LLM Applied Scientist Intern (Summer 2024)

About Us:

Genies is a pioneering technology company that enables developers and creatives to craft their own engaging, interconnected gamified experiences. With substantial backing of $250 million from respected investors like Silver Lake, BOND, and NEA, as well as prominent industry figures including Bob Iger, Genies has emerged as a leader in avatar technology. Initially embraced by numerous Hollywood stars like Justin Bieber and Rihanna in collaboration with major music groups, Genies has expanded to offer avatars to a wider audience through its Developer Kit and artist-driven platform, The Workshop. These diverse experiences merge to create the lively avatar community known as Genies Party.

Position Overview:

Genies seeks an enthusiastic Applied Scientist Intern to join our team in San Mateo, California, during the upcoming summer. Collaborating closely with our skilled team of Engineers and Researchers, you will delve into the convergence of LLM, data, and gaming. Your primary responsibilities will involve contributing to the development of a cutting-edge system driven by advanced LLM technology to enhance the interaction between designers and players. We are searching for an individual passionate about crafting top-tier visuals and possesses the technical acumen required to shape the future of game design and gameplay experiences.

Key Responsibilities:

• Conduct research and devise LLM-based solutions and pipelines to revolutionize game development methodologies through data analysis and strategic insights.
• Design evaluations and execute controlled experiments plus observational analyses to measure the effectiveness of systems.
• Dive into machine learning literature, particularly in natural language processing, to experiment with novel techniques gleaned from research papers and texts.
• Explore the potential for productizing solutions, identifying challenges and openings that could lead to immediate deployment or inspire future research ventures.
• Showcase your accomplishments and impact to the team and wider company through effective presentations.

Minimum Qualifications:

• Currently pursuing or recently graduated from a PhD or Master's degree program in Computer Science, Artificial Intelligence, Machine Learning, or related disciplines.
• Profound grasp of machine learning principles and the latest advancements in natural language processing methods.
• Proficiency in Python and experience with machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn, Hugging Face).
• Ability to conduct research and prototype solutions based on academic literature.
• Strong problem-solving abilities and adeptness in both independent and collaborative work.
• Exceptional communication skills to articulate findings clearly and compellingly.

Preferred Qualifications:

• Enrolled in a PhD program in Computer Science, Artificial Intelligence, Machine Learning, or allied fields.
• Proven experience in developing LLM-based solutions and pipelines.
• In-depth knowledge and hands-on involvement with cutting-edge natural language processing techniques.
• Record of published research or participation in academic forums.
• Demonstrated coding proficiency and hands-on experience with LLMs, along with familiarity with popular prompt methods like chain-of-thought and graph-of-thought.
• Previous exposure to using SQL or similar query languages for data analysis and statistics in Python.

What We Offer:

• Collaborative learning environment with ample opportunities for professional growth.
• Autonomy in steering your career path by making innovative contributions to a dynamic team and product, along with flexible working hours and a hybrid office-home policy.
• Startup culture and perks combined with solid financial backing.

Compensation:

$35 to $50 per hour commensurate with qualifications.

Genies is an equal opportunity employer striving to foster an inclusive, discrimination-free work environment. We embrace diversity, inclusion, and endeavor to build a sense of belonging for all team members.