Senior Machine Learning Engineer

To keep up with our growth, we are hiring a Machine Learning Engineer to help us expand and scale our data analytics and marketing analytics platforms. The ideal candidate for this role will excel at tackling complex open-ended problems and working in a fast-paced environment, as well helping to guide the strategic direction of the R&D team.

While we are considering stellar remote candidates, this is a hybrid role. We work from our downtown Raleigh office on Mondays, Wednesdays and Fridays, with the option to work remotely on Tuesdays and Thursdays.

A few of our perks and benefits include:

• Competitive salary with generous equity package
• 4% 401K contribution match
• Health, dental and vision insurance
• Short and long-term disability insurance
• Unlimited PTO
  
  

Responsibilities

• Research, develop, evaluate, deploy, and monitor scalable ML platforms and pipelines
• Build and maintain NLP systems, including training and fine-tuning language models, entity resolution tools and LLM-based classification systems
• Review code and promote software development best practices operating inside of Liine’s standard SDLC
• Integrate and update backend APIs, microservices and data pipelines to connect to our ML platforms
• Provide thoughtful input on machine learning strategy, model architecture, and the evolution of our ML systems and team practices.
• Collaborate with engineering and product to deliver machine learning features that create real value
  
  

Requirements

• 3 years of machine learning experience
• Proficiency in Python and key data science libraries (e.g., NumPy, Pandas, PyTorch)
  
  

Experience with the following:

• Prototyping solutions to novel, open-ended problems and transforming them into reliable solutions
• Deploying machine learning models into production environments (MLOps / ModelOps)
• Feature engineering, feature selection, and model architecture design
• Working with large distributed systems and data pipelines
• A high-output, high-excitement environment
• Using AI tools as a core part of how you build. This is your default, not an experiment.
• Solving complex problems at scale
• Meticulous attention to detail
• Communicating honestly and transparently
  
  

Extra credit for experience working with:

• Model interpretability and explainable AI
• Fine-tuning and deploying Large Language Models (LLMs) to production
• Audio and multi-modal model development
• HIPAA compliance