AI Research Lead
1 week ago
Responsibilities
Research Leadership & Strategy
- Define and execute the macro research direction across multiple modalities, including post-training LLMs for agent trajectories and future mid-training initiatives
- Lead strategic research planning and roadmap development to advance Sonar model capabilities
- Drive innovation in supervised and reinforcement learning techniques for query answering
- Collaborate with leadership to align research priorities with product and business objectives
- Coach and mentor a team of AI research scientists and engineers, fostering their technical and professional growth
- Establish the long-term macro research direction across the team, including our direction across different modalities
- Lead hiring and onboarding of new research talent
- Create a collaborative environment that encourages knowledge sharing and innovation
- Post-train SOTA LLMs on query answering using cutting-edge supervised and reinforcement learning techniques
- Own and optimize the full stack data, training, and evaluation pipelines required for LLM post-training
- Deliver Sonar models that provide SOTA query answering performance
- Drive research into agent trajectories and multi-modal capabilities
- Lead the technical roadmap for eventual mid-training investments
- Work closely with engineering teams to integrate Sonar models into our product
- Partner with product teams to understand user needs and translate them into research priorities
- Collaborate with data teams to leverage our unique query/answer dataset effectively
- Communicate research progress and findings to stakeholders across the organization
Required
- Minimum of 5 years of experience working on relevant AI/ML projects with 3**+ years in a technical leadership role**
- Proven track record of leading and mentoring technical and research teams
- A Computer Science graduate degree at a premier academic intitution
- Deep expertise with large-scale LLMs and Deep Learning systems
- Strong programming skills with versatility across multiple languages and frameworks
- Demonstrated ability to set technical vision and drive execution
- Experience with pre-training and post-training techniques (self-supervised learning along with SFT/DPO/GRPO/PPO)
- Self-starter with exceptional ownership mentality and ability to work in ambiguous environments
- Passion for solving challenging problems and pushing the boundaries of AI research
- PhD in Machine Learning, Computer Science, or related areas
- Experience with agent-based AI systems and multi-modal model development
- Background in mid-training or pre-training of large language models
- Publications in top-tier AI/ML conferences
- Experience in fast-paced startup environments
- Track record of translating research into production systems
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