Job Description

Responsibilities

• Drive applied research by conceptualizing, designing, implementing, and validating innovative algorithmic solutions
• Explore and apply state-of-the-art AI/ML techniques including LLM pretraining, fine-tuning, and robust offline experimentation
• Develop production-ready systems and scale machine learning solutions
• Work on personalization, recommendations, search, content understanding, messaging, targeting, new member acquisition, and evidence
• Collaborate within multi-disciplinary teams and communicate research results to stakeholders
• Set priorities and maintain strong execution focus in a dynamic, fast-paced environment
• Mentor or lead technical efforts and contribute to technical leadership when applicable

Requirements

• Ph.D or Masters in Computer Science or related fields
• 6+ years of research experience with a track record of delivering quality results
• Deep expertise in machine learning, including supervised and unsupervised learning
• Practical experience in LLM development, including pretraining, fine-tuning, and post-training techniques such as fine-tuning and distillation
• Strong software engineering skills; Required: Python, TensorFlow, PyTorch
• Nice to have: Java, Scala, Spark, Hive, Jax, Flink, Hadoop
• Excellent interpersonal, written, and verbal communication skills
• Preferred: Proven experience as a technical leader
• Skilled in collaborating with cross-functional teams
• Research publications in peer-reviewed journals and conferences on relevant topics (preferred)
• Hands-on experience in distributed training, reinforcement-learning-based training of LLMs, conversational agents, and personalization (preferred)
• Proficiency with cloud computing platforms and large web-scale distributed systems (preferred)
• Applied research experience in industrial settings (preferred)
• Contributions to open source (preferred)
• Experience in one or more: search, natural language processing, knowledge graphs, conversational agents, personalization, reinforcement learning

Benefits

• Health Plans
• Mental Health support
• 401(k) Retirement Plan with employer match
• Stock Option Program
• Disability Programs
• Health Savings and Flexible Spending Accounts
• Family-forming benefits
• Life and Serious Injury Benefits
• Paid leave of absence programs
• Paid time off: Full-time hourly employees accrue 35 days annually; Full-time salaried employees have flexible time off
• Ability to choose compensation mix between salary and stock options