Generative AI Engineer

Overview

On Site
Full Time
Part Time
Accepts corp to corp applications
Contract - Independent
Contract - W2

Skills

Large Language Models (LLMs)
BERT
Data Management
Data Quality
Optimization
Scalability
Workflow
Collaboration
Artificial Intelligence
Research
Generative Artificial Intelligence (AI)
Research and Development
Innovation
Computer Science
Mathematics
Programming Languages
Python
TensorFlow
PyTorch
Keras
Machine Learning (ML)
Algorithms
Deep Learning
Evaluation
Management
Cloud Computing
Amazon Web Services
Google Cloud Platform
Google Cloud
Microsoft Azure
Presentations
Communication

Job Details

Hiring: W2 Candidates Only

Location: USA

Visa: Open to any visa type with valid work authorization in the USA

Experience Required: 6 to 12 years

Level: Mid to Lead positions

Key Responsibilities

  • Model Development: Design and implement generative models, including GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and large language models (LLMs) like GPT or BERT.

  • Data Management: Collect, preprocess, and augment large datasets to train generative models, ensuring data quality and relevance.

  • Model Optimization: Tune hyperparameters and employ techniques like model pruning and quantization to enhance model performance and efficiency.

  • Deployment & Integration: Deploy generative models into production environments, ensuring scalability and reliability. Integrate models with existing systems and workflows.

  • Collaboration: Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to align AI solutions with business objectives.

  • Research & Innovation: Stay updated with the latest advancements in generative AI technologies and methodologies. Contribute to research and development efforts to drive innovation within the organization.


Required Skills & Qualifications

  • Education: Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.

  • Programming Languages: Proficiency in Python, with experience in ML libraries such as TensorFlow, PyTorch, and Keras.

  • Machine Learning Expertise: Strong foundation in machine learning algorithms, deep learning techniques, and model evaluation metrics.

  • Data Handling: Experience with data preprocessing, augmentation, and management of large-scale datasets.

  • Model Deployment: Familiarity with deploying models on cloud platforms (AWS, Google Cloud Platform, Azure) and integrating them into production systems.

  • Communication Skills: Ability to communicate complex technical concepts to non-technical stakeholders.


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