AI-ML Intern

About the Role

We are seeking a curious and driven AI/ML Intern to join our team and contribute to the development and deployment of cutting-edge machine learning systems, with a special focus on Generative AI. This internship offers hands-on experience at the intersection of machine learning, software engineering, and MLOps, including exposure to large language models (LLMs), fine-tuning techniques, and AI agentic systems.

What You'll Do

Core Responsibilities

• Assist in building and maintaining ML pipelines for training, evaluation, and deployment of generative models
• Support the deployment and monitoring of LLMs in production environments
• Help implement CI/CD workflows for model versioning and automated testing
• Contribute to infrastructure automation using tools like Docker, Kubernetes, and cloud platforms
• Document AI/ML processes, best practices, and technical solutions
• Participate in code reviews and learn industry-standard development practices

Learning Opportunities

• Work with state-of-the-art ML frameworks (PyTorch, Hugging Face Transformers)
• Gain experience with MLOps tools and workflows in AWS (including SageMaker)
• Learn techniques for training and fine-tuning LLMs
• Understand containerization and orchestration (Docker, Kubernetes)
• Develop skills in model monitoring, versioning, and governance
• Explore agentic systems and autonomous AI workflows
• Exposure to real-world production ML systems at scale

What We're Looking For

Required Qualifications

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field
• Strong programming skills in Python
• Basic understanding of machine learning concepts and workflows
• Familiarity with version control systems (Git)
• Knowledge of Linux/Unix command line
• Strong problem-solving skills and attention to detail
• Excellent communication and teamwork abilities
• Eagerness to learn and adapt to new technologies

Preferred Qualifications

• Experience with ML frameworks (PyTorch, TensorFlow, Hugging Face)
• Exposure to cloud platforms (AWS, GCP, Azure)
• Understanding of containerization (Docker) and orchestration (Kubernetes)
• Familiarity with CI/CD tools (GitLab CI, GitHub Actions)
• Understanding of monitoring and logging tools
• Basic knowledge of infrastructure as code (Terraform, CloudFormation)
• Coursework or projects in machine learning, deep learning, or data engineering

Bonus Skills

• Experience with LLM deployment and optimization
• Knowledge of model quantization, distillation, and optimization techniques
• Familiarity with feature stores and vector databases
• Understanding of data versioning and experiment tracking
• Exposure to agentic systems and autonomous AI agents, such as LangGraph

What We Offer:

• A culture that celebrates diversity & inclusion, promotes professional
development, and strives for a work-life balance that supports the team
members. Offers flexible work options to support your work and personal needs.
• Full Benefit Package (Medical, Dental & Vision) that starts your first day.
• 401k plan with company match, Profit Sharing & Retirement Savings
Contribution.
• Paid Vacation, Paid Holidays, Maternity and Paternity Leave, Education
Assistance, Wellness Programs, Corporate Discounts, among other benefits.
Syngenta has been ranked as a top employer by Science Journal.
Learn more about our team and our mission here:
https://www.youtube.com/watch?v=OVCN_51GbNI
Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment,
hiring, training, promotion or any other employment practices for reasons of race, color,
religion, gender, national origin, age, sexual orientation, marital or veteran status,
disability, or any other legally protected status.