About This Role

Simular is seeking a talented PhD Research Intern to join our research team and contribute to cutting-edge advances in AI systems. This is an exceptional opportunity for PhD candidates to conduct meaningful research at the intersection of reinforcement learning, multimodal AI, and computer use automation—bridging fundamental research with real-world applications.

This remote position offers direct collaboration with research scientists on technically challenging problems that will shape the future of AI agents capable of understanding and executing complex tasks across diverse domains.

Key Responsibilities

Research Collaboration: Partner with research scientists to advance methods across multiple AI domains, including planning and reinforcement learning, multimodal perception, and reward modeling
Planning & Reinforcement Learning for Computer Use: Explore techniques such as behavioral cloning, reinforcement learning on model weights, and RAG-based domain knowledge integration for autonomous agent systems
Multimodal Grounding Research: Investigate vision-only models, tree search algorithms, and hybrid approaches that combine large language models with visual understanding capabilities
Reward & Judge Modeling: Conduct error analysis, facilitate human evaluation studies, and develop machine learning models for evaluating agent performance and decision-making
User Intent Understanding: Build systems to model vague and ambiguous user queries, implement preference learning mechanisms, and improve human-AI alignment
Dataset Development & Experimentation: Contribute to creating high-quality datasets, executing rigorous experiments, and benchmarking results against established baselines
Technical Innovation: Explore novel research approaches that help derisk Simular's long-term technical roadmap and advance the state of the art
Documentation & Communication: Prepare comprehensive internal reports, academic-style papers, and presentations to communicate research findings to both technical and non-technical stakeholders

Ideal Candidate Profile

You are an excellent fit for this role if you meet the following criteria:

Academic Background: Currently pursuing a PhD in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field
Research Expertise: Demonstrated research background in at least one of the following areas: reinforcement learning, large language models (LLMs), vision-language models (VLMs), computer vision, multimodal perception, or representation learning
Publication Record: Experience conducting rigorous experiments and publishing or preparing papers for top-tier academic conferences such as NeurIPS, ICLR, ICML, CVPR, ACL, or equivalent venues
Programming Proficiency: Strong coding and prototyping abilities in Python with hands-on experience in modern deep learning frameworks such as PyTorch or JAX
Research Mindset: Intellectual curiosity, self-motivation, and the initiative to identify important research problems independently
Applied Research Interest: Genuine passion for bridging fundamental machine learning research with practical, deployed AI systems that create measurable impact

Why Join Simular?

This internship provides a unique opportunity to work on high-impact AI research problems with a talented team of researchers and engineers. You'll gain experience conducting cutting-edge research, develop your technical skills across multiple AI domains, and contribute to advancing the capabilities of intelligent AI systems. The fully remote nature of the position offers flexibility while maintaining close collaboration with your research team.

If you're a PhD candidate passionate about advancing AI capabilities and eager to see your research applied in real-world contexts, we'd love to hear from you.

💰 Compensation not publicly listed. Market estimate for similar roles: from $80K, varying by experience and location.

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