ideas to Evernorth Health Services a division of The Cigna Group. This internship is a foundational development opportunity for emerging AI/ML engineers ready to build scalable solutions for meaningful health care challenges. You will contribute to strategically important work learn alongside ambitious and compassionate experts and explore how modern AI data cloud and software engineering can improve health outcomes and business decisions.

This is more than a summer project. Solutions developed by our teams have evolved into enterprise capabilities supporting critical business functions and several projects have contributed to innovative intellectual property and patent filings. You will gain exposure to the full AI lifecycle while building relationships through professional development networking and collaboration with experienced engineers data scientists architects and business stakeholders.

Responsibilities

• Build and improve reusable machine learning frameworks that accelerate model development and production deployment.
• Design scalable data pipelines and feature-engineering solutions using Python SQL Spark Databricks or related technologies.
• Develop production-ready APIs cloud-native services and intelligent applications that make AI capabilities easier to use across the enterprise.
• Contribute to MLOps automation containerized deployment monitoring and reliable engineering practices that improve speed quality and repeatability.
• Work with large health care datasets including pharmacy and medical claims member information call transcripts surveys and web logs to identify actionable opportunities.
• Partner with technical and business stakeholders to translate complex needs into scalable responsible solutions and communicate outcomes clearly.
• Explore generative AI agentic AI retrieval-augmented generation document intelligence or real-time prediction while seeking feedback and documenting what you learn.

Past projects have included Spark and Databricks feature-engineering platforms; AI/ML experimentation frameworks; MLOps and deployment automation; agentic and generative AI applications; enterprise chatbots; retrieval-augmented generation and document intelligence platforms; and real-time prediction services.

Required Qualifications

• Pursuing a masters degree or PhD in computer science statistics applied mathematics engineering operations research bioinformatics information systems computational linguistics or another quantitative field.
• At least 1 year of hands-on machine learning data engineering analytics or software engineering experience gained through coursework research internships or professional projects.
• Working knowledge of Python and SQL with experience preparing data or building technical solutions.
• Experience developing or supporting machine learning data engineering or software engineering solutions through academic or applied projects.
• Ability to explain technical work clearly collaborate across disciplines and adapt based on feedback and new information.

Preferred Qualifications

• Experience with scikit-learn MLlib TensorFlow PyTorch AWS Apache Spark Databricks PySpark or Spark SQL.
• Experience developing APIs with FastAPI or Flask and using CI/CD tools such as Jenkins or GitHub Actions.
• Exposure to Docker Kubernetes Hive Scala HDFS or other distributed computing and containerization technologies.
• Previous software engineering experience and a 3.0 GPA or higher with strength in quantitative coursework.

Additional Information

Location: This internship follows a hybrid schedule with three days per week in the Austin TX; Morris Plains NJ; or St. Louis MO office.

Compensation: Hourly pay ranges from $35.00-$43.00 based on degree program and year of study.

Schedule: This is a full-time 12-week summer internship working 40 hours per week beginning in May 2027.

Work Authorization: Candidates must be authorized to work in the United States and not require current or future employment sponsorship.

If you will be working at home occasionally or permanently the internet connection must be obtained through a cable broadband or fiber optic internet service provider with speeds of at least 10Mbps download/5Mbps upload.

About The Cigna Group

Doing something meaningful starts with a simple decision a commitment to changing lives. At The Cigna Group were dedicated to improving the health and vitality of those we serve. Through our divisions Cigna Healthcare and Evernorth Health Services we are committed to enhancing the lives of our clients customers and patients. Join us in driving growth and improving lives.

Qualified applicants will be considered without regard to race color age disability sex childbirth (including pregnancy) or related medical conditions including but not limited to lactation sexual orientation gender identity or expression veteran or military status religion national origin ancestry marital or familial status genetic information status with regard to public assistance citizenship status or any other characteristic protected by applicable equal employment opportunity laws.

If you need a reasonable accommodation to complete the online application process please email for assistance. Please note that this email inbox is dedicated to accommodation requests only and cannot provide application updates or accept resumes.

The Cigna Group has a tobacco-free policy and reserves the right not to hire tobacco/nicotine users in states where that is legally permissible. Candidates in such states who use tobacco/nicotine will not be considered for employment unless they enter a qualifying smoking cessation program prior to the start of their employment. These states include: Alabama Alaska Arizona Arkansas Delaware Florida Georgia Hawaii Idaho Iowa Kansas Maryland Massachusetts Michigan Nebraska Ohio Pennsylvania Texas Utah Vermont and Washington State.

Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal state and local ordinances.