Senior Generative AI Engineer

Role: Senior Generative AI Engineer
Location: McLean
Duration: 6 months

Exp range in required skills: 10+ years
Key Responsibilities:
Designing and Developing Generative AI Models: This involves creating and fine-tuning algorithms for generating new content, using techniques like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer-based models.
Optimizing Model Performance: This includes improving model efficiency, scalability, and accuracy
Collaborating with Cross-Functional Teams: Working with product managers, engineers, and other stakeholders to define project goals, requirements, and solutions.
Developing and Maintaining Documentation:
Creating clear and concise documentation for models, processes, and results.
Communicating Complex Concepts:
Explaining technical details to both technical and non-technical audiences.
Providing Support and Guidance:
Mentoring junior team members and offering expertise on generative AI.
Integrating AI Solutions: Implementing and integrating generative AI solutions into existing systems and workflows.
Data Preprocessing and Analysis: Working with large datasets, including tasks like data cleaning, feature extraction, and data analysis.
Skills and Knowledge:
Strong Foundation in Computer Science: A degree or equivalent experience in computer science, AI, machine learning, or a related field is usually required.
Programming Proficiency:
Fluency in programming languages like Python is essential, along with knowledge of data structures and algorithms.
Machine Learning and Deep Learning: Expertise in machine learning principles, deep learning techniques, and relevant frameworks like TensorFlow or PyTorch.
Generative AI Expertise: Deep understanding of GANs, VAEs, and transformer-based models.
Natural Language Processing (NLP): Experience with NLP techniques and tools can be beneficial, especially for text-based generative AI models.
Generative AI 7+ years.