AI Engineer

Loop; United States; Remote; USD 80,000 - 150,000; Full time

Job summary

An innovative company is seeking a talented AI Engineer to join its dynamic team. In this role, you will work on cutting-edge AI models and features that will directly influence the company's growth in the freight audit and pay market. Your work will involve tackling complex technical challenges, from training multimodal LLMs to enhancing backend systems for automation. This position offers a unique opportunity to shape the future of AI capabilities within the organization, ensuring high standards of data accuracy and system reliability. If you're passionate about AI and eager to make a significant impact, this role is perfect for you.

Qualifications

• Experience with training and deploying machine learning models.
• Strong understanding of ML infrastructure and reliability.

Responsibilities

• Train, evaluate, and deploy machine learning models for high accuracy.
• Scale data infrastructure and improve reliability of ML systems.

Skills

Machine Learning

AI Engineering

Backend Engineering

Data Infrastructure

Model Training and Evaluation

API Integration

Education

Bachelor's Degree in Computer Science or related field

Master's Degree in AI/ML

Tools

Python

TensorFlow

PyTorch

Docker

Kubernetes

Job description

Loop is growing its AI team and you’ll have the opportunity to build both AI models and features that directly impact Loop’s business. Loop is positioned to disrupt the incumbent freight audit and pay market, and is one of the companies leading the AI services wave, utilizing AI to automate complex back-office workflows and tasks. You will face and solve many complex technical challenges while you receive guidance and feedback from the team. The range of work here is broad, you can work on everything from training and deploying in-house multimodal LLMs, scaling our inference infrastructure, or building out and shipping AI agent workflows. In doing so, you’ll have the opportunity to define how the AI and broader Loop team will grow.

What you will work on

Our primary focus has been on document extraction and understanding, where we utilize multimodal LLMs to extract, normalize, and link data together into our domain model. As Loop’s customers rely on Loop to ingest and normalize highly accurate data, we hold ourselves to a high standard to build models with a very high level of accuracy. In tandem, Loop’s machine learning platform requires a high degree of reliability and scalability, and we expect our training and inference volume to scale several orders of magnitude in the coming year. Going forward, Loop will expand its AI capabilities, expanding into other areas such as workflow automation and audit, where we will utilize agents to tackle these problems.

This role spans multiple domains:

• ML modeling – training, evaluating, and deploying models.

• ML infrastructure – scaling data infrastructure, training, or inference, improving reliability of ML systems at Loop.

• AI engineering – utilizing and orchestrating API LLM models to solve business problems at Loop.

• Backend engineering – building out atomic tasks, general backend work in the servicing or automation domain.

Some projects you might work on:

• Scaling up throughput of Loop’s inference engine through continuous batching.

• Developing ways to fine-tuning multimodal LLMs to reduce hallucinations.

• Build out agents that audits freight invoices.