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Senior AI Engineer - Shaping the Future of Intelligence

Nexus Horizon Labs
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

Are you ready to define the next generation of Artificial Intelligence?

Nexus Horizon Labs is a pioneer in building autonomous, reasoning-based AI systems. As we gear up for our 2026 roadmap, we are seeking a visionary Senior AI Engineer to lead the development of our flagship Large Language Model (LLM) infrastructure. You will not just be maintaining models; you will be architecting the neural foundations of tomorrow's intelligent applications.

Why join us?
We offer a competitive equity package, flexible remote-first culture, and the opportunity to work on projects that will redefine human-machine interaction.

Responsibilities

  • Architect & Deploy: Design and implement scalable inference pipelines for large-scale generative AI models, optimizing for speed and cost efficiency.
  • Model Fine-Tuning: Lead the fine-tuning and alignment processes for proprietary LLMs using state-of-the-art techniques like RLHF and DPO.
  • Edge AI: Develop lightweight models optimized for edge deployment, ensuring high-performance AI runs on-device without latency.
  • MLOps & Infrastructure: Build robust CI/CD pipelines for machine learning, managing the full lifecycle from data ingestion to model serving.
  • Cross-Functional Leadership: Collaborate with product managers and data scientists to translate complex AI capabilities into user-centric features.
  • R&D: Stay ahead of the curve by researching emerging architectures (e.g., Mamba, MoE) and integrating breakthrough technologies into our core stack.

Qualifications

  • Education: MS or PhD in Computer Science, Mathematics, or a related field, or equivalent professional experience.
  • Programming: Deep expertise in Python and C++ with strong proficiency in data structures and algorithms.
  • Frameworks: Extensive experience with PyTorch, TensorFlow, or JAX.
  • AI Specialization: Proven track record of working with LLMs, Transformers, and distributed training systems.
  • System Design: Experience designing high-throughput, low-latency systems and familiarity with Kubernetes and cloud infrastructure (AWS/GCP).
  • Communication: Ability to articulate complex technical concepts to non-technical stakeholders clearly and persuasively.

Required Skills

Python PyTorch TensorFlow LLMs MLOps Kubernetes AWS Distributed Systems Machine Learning Deep Learning System Design

Ready to Take This Challenge?

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