

Apptad Inc.
Lead AI/Machine Learning Engineer (On W2 Only)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Lead AI/Machine Learning Engineer in Charlotte, NC (Hybrid) for a long-term contract on W2 only. Requires strong Python skills, experience with ML frameworks, and hands-on NLP expertise. No H1B or CPT candidates accepted.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
480
-
🗓️ - Date
May 7, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Hybrid
-
📄 - Contract
W2 Contractor
-
🔒 - Security
Unknown
-
📍 - Location detailed
Charlotte, NC
-
🧠 - Skills detailed
#Spring Boot #NLP (Natural Language Processing) #TensorFlow #Automation #ML (Machine Learning) #"ETL (Extract #Transform #Load)" #AI (Artificial Intelligence) #Data Ingestion #REST (Representational State Transfer) #Python #Programming #Flask #Security #Code Reviews #Classification #Compliance #REST API #Data Engineering #Transformers #FastAPI #Data Pipeline #PyTorch #Microservices #Deployment #Scala #Anomaly Detection #Monitoring
Role description
AI / Machine Learning Engineer
Job Location: Charlotte, NC (Hybrid)
Job Duration: Long Term
(Only on W2)
• No H1B or CPT as per the current client's requirement.
Role Summary
We are seeking an AI / Machine Learning Engineer to design, develop, deploy, and scale AI/ML solutions that solve real‑world business problems. The role focuses on building production‑grade ML models and AI services, integrating them with enterprise systems, and enabling automation, intelligence, and decisioning across platforms.
This role is hands‑on and execution‑focused, working closely with product owners, data engineers, architects, and business stakeholders.
Key Responsibilities
• Design, build, and deploy AI/ML models (supervised, unsupervised, NLP, GenAI where applicable)
• Develop end‑to‑end ML pipelines including data ingestion, feature engineering, model training, evaluation, and deployment
• Build and expose models as APIs / microservices for integration with enterprise applications
• Apply AI to use cases such as:
• Intelligent automation
• Document processing & extraction
• Intent classification & routing
• Prediction, scoring, and anomaly detection
• Collaborate with Data Engineering teams on data pipelines and feature stores
• Implement model monitoring, performance tracking, and retraining strategies
• Ensure solutions meet security, compliance, and governance standards
• Optimize models for accuracy, latency, and scalability
• Contribute to technical design, code reviews, and best practices
Required Skills & Qualifications
• Core Technical Skills
• Strong programming skills in Python (required)
• Experience with ML frameworks: TensorFlow, PyTorch, Scikit‑learn
• Hands‑on with NLP / LLMs (tokenization, embeddings, transformers, prompt engineering)
• Experience building REST APIs (FastAPI, Flask, Spring Boot integrations)
AI / Machine Learning Engineer
Job Location: Charlotte, NC (Hybrid)
Job Duration: Long Term
(Only on W2)
• No H1B or CPT as per the current client's requirement.
Role Summary
We are seeking an AI / Machine Learning Engineer to design, develop, deploy, and scale AI/ML solutions that solve real‑world business problems. The role focuses on building production‑grade ML models and AI services, integrating them with enterprise systems, and enabling automation, intelligence, and decisioning across platforms.
This role is hands‑on and execution‑focused, working closely with product owners, data engineers, architects, and business stakeholders.
Key Responsibilities
• Design, build, and deploy AI/ML models (supervised, unsupervised, NLP, GenAI where applicable)
• Develop end‑to‑end ML pipelines including data ingestion, feature engineering, model training, evaluation, and deployment
• Build and expose models as APIs / microservices for integration with enterprise applications
• Apply AI to use cases such as:
• Intelligent automation
• Document processing & extraction
• Intent classification & routing
• Prediction, scoring, and anomaly detection
• Collaborate with Data Engineering teams on data pipelines and feature stores
• Implement model monitoring, performance tracking, and retraining strategies
• Ensure solutions meet security, compliance, and governance standards
• Optimize models for accuracy, latency, and scalability
• Contribute to technical design, code reviews, and best practices
Required Skills & Qualifications
• Core Technical Skills
• Strong programming skills in Python (required)
• Experience with ML frameworks: TensorFlow, PyTorch, Scikit‑learn
• Hands‑on with NLP / LLMs (tokenization, embeddings, transformers, prompt engineering)
• Experience building REST APIs (FastAPI, Flask, Spring Boot integrations)






