Machine Learning Systems Research Intern at Red Hat working on AI inference and model optimization techniques. Collaborating with experts in the field while gaining hands - on experience in applied ML research.
About the role
- AI Engineer at PayPal designing, building, and deploying autonomous AI systems powered by LLMs. Collaborating across teams on AI engineering, distributed systems, and product development.
Responsibilities
- Assist in the development and optimization of machine learning models.
- Preprocess and analyze datasets to ensure data quality.
- Collaborate with senior engineers and data scientists on model deployment.
- Conduct experiments and run machine learning tests.
- Stay updated with the latest advancements in machine learning.
- Design and develop agentic AI systems that can plan, reason, retrieve knowledge, and interact with external tools and APIs.
- Build and optimize LLM-powered applications using frameworks such as LangChain, LlamaIndex, Semantic Kernel, or similar.
- Implement advanced capabilities such as Retrieval-Augmented Generation (RAG), multi-agent orchestration, memory management, tool calling and function execution, prompt engineering and structured output generation.
- Develop scalable backend services (REST/gRPC APIs) to support AI-driven workflows.
- Integrate vector databases and knowledge stores.
- Establish evaluation pipelines for agent performance, reliability, hallucination mitigation, and safety.
- Optimize model performance, latency, and cost in production environments.
- Collaborate with product managers, data scientists, and frontend teams to deliver AI-powered features.
- Stay up to date with advancements in autonomous agents, reasoning models, and AI infrastructure.
Requirements
- 1+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience
- Familiarity with ML frameworks like TensorFlow or scikit-learn
- Strong analytical and problem-solving skills
- 1–3 years of experience in software engineering, ML engineering, or AI application development
- Strong proficiency in Python (mandatory)
- Hands-on experience with LLM APIs (e.g., OpenAI, Anthropic, open-source LLMs)
- Experience building AI agents using frameworks like LangChain, LlamaIndex, CrewAI, AutoGen, or similar.
- Understanding of prompt engineering techniques, RAG architectures, vector embeddings and similarity search, model evaluation metrics for generative AI
- Experience with REST APIs and backend frameworks (FastAPI, Flask, Django, etc.)
- Familiarity with cloud platforms (AWS/GCP/Azure) and containerization (Docker, Kubernetes)
- Knowledge of Git, CI/CD, and production deployment best practices.
Benefits
- generous paid time off
- healthcare coverage for you and your family
- resources to create financial security and support your mental health
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
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