Description

You will design, build, and operate production-grade ML and Generative AI services, setting technical direction for scalable solutions.

This role is remote.

Responsibilities

• Design, develop, and deploy ML/LLM/GenAI solutions from concept through production, owning reliability and operability.
• Build and institutionalize MLOps capabilities, including automated pipelines for deployment, monitoring, and model lifecycle management.
• Fine-tune generative models for specific NLP use cases, implementing optimizations for summarization and text generation.
• Evaluate and iterate on model architectures (e.g., GPT-4.1) to enhance performance in NLP applications.
• Mentor junior engineers through design reviews, code reviews, and coaching to raise engineering quality.

Required Skills

• 10+ years of engineering experience, including 3-5+ years building and operating applied AI/ML systems in production.
• Proficiency in Python for model development, experimentation, and integration with OpenAI API.
• Experience with TensorFlow, PyTorch, and Scikit-learn.
• Experience with cloud platforms (AWS, Azure, or GCP), Docker, and Kubernetes.
• Strong understanding of statistics, machine learning fundamentals, and generative model architectures (GANs, VAEs).
• Ability to implement monitoring mechanisms for real-time model performance tracking.
• Experience with RAG (Retrieval-Augmented Generation) pipelines.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

Preferred Skills

• Familiarity with the financial services industry.
• Proven portfolio of successful generative model applications in NLP projects.

Key Skills

Education

Any Graduate