Applied Machine Learning Scientist - Vice President

What you'll do

• Develop and deploy ML systems across NLP, speech recognition, recommendation, and information retrieval; build agentic AI for multi-step workflows.
• Fine-tune and optimize LLMs and SLMs, and use reinforcement learning approaches to improve personalization and sequential decision-making.
• Evaluate and operate models in production, collaborate with partner teams, and implement privacy, safety, and security controls for GenAI systems.

What they ask for

• MS with 7+ years, or PhD with 4+ years, of hands-on industry experience building and deploying production ML systems.
• Applied GenAI experience with LLMs, including fine-tuning and deploying SLMs; familiarity with prompt design, grounded generation, and RAG.
• Strong foundations in machine learning, deep learning, statistical modeling, and model evaluation; understanding of NLP and information retrieval and/or recommendation systems.
• Proficiency in Python and common ML libraries, including PyTorch/TensorFlow, Hugging Face, and scikit-learn; ability to write production-quality code.

Nice to have

• 5 years of hands-on experience with virtual assistant model development and optimization.
• Experience with multi-agent systems, agent governance and evaluation, reinforcement learning or bandits, regulated finance, MLOps/LLMOps, or A/B experimentation.

Pay

USD $171,000.00-$260,000.00 base salary

Tools

Python, PyTorch/TensorFlow, Hugging Face, scikit-learn, LLMs, SLMs, RAG, LoRA

AI focus

Production ML and GenAI, including LLM-powered RAG and agentic systems, model fine-tuning and evaluation, reinforcement learning, and privacy, safety, and security controls.