Text and Speech Analyst (AI/NLP/LLM/ASR)

Location: 100% Remote (U.S.)

Duration: 3–6 Months Contract-to-Hire

Employment Type: W2 Only

Job Summary

We are seeking a highly skilled Text and Speech Analyst with expertise in Artificial Intelligence (AI), Natural Language Processing (NLP), Large Language Models (LLMs), and Automatic Speech Recognition (ASR). The ideal candidate will design, develop, optimize, and deploy AI-powered speech and text solutions while collaborating with cross-functional teams to deliver scalable, production-ready AI applications.

Responsibilities

• Design, develop, and optimize Automatic Speech Recognition (ASR) and NLP models.
• Build AI-powered speech-to-text and text analytics solutions.
• Develop and enhance AI services using ASR frameworks and Large Language Models (LLMs).
• Collaborate with Product Managers, Data Scientists, ML Engineers, Data Engineers, and business stakeholders to deliver AI solutions.
• Evaluate model performance, conduct testing, identify model degradation, and improve accuracy.
• Deploy and monitor AI models in production using MLOps best practices.
• Implement AI governance, model observability, explainability, Responsible AI, and ethical AI practices.
• Ensure data quality, security, compliance, and governance across AI solutions.
• Create reusable AI components, technical documentation, and mentor junior team members.
• Stay current with emerging AI, NLP, Speech AI, and Generative AI technologies.

Required Qualifications

• Bachelor''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''s or Master''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''s degree in Computer Science, Data Science, Artificial Intelligence, Information Systems, Linguistics, or a related field.
• 6+ years of experience in Artificial Intelligence, Machine Learning, NLP, Speech Recognition, or related disciplines.
• Strong hands-on experience building production AI/ML solutions.
• Excellent communication, analytical, and problem-solving skills.
• Experience working in Agile environments.

Required Skills

• Python
• Natural Language Processing (NLP)
• Large Language Models (LLMs)
• Generative AI
• OpenAI
• Azure OpenAI
• GPT
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• Transformer Models
• BERT
• Hugging Face
• Automatic Speech Recognition (ASR)
• Speech Recognition
• Speech-to-Text
• Speech Processing
• Voice AI
• OpenAI Whisper
• Wav2Vec
• DeepSpeech
• Kaldi
• TensorFlow
• PyTorch
• Keras
• Machine Learning
• Deep Learning
• CNN
• RNN
• LSTM
• ANN
• Connectionist Temporal Classification (CTC)
• Hidden Markov Models (HMM)
• Gaussian Mixture Models (GMM)
• Azure AI Services
• Azure Machine Learning (Azure ML)
• Microsoft Azure
• AWS
• Google Cloud Platform (Google Cloud Platform)
• MLOps
• Model Deployment
• Model Monitoring
• Model Observability
• Data Preprocessing
• Data Labeling
• Data Augmentation
• Synthetic Data
• AI Governance
• Responsible AI
• Explainable AI (XAI)
• Data Governance
• Data Security
• Snowflake
• Snowflake Cortex AI
• Databricks
• Databricks AI
• MLflow
• SQL

Preferred Skills

• Dataiku
• Power BI
• WebFOCUS
• Text Analytics
• Text Mining
• Text Classification
• Text Parsing
• Sentiment Analysis
• Named Entity Recognition (NER)
• Conversational AI
• AI Model Evaluation
• AI Model Optimization
• REST APIs
• Git
• CI/CD
• Cloud Computing
• Insurance Domain
• Auto Insurance Claims
• AI Ethics
• Technical Leadership
• Cross-functional Collaboration
• Mentoring

Preferred Experience

• Experience with enterprise AI and Machine Learning solutions.
• Experience deploying AI models on Azure, AWS, or Google Cloud.
• Experience implementing MLOps pipelines and production AI systems.
• Experience with Responsible AI, model governance, and explainability.
• Insurance or Auto Claims industry experience is a plus.

Regards,

Shawn Davis