NLP Engineer
Trunk Tools$140,000 - $200,000/year
Full Time
Junior (1 to 2 years)
Not SpecifiedCompensation
Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Legal Tech, Artificial Intelligence, SaaSIndustries
Requirements
Candidates should possess a Master's degree in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or a related field, or have at least 2 years of equivalent work experience in a comparable full-time data science role. A minimum of 2 years of experience applying NLP techniques and information retrieval, with a strong understanding of modeling and evaluation methods, is required. Proficiency in Scala or Python is essential, and experience in the medical domain is a plus. The ability to share project samples demonstrating skills is also necessary.
Responsibilities
The Machine Learning Engineer will lead the full data science project lifecycle, including data retrieval, wrangling, model training, validation, deployment, and monitoring. Responsibilities include designing and applying a range of natural language processing techniques, implementing and deploying models into highly performant, real-time applications, and understanding practical business implications to maximize model impact. The role involves embracing an iterative approach to software development, collaborating across the stack, and contributing to technical direction and product strategy.
Skills
Machine Learning
Data Science
Data Retrieval
Data Wrangling
Model Training
Model Validation
Model Deployment
Model Monitoring
Natural Language Processing (NLP)
Containerization
Docker
Python
Pattern Data
AI platform for streamlining litigation processes
About Pattern Data
Pattern Data provides an AI-powered software platform aimed at improving the litigation process for law firms, especially those handling mass tort cases. The platform automates repetitive tasks like reviewing medical records and extensive documentation, enabling legal teams to gather evidence more efficiently and reduce case backlogs. It also offers features such as predicting case quality, conducting rapid case reviews, and automating settlement analysis. Unlike its competitors, Pattern Data focuses specifically on the needs of law firms, providing tools that enhance productivity and accuracy in case management. The goal of Pattern Data is to streamline legal operations, allowing firms to make informed strategic decisions based on comprehensive data analysis.
Charlotte, North CarolinaHeadquarters
2020Year Founded
$1.1MTotal Funding
SEEDCompany Stage
Enterprise Software, AI & Machine Learning, LegalIndustries
11-50Employees
Risks
Competitors like Luminance and Kira Systems are advancing their AI capabilities.
Data privacy regulations like CPRA may increase compliance costs for Pattern Data.
Law firms developing in-house AI solutions could reduce demand for Pattern Data.
Differentiation
Pattern Data uses AI to streamline personal injury claims processing.
The platform automates tedious tasks, improving efficiency for law firms.
Pattern Data offers predictive analytics to enhance case quality assessment.
Upsides
AI adoption in legal tech increased by 30% in 2023.
AI in legal tech is projected to grow at a 28% CAGR until 2028.
AI can reduce case processing time by up to 50%, boosting efficiency.
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