Machine Learning Engineer 🎓

Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you’ll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what’s possible and powering the future.

We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We’re dedicated to empowering people to be their true selves. Together, we’re building a better tomorrow for our employees, customers, partners, and communities.

What You’ll Learn

• Project Overview: This project focuses on developing innovative LLM models and building robust, modular agent pipelines that combine planning, retrieval-augmented reasoning (hybrid RAG), tool-use orchestration, and multi-agent collaboration.

• Skills You’ll Learn:

• Deep understanding of agentic AI framework

• Hands-on algorithm and system development

• Collaborative develop skills

What You’ll Do

Samsung DSA has launched a new AI initiative to build the foundational capabilities for practical, agentic AI systems. The AI Innovation team is the driving force behind this vision, leading innovation at the intersection of machine learning and system engineering to develop and operate our next-generation Agentic AI framework. We aim to enable LLMs to autonomously plan, retrieve information, coordinate with tools, and execute multi-step workflows across our internal knowledge ecosystem. We are actively seeking talented Machine Learning Engineers specializing in building next-generation AI/ML solutions.

Location: Daily onsite presence at our San Jose headquarters in alignment with our Flexible Work policy

**Reports to:**Director, AI/ML Software Engineering

The intern will contribute to design, prototype, and evaluate new agentic mechanisms—such as self-reflection loops, verifiers, memory modules, and multi-agent task decomposition—that strengthen both short- and long-horizon reasoning. Potential topics include, but not limited to:

• Model Development: Development of customized VLM models tailored to specific agent requirements.

• Agentic AI Workflow Prototype (MVP): A functioning agent pipeline capable of task planning, tool-use, and hybrid RAG-based reasoning.

• Integration with Internal Tools & Services: Extensions demonstrating agent interaction with microservices, search/retrieval systems, or multi-agent components.

• Benchmarking & Evaluation Suite: A compact set of metrics and experiments evaluating task completion, retrieval accuracy, and reasoning robustness.

• Technical Report & Recommendations: A concise write-up summarizing findings, design insights, and proposed next steps for production deployment.

• Complete other responsibilities as assigned.

What You Bring

• Pursuing Ph.D. in Computer Science, Computer Engineering, Machine Learning, Artificial Intelligence, or a closely related field

• Must have at least 1 academic quarter/semester remaining

• Strong Python programming skills

• Familiarity with machine learning frameworks (e.g., PyTorch)

• Ability to translate research ideas into working prototypes

• Experience in one or more of the following is a bonus: LLM/VLM related publications in top-tier conferences (ICML, NeurIPS, ICLR, CVPR, etc.)

• You’re inclusive, adapting your style to the situation and diverse global norms of our people.

• An avid learner, you approach challenges with curiosity and resilience, seeking data to help build understanding.

• You’re collaborative, building relationships, humbly offering support and openly welcoming approaches.

• Innovative and creative, you proactively explore new ideas and adapt quickly to change.