Applied ML and Generative AI Lead Vice President

What you'll do

• Design, develop, and deploy production-grade ML, LLM, and Generative AI solutions from concept through deployment.
• Establish technical direction, architecture decisions, and engineering standards for scalable machine learning workstreams.
• Build and institutionalize MLOps capabilities including automated pipelines for deployment, monitoring, and model lifecycle management.
• Fine-tune generative models and implement optimization strategies for specific NLP use cases like summarization and text generation.
• Conduct thorough evaluations of generative models and iterate on architectures to improve performance in NLP applications.
• Implement real-time monitoring mechanisms to ensure the reliability and performance of deployed models.
• Communicate complex AI/ML capabilities and results effectively to both technical and non-technical stakeholders.
• Mentor junior engineers through design reviews, code reviews, and coaching to improve team delivery discipline.

What we're looking for

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 7+ years of experience in applied AI/ML engineering with a track record of deploying business-critical models in production.
• Experience in hands-on engineering leadership including setting technical direction, making architecture decisions, and mentoring junior engineers.
• Proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, and the OpenAI API.
• Experience with cloud platforms (AWS, Azure, or GCP), containerization (Docker, Kubernetes), and microservices design.
• Solid understanding of statistics, machine learning fundamentals, and generative model architectures like GANs and VAEs.
• Ability to fine-tune models for NLP applications and a portfolio showcasing successful generative model applications in NLP projects.
• Familiarity with financial services, RAG pipelines, and advanced prompting strategies (preferred).