AI Engineer — Build & Deploy Scalable ML Solutions

VDart Inc; Herndon (VA); On-site; USD 110,000 - 170,000; Full time

Job summary

VDart Inc. is seeking an AI Engineer to design, develop, and deploy AI/ML models that solve real-world business challenges. You will work with data scientists, software engineers, and product managers to integrate AI-driven solutions into our products and services.

The role emphasizes data preprocessing, model evaluation, and deployment in production environments, with a focus on scalability, performance, and clear documentation across teams.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Mathematics or related field.
• Proficiency in Python and ML libraries (TensorFlow, PyTorch, scikit-learn).
• Experience with data preprocessing and analysis using Pandas/NumPy.
• Strong knowledge of ML concepts, model evaluation, and validation.
• Familiarity with Git and basic software engineering practices.
• Ability to explain complex concepts to non-technical stakeholders.

Responsibilities

• Design, develop, test, and deploy ML models and AI algorithms.
• Collaborate with cross-functional teams to translate requirements into AI solutions.
• Preprocess and analyze large datasets to extract insights.
• Implement and optimize AI models for scalability and performance.
• Monitor, maintain, and improve deployed AI systems.
• Document solutions and processes for knowledge sharing.
• Stay updated with advancements in AI/ML.

Skills

Python

TensorFlow

PyTorch

scikit-learn

Pandas

NumPy

Git

Problem-solving

Communication

Education

Bachelor's degree in CS/Engineering/Math

Tools

AWS

GCP

RESTful APIs

Docker

Job description

VDart Inc. is seeking an AI Engineer to design, develop, and deploy AI/ML models that solve real-world business challenges. You will work with data scientists, software engineers, and product managers to integrate AI-driven solutions into our products and services.

The role emphasizes data preprocessing, model evaluation, and deployment in production environments, with a focus on scalability, performance, and clear documentation across teams.