AI Researcher

This is a fully remote position, open to applicants in Argentina.

📋 Description

• Conduct advanced research on agentic AI systems utilizing real-world interaction signals and multimodal data.

• Design and implement experimental learning paradigms for large-scale models, incorporating RAG, supervised fine-tuning, RLHF, DPO, and GRPO-style techniques.

• Develop approaches for multimodal representation learning, including the creation of joint embedding spaces across text, audio, logs, and structured interaction data.

• Enhance capabilities in speech and audio intelligence, focusing on STT, ASR, and audio-driven learning signals.

• Investigate methods to improve agent reasoning, planning, tool usage, and adaptability in real-world settings.

• Establish how complex behavioral and interaction signals can be effectively transformed into training objectives for large-scale models.

• Create and optimize evaluation methodologies to assess agent performance in specific real-world contexts.

• Collaborate with engineering and product teams to translate research concepts into production systems.

• Recognize patterns in real-world workflows and develop generalizable modeling and representation strategies.

• Contribute to the strategic research direction of Toptal’s agentic AI systems and their multimodal capabilities.

• Remain updated on academic and industry research and incorporate relevant advancements into internal systems.

⛳️ Requirements

• PhD in Computer Science, Machine Learning, AI, Electrical Engineering, or a related discipline.

• Over 5 years of experience in applied AI research or ML systems with tangible production impact.

• Strong expertise in large-scale machine learning, LLMs, or multimodal AI systems.

• Practical experience with RAG systems.

• Proficient in fine-tuning large language models.

• Familiarity with reinforcement learning methods including RLHF, DPO, or GRPO-style techniques.

• Experience with VLM.

• In-depth understanding of representation learning, embeddings, and joint embedding spaces.

• Background in speech and audio modeling, including STT, ASR, or audio signal processing.

• Proficiency in Python and contemporary ML frameworks (such as PyTorch and the Hugging Face ecosystem).

• Experience in designing or enhancing evaluation methodologies for LLMs or agentic systems.

• Knowledge of agentic AI systems, particularly in reasoning, planning, or tool-use architectures.

• Background in multimodal AI systems encompassing text, audio, vision, or structured logs.

• Experience embedding AI into practical products (such as browsers, IDEs, or enterprise tools).

• Familiarity with real-time or streaming AI systems.

• Contributions to open-source projects or publications in leading ML/AI conferences.

• Strong aptitude for formulating research hypotheses from unclear, real-world challenges.

• Excellent written and verbal communication skills in English.

🏝️ Benefits

• Health insurance

• 401(k) matching

• Flexible work hours

• Paid time off

• Remote work options