Job Description
Are you ready to architect the intelligence of tomorrow?
At Nexus Horizon Labs, we are not just building software; we are defining the landscape of the future. As a Senior Generative AI Engineer, you will be at the forefront of the next technological revolution. We are seeking a visionary engineer to lead our initiatives in Large Language Models (LLMs), neural architecture search, and autonomous intelligent agents.
Join a team of world-class researchers and developers dedicated to pushing the boundaries of what is possible in 2026 and beyond. If you are passionate about ethical AI, scalable architecture, and building systems that think, we want to hear from you.
Why Join Us?
- Work on cutting-edge AI projects that impact millions.
- Competitive compensation package with equity options.
- Flexible remote-first culture with premium San Francisco amenities.
Key Responsibilities:
- Design and deploy robust, scalable AI infrastructure and large-scale generative models.
- Lead the research and implementation of novel fine-tuning techniques for Large Language Models (LLMs) and multimodal systems.
- Collaborate with product and design teams to translate complex AI capabilities into intuitive user experiences.
- Optimize model inference pipelines for speed, latency, and cost-efficiency in production environments.
- Establish best practices for data governance, model evaluation, and ethical AI deployment.
- Mentor junior engineers and researchers, fostering a culture of innovation and continuous learning.
Qualifications:
- Master’s or PhD degree in Computer Science, Mathematics, Statistics, or a related technical field.
- 5+ years of professional experience in machine learning, deep learning, or natural language processing.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Proven experience working with Hugging Face, LangChain, or similar LLM frameworks.
- Strong understanding of distributed systems, cloud architecture (AWS/GCP/Azure), and MLOps.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
Responsibilities
- Design and deploy robust, scalable AI infrastructure and large-scale generative models.
- Lead the research and implementation of novel fine-tuning techniques for Large Language Models (LLMs) and multimodal systems.
- Collaborate with product and design teams to translate complex AI capabilities into intuitive user experiences.
- Optimize model inference pipelines for speed, latency, and cost-efficiency in production environments.
- Establish best practices for data governance, model evaluation, and ethical AI deployment.
- Mentor junior engineers and researchers, fostering a culture of innovation and continuous learning.
Qualifications
- Master’s or PhD degree in Computer Science, Mathematics, Statistics, or a related technical field.
- 5+ years of professional experience in machine learning, deep learning, or natural language processing.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Proven experience working with Hugging Face, LangChain, or similar LLM frameworks.
- Strong understanding of distributed systems, cloud architecture (AWS/GCP/Azure), and MLOps.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.