Thermo Fisher is looking for a Software Engineering Intern skilled in machine learning and Java/Spring development to develop and prototype features using LLMs, RAG pipelines, AWS-hosted data lakes, model deployment, inference, and monitoring.
Requirements
- Hands-on experience with machine learning, LLMs, transformers, and agent frameworks (LangChain, Haystack, or similar)
- Experience building RAG pipelines using vector search (e.g., FAISS, Weaviate) and AWS data lakes
- Strong skills in Java, Spring Framework, and REST API development
- Experience with AngularJS or modern JavaScript frameworks
- Familiarity with PostgreSQL, Tomcat, Apache or Nginx
- Working knowledge of automation testing frameworks (JUnit, Selenium, etc.)
- Familiarity with GitHub Actions, continuous integration/continuous deployment pipelines, and containerized deployments
Responsibilities
- Develop and prototype features using LLMs, RAG pipelines, AWS-hosted data lakes, model deployment, inference, and monitoring
- Develop or fine-tune agents capable of handling scientific workflows and knowledge retrieval
- Participate in full-stack software development involving Java, Spring Framework, Spring Boot, AngularJS, Electron, PostgreSQL, and Tomcat
- Integrate and test services with AWS components (e.g., S3, DynamoDB, Lambda, Bedrock/SageMaker, Redshift, etc.)
- Establish CI/CD pipelines with the use of GitHub Actions, self-hosted runners, and deployment automation
- Implement automated test cases (unit, integration, and regression)
- Work together with senior engineers and the SCM team to incorporate security tools like CodeQL, SonarQube, Qualys, GitHub X-ray, and SBOM generation tools.
Other
- Currently pursuing a Master’s or Ph.D. in Computer Science, Data Science, Machine Learning, or a related technical field
- Familiarity with cybersecurity tools like CodeQL, SonarQube, SBOM generation, GitHub security features, and Qualys scanning tools
- Experience deploying LLMs on cloud platforms (AWS Bedrock, SageMaker, or Azure OpenAI)
- Understanding secure software development and vulnerability management protocols
- Familiarity with scientific or laboratory workflows is a plus
