Applied Machine Learning Scientist, Vice President

What you'll do

• Lead the development and deployment of production-grade ML systems for NLP, speech recognition, and recommendation systems.
• Design and build agentic AI systems featuring multi-agent orchestration, tool calling, and safety guardrails.
• Fine-tune and adapt LLMs and SLMs using PEFT, distillation, and quantization to optimize for latency and cost.
• Apply reinforcement learning techniques to improve personalization, dialog policies, and sequential decision-making.
• Implement privacy, safety, and security controls for GenAI systems, including jailbreak resistance and auditability.
• Analyze and evaluate the ongoing performance of developed ML systems using rigorous experimental design and metrics.
• Translate ambiguous business problems into measurable goals and production-ready machine learning solutions.

What we're looking for

• MS with 7+ years or PhD with 4+ years of hands-on industry experience building and deploying production ML systems.
• Proficiency in Python and common ML libraries including PyTorch, TensorFlow, and Hugging Face to write production-quality code.
• Expertise in deep learning, transformer architectures, and statistical modeling including model evaluation and error analysis.
• Experience fine-tuning and deploying LLMs and SLMs using techniques like PEFT, distillation, and quantization.
• Solid understanding of Information Retrieval concepts or recommendation systems.
• Ability to design experiments, establish baselines, and choose meaningful metrics to evaluate model performance.
• 5 years of hands-on experience with virtual assistant model development and optimization (preferred).
• Experience with MLOps/LLMOps, RL/bandits, and regulated finance domains (preferred).