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 Youll 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

Qualifications :

What Were Looking For

Required Qualifications

• Currently pursuing a Bachelors or Masters 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

Additional Information :

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:
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.

Remote Work :

Yes

Employment Type :

Intern