- This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents
- The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation
- You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions
Benefits
- Health & Wellbeing: Our holistic approach to supporting Scaliens includes comprehensive health coverage, dental and vision insurance, mental healthcare services, and more. PTO policies and accommodating schedules ensure you’ll get time off when you need it to relax and recharge. Note that our offerings may vary by region as we strive to respond to the unique needs of Scaliens around the globe.
- Personal & Career Growth: Continuously learn and grow through annual learning & development stipend, attending leadership breakfasts, manager training, speaker series, and joining an ERG.
- Building Scale Community: We welcome guests to our offices, and you can expect to see Scalien families and friends around. Join local happy hours, and accept invites to game nights, book clubs, and many other employee-led community events.
- Parental Support: Balancing work and family is essential, and Scale understands the importance of having adequate leave policies in place to promote a healthy home and work life.
This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluationPractical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow. You should also be adept at interpreting research literature and quickly turning new ideas into prototypesAt least three years of experience addressing sophisticated ML problems, either in a research setting or product developmentA track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.)Strong written and verbal communication skills and the ability to operate cross-functionallyHands-on experience and publications in building evaluations and benchmarks related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agentsHands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/JaxHands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etcFamiliarity with agentic reasoning methods such as STaR and PLANSEARCHExperience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.
#J-18808-Ljbffr…