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AI/LLM Engineer

T

Location
United States
Trellis

Job Description

About Trellis Law:

We're the leading provider of state trial court data in the US. We utilize AI and Machine Learning to harvest and analyze hundreds of millions of state trial court documents and data that we mine to provide our clients with practical, data-backed intelligence to deliver fast, high-quality results about judicial rulings and competitive analysis. We've recently concluded our Series B finance round and raised $40M!

About The Role:

We are now looking for a seasoned, impact-driven AI/LLM Engineer that wants to be a meaningful part of our Engineering team. You will be building clean, scalable architecture to keep up with our rapidly growing user base and data. As an AI/ML Engineer at Trellis Law, you will work on backend services, data flows and analytics. You will organize, transform and serve large data sets in a high speed and high volume environment.

Key Responsibilities:

  • Use your experience to design features connecting natural language queries with a large corpus of legal knowledge.
  • Build a data architecture you are proud to highlight.
  • Use unstructured data to build large scale data sets.
  • Work on a team dedicated to ML and Data Science with ownership of multiple projects and products.
  • Collaborate with the Product team to understand new features.

About You:

  • At least 7 years of backend engineering experience, at least 3-4 of which were spent building products using LLMs.
  • At least 1-2 years of experience fine-tuning LLMs for domain-specific and otherwise custom use-cases.
  • At least 1-2 years of experience building or using tooling to evaluate LLMs and LLM-based products, e.g. experience evaluating extractive and abstractive summaries.
  • At least 4-5 years of experience deploying custom machine learning models and working on end-to-end ML pipelines, including with unstructured data.
  • Experience building semantic search is a plus.
  • Python proficiency and working knowledge of SageMaker and Bedrock.
  • Strong understanding of Machine Learning, specifically Large Language Models.
  • Have mentored other Engineers in multiple projects.
  • Startup experience is highly valued.
  • BS/MS in Computer Science or a related technical discipline, or equivalent technical work experience.

Benefits:

  • Flexible remote-first work culture (with office space in Los Angeles).
  • We cover 100% of health, dental, and vision insurance for you and for spouses and dependents.
  • 401(k) retirement savings plan with up to 3% employer matching.
  • Flexible vacation policy.
Trellis Law is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, veteran status, parental status, disability status, or any other status protected by the local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.

Advice from our career coach

To excel in the role of an AI/LLM Engineer at Trellis Law, it is essential for applicants to possess a strong foundation in machine learning and data architecture. Here are some key tips for standing out as a candidate:

  • Highlight your experience in backend engineering, specifically building products using Large Language Models (LLMs).
  • Showcase your expertise in fine-tuning LLMs for custom use-cases and evaluating LLM-based products.
  • Demonstrate your proficiency in Python and knowledge of SageMaker and Bedrock.
  • Emphasize your experience with semantic search and deploying custom machine learning models.
  • Illustrate your ability to work on end-to-end ML pipelines with unstructured data.
  • Highlight any experience mentoring other engineers and working in a startup environment.
  • Ensure your resume reflects a BS/MS in Computer Science or equivalent technical work experience.

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About the job

May 4, 2024

Full-time

  1. US United States
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