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Information Technology 🏒 Full Time ⭐️ Verified

Senior Generative AI Engineer

NextGen Systems
San Francisco
Estimated Salary
USD 160.000 – USD 220.000
Live Update
20 Mei 2026
Deadline
20 Mei 2027

Job Description

We are looking for a visionary Senior AI Engineer to join our elite engineering team in San Francisco. As the frontier of technology shifts towards autonomous systems and advanced intelligence, NextGen Systems is leading the charge.

In this role, you will design and implement state-of-the-art machine learning models, focusing on Large Language Models (LLMs) and computer vision applications. You will bridge the gap between theoretical research and production-grade deployment, ensuring our AI solutions are scalable, efficient, and ethically sound.

If you are passionate about building the future of AI and want to work in a dynamic, high-growth environment, we want to hear from you.

Responsibilities

  • Architect and train complex machine learning models using PyTorch and TensorFlow.
  • Optimize inference pipelines to reduce latency and improve cost-efficiency.
  • Collaborate with cross-functional teams of data scientists, engineers, and product managers.
  • Mentor junior engineers and establish best practices for MLOps and model governance.
  • Research and integrate novel techniques in Natural Language Processing (NLP) and Generative AI.
  • Ensure data privacy, security, and compliance in all AI model deployments.

Qualifications

  • Ph.D. or Master’s degree in Computer Science, Statistics, or a related technical field.
  • 5+ years of experience in software development with a focus on AI/ML.
  • Strong proficiency in Python and deep understanding of machine learning algorithms.
  • Experience deploying models on cloud platforms (AWS, GCP, or Azure) using Kubernetes or Docker.
  • Proven track record of working with LLMs (e.g., GPT, BERT, LLaMA) or transformers.
  • Excellent problem-solving skills and ability to work in a fast-paced, agile environment.

Required Skills

Python PyTorch TensorFlow Machine Learning MLOps Kubernetes AWS GCP NLP Large Language Models Deep Learning

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