Data Scientist - USA | Remote
TRENT HOEK OUTDOORS LLC
United States
10 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$140,000
Working hours
Regular working hours
Job source
Tech stack
Data Cleansing
Machine Learning
Natural Language Processing
Software Deployment
Feature Engineering
Chatbots
Large Language Models
Multi-Agent Systems
Model Validation
Document Classification
Job description
3 Dots IT Solutions is seeking a Data Scientist specializing in Conversational AI and Natural Language Processing (NLP) for an investment partner. This is a remote position open to candidates located within the United States. Candidates should be available for a face-to-face interview as part of the selection process., * Build and enhance complex virtual assistants, including conversation design, intent and entity modeling, error analysis, and production improvements.
- Develop and improve NLP and machine learning solutions, including text classification, embeddings, and models based on Transformer architecture and large language models (LLMs).
- Perform machine learning tasks such as feature engineering, time-series forecasting, data preprocessing, and model evaluation.
- Work with agentic AI and multi-agent architectures, including evaluation frameworks, golden datasets, and LLM-as-a-Judge approaches.
- Support model fine-tuning and continuous improvement of AI systems.
- Improve the performance of AI models in production through inference optimization, KV caching, latency reduction, scalability, and deployment practices.
Requirements
- Strong expertise in Natural Language Processing (NLP), including text classification and embeddings.
- Solid understanding of LLM fundamentals and Transformer architecture.
- Hands-on experience with machine learning modeling, feature engineering, time-series forecasting, data preprocessing, and model evaluation.
- Experience building and enhancing conversational AI systems, including virtual assistants, intent and entity modeling, and conversation design.
- Knowledge of multi-agent architectures and agentic AI evaluation methods.
- Understanding of production deployment and optimization of machine learning and LLM systems, including inference performance, KV caching, latency, and scalability.
- Ability to attend a face-to-face interview during the selection process.
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