Design, train, and fine-tune large language models (e.g., GPT, LLaMA, PaLM) for various applications.
Conduct research on cutting-edge techniques in natural language processing (NLP) and machine learning to improve model performance.
Explore advancements in transformer architectures, multi-modal models, and emergent AI behaviors.
Collect, clean, and preprocess large-scale text datasets from diverse sources.
Develop and implement data augmentation techniques to improve training data quality.
Ensure data is free from bias and aligned with ethical AI standards.
Optimize model architecture to improve accuracy, efficiency, and scalability.
Implement techniques to reduce latency, memory footprint, and inference time for real-time applications.
Collaborate with MLOps teams to deploy LLMs into production environments using Docker, Kubernetes, and cloud
Develop robust evaluation pipelines to measure model performance using key metrics like accuracy, perplexity, BLEU, and F1 score.
Continuously test for bias, fairness, and robustness of language models across diverse datasets.
Conduct A/B testing to evaluate model improvements in real-world applications. Stay updated with the latest advancements in generative AI, transformers, and NLP research.
Contribute to research papers, patents, and open-source projects.
Present findings and insights at conferences and internal knowledge-sharing sessions.
Qualifications:
7-10 years experience
Advanced degree in CS, Artificial Intelligence, Data Science, or a related field.
Strong programming skills.
Proficiency with deep learning frameworks such as TensorFlow, PyTorch, or JAX.
Hands-on experience with transformer-based models (e.g., GPT, BERT, RoBERTa, LLaMA).
Expertise in natural language processing (NLP) and sequence-to-sequence models.
Familiarity with Hugging Face libraries and OpenAI APIs.
Experience with MLOps tools like Docker, Kubernetes, and CI/CD pipelines.
Strong understanding of distributed computing and GPU acceleration using CUDA.
Knowledge of reinforcement learning and RLHF (Reinforcement Learning with Human Feedback).
Compensation: $90 - $121.86 per hour
ID#: 36408719
Numbers & Facts
Location
Mountain View, CA
Salary
$90–$121.86 Per Hour
Skills
A/B Testingunmatched
Application Programming Interface (API)unmatched
Artificial Intelligence (AI)unmatched
CUDA (Compute Unified Device Architecture)unmatched
Cloud Computingunmatched
Computer Programmingunmatched
Conferencesunmatched
Continuous Deployment/Deliveryunmatched
Continuous Integrationunmatched
Data Qualityunmatched
Data Scienceunmatched
Data Setsunmatched
Deep Learningunmatched
Distributed Computingunmatched
Dockerunmatched
GPU (Graphics Processing Unit)unmatched
JAX (Java API for XML)unmatched
Machine Learningunmatched
Memory Hardwareunmatched
Modeling Languagesunmatched
Natural Language Processing (NLP)unmatched
Open Sourceunmatched
Patentsunmatched
Performance Managementunmatched
Performance Metricsunmatched
Performance Modelingunmatched
Production Systemsunmatched
Quality Managementunmatched
Reinforcement Learningunmatched
Research Skillsunmatched
Training Data Setsunmatched
🎯
Be found by employers
5,500+ employers search our resume database daily. Add yours to get found by recruiters looking for candidates like you.
Level up your application
Professional resume templates
Browse dozens of recruiter approved resume templates, layouts and formats. Choose your favorite and make it your own in minutes.