Senior ML Engineer: NLP & LLMs for Production (Remote)

Canoe Intelligence; New York (NY); Hybrid; USD 180,000 - 220,000; Full time

Benefits offered by this job

Medical, dental, vision benefits

Flexible PTO

401(k)

Home office stipend

Education assistance

Parental Leave

Job summary

Canoe Intelligence is seeking a Senior Machine Learning Engineer to design and deploy advanced models that enhance the analysis of unstructured financial documents. The role involves collaboration with engineering teams to build scalable systems, while utilizing expertise in machine learning and AI.

With a competitive salary range of $180,000 to $220,000, applicants should have significant experience in applied ML engineering. The position offers flexible hybrid work arrangements between New York and London.

Qualifications

• Minimum of 5 years of experience in applied ML engineering, focus on NLP or LLMs.
• Proficiency with AI‑assisted development tools (e.g., GitHub Copilot).
• Experience training and deploying large language models.

Responsibilities

• Design, train, and evaluate ML models for document classification and information retrieval.
• Fine-tune and optimize large language models for specific use cases.
• Collaborate with teams to integrate machine learning models into solutions.

Skills

Proficiency in Python

Experience in applied ML engineering focused on NLP

Strong understanding of MLOps

Excellent communication skills

Problem solving with a product mindset

Education

Bachelor's degree in computer science or related field

Tools

TensorFlow

PyTorch

Docker

Kubernetes

Job description

Canoe Intelligence is seeking a Senior Machine Learning Engineer to design and deploy advanced models that enhance the analysis of unstructured financial documents. The role involves collaboration with engineering teams to build scalable systems, while utilizing expertise in machine learning and AI.

With a competitive salary range of $180,000 to $220,000, applicants should have significant experience in applied ML engineering. The position offers flexible hybrid work arrangements between New York and London.