Description

You will design, build, and operate production-grade ML and Generative AI services while setting technical direction across multiple workstreams.

This role is remote.

Responsibilities

• Design and deploy ML/LLM/GenAI solutions from concept through production, owning reliability and operability.
• Build MLOps capabilities including automated pipelines for deployment, monitoring, and model lifecycle management.
• Fine-tune generative models for NLP use cases like summarization and text generation, optimizing for quality and performance.
• Mentor junior engineers through design/code reviews and pairing to raise engineering standards.
• Communicate technical outcomes and model performance to technical and non-technical stakeholders.

Required Skills

• 10+ years of engineering experience, with 3-5+ years in production AI/ML systems.
• Proficiency in Python for model development and integration with OpenAI API.
• Experience with TensorFlow, PyTorch, and Scikit-learn.
• Hands-on experience with cloud platforms: AWS, Azure, or Google Cloud Platform.
• Containerization and orchestration using Docker and Kubernetes.
• Solid understanding of statistics, ML fundamentals (classification, regression, deep learning), and generative architectures (GANs, VAEs).
• Ability to evaluate models (e.g., GPT-4.1), implement monitoring, and iterate on architectures.

Preferred Skills

• Familiarity with the financial services industry.
• Expertise in designing RAG pipelines.

Key Skills

Education

Any Graduate