AI Engineer

VDart, Inc.
Herndon, VA, United States
9 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Computer Vision Microsoft Azure Big Data Cloud Computing Computer Programming Data Cleansing Python (Programming Language) Machine Learning NumPy Tensorflow
+15 more
Software Engineering Systems Integration Data Processing Google Cloud Pytorch Deep Learning Model Validation Git Pandas Scikit Learn Information Technology Optimization Algorithms Restful APIs Software Version Control Unsupervised Learning

Job description

We are seeking a talented and motivated AI Engineer to join our team. In this role, you will be responsible for designing, developing, and deploying artificial intelligence and machine learning models to solve real-world business challenges. You will work closely with data scientists, software engineers, and product managers to integrate AI-driven solutions into our products and services. —, Design, develop, test, and deploy machine learning models and AI algorithms.

  • Collaborate with cross-functional teams to understand business requirements and deliver AI solutions.
  • Preprocess and analyze large datasets to extract meaningful insights.
  • Implement and optimize AI models for scalability and performance.
  • Monitor, maintain, and improve deployed AI systems.
  • Document solutions, processes, and methodologies for internal knowledge sharing.
  • Stay updated with the latest advancements in AI and machine learning.

Requirements

Programming: Proficiency in Python (preferred) and familiarity with libraries such as TensorFlow, PyTorch, or scikit-learn.

  • Mathematics & Statistics: Solid understanding of linear algebra, probability, statistics, and optimization techniques.
  • Data Handling: Experience with data preprocessing, cleaning, and analysis using tools like Pandas and NumPy.
  • Machine Learning: Knowledge of supervised and unsupervised learning techniques, model evaluation, and validation.
  • Software Development: Understanding of version control systems (e.g., Git) and basic software engineering principles.
  • Problem-Solving: Strong analytical and critical thinking skills.
  • Communication: Ability to clearly explain complex technical concepts to non-technical stakeholders.
  • Education: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent practical experience)., Experience with deep learning frameworks.
  • Familiarity with cloud platforms (AWS, Azure, GCP) and deploying AI models in production environments.
  • Knowledge of natural language processing (NLP) or computer vision.
  • Experience with RESTful APIs and integrating AI models into applications.

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