Senior ML Engineer - NLP/LLMs for Financial Data (Remote)

Canoe Intelligence; United States; Hybrid; USD 180,000 - 220,000; Full time

Benefits offered by this job

Medical, dental, vision benefits

Flexible PTO

401(k)

Flexible work from home policy

Home office stipend

Gym/Wifi reimbursement

Education assistance

Parental Leave

Job summary

Canoe Intelligence is seeking a Senior Machine Learning Engineer to develop and deploy models enhancing data management processes. Located in New York City or fully remote in the U.S., the role demands expertise in machine learning, optimization of large language models, and collaboration with engineering teams. Candidates should have at least 5 years’ experience in applied ML engineering and excel in Python. We offer medical benefits, flexible PTO, and a supportive work environment.

Qualifications

• Minimum of 5 years of experience in applied ML engineering, focused on NLP.
• Strong understanding of MLOps and cloud computing platforms.
• Excellent communication skills to collaborate across teams.

Responsibilities

• Design, train, and evaluate ML models for document classification.
• Optimize large language models for domain-specific use cases.
• Work closely with data engineering teams for feature engineering.

Skills

Proficiency in Python

Machine Learning libraries (e.g., TensorFlow, PyTorch)

MLOps (Docker, Kubernetes)

AI-assisted development tools

Communication skills

Problem-solving with product mindset

Education

Bachelor's degree in computer science

Tools

Docker

Kubernetes

Job description

Canoe Intelligence is seeking a Senior Machine Learning Engineer to develop and deploy models enhancing data management processes. Located in New York City or fully remote in the U.S., the role demands expertise in machine learning, optimization of large language models, and collaboration with engineering teams. Candidates should have at least 5 years’ experience in applied ML engineering and excel in Python. We offer medical benefits, flexible PTO, and a supportive work environment.