GenAI ML Researcher

Description

ActiveFence is seeking a motivated and detail-oriented professional to play a key role in shaping the future of technology as a Generative ML Researcher. This is your chance to contribute to cutting-edge developments in machine learning and help improve the safety and integrity of generative AI systems used around the world.

In this role, you will manage complex datasets with precision and investigate emerging trends that may impact the safety and reliability of foundation models. You’ll collaborate closely with cross-functional teams—engineering, product, and policy—to identify and solve high-stakes problems in a rapidly evolving landscape. You’ll also help foster a culture of research-driven innovation and continuous knowledge sharing to strengthen our collective understanding of generative AI systems.

Requirements

Must-Have Qualifications:

• Machine Learning Expertise: Solid understanding of ML concepts and algorithms.
• Strong Research Capability: Skilled in developing novel ideas, designing and executing experiments, and critically analyzing results.
• Proficiency in Python: Strong experience using Python for data science and machine learning, including hands-on familiarity with libraries such as Pandas, NumPy, and scikit-learn. Capable of working with complex codebases and quick to learn new tools, libraries, and paradigms as needed.
• Experience with Generative Models: Practical experience working with LLMs, image generation models, or multi-modal systems.
• Strong English Skills: Able to clearly communicate ideas in both written and spoken English, including technical topics.

Preferred Qualifications:

• Research Background – Experience in research-focused roles or advanced academic work (e.g., Master’s or PhD in a relevant field) 
• Engineering Skills – Experience with data handling, cloud platforms, integrating multiple APIs, and building robust, error-tolerant systems.
• Experience in Fine-Tuning LLMs – Hands-on experience customizing large language models for specific tasks or domains using techniques like supervised fine-tuning or reinforcement learning.
• Familiarity with Content Moderation – Understanding of online safety challenges, harmful content detection, and moderation systems.

About ActiveFence