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Senior AI/ML Engineer - Future Tech (2026 Roadmap)

Apex Horizon Labs
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
14 Mei 2026
Deadline
14 Mei 2027

Job Description

We are building the foundational architecture for the AI era of 2026 and beyond. Apex Horizon Labs is looking for a visionary Senior AI/ML Engineer to spearhead our generative AI initiatives and define the future of intelligent systems.

In this role, you will not just implement existing models; you will push the boundaries of what's possible, optimizing for efficiency, scalability, and ethical AI deployment. If you are passionate about the next generation of Artificial General Intelligence (AGI) and want to shape the roadmap for 2026, we want to hear from you.

Why Join Us?

  • Future-First: Work on cutting-edge technologies that will define the industry standard for 2026.
  • Impact: Your code will power autonomous agents and next-gen LLM applications used by millions.
  • Equity: Competitive stock options in a high-growth startup environment.

Responsibilities

  • Architect LLM Pipelines: Design and deploy robust, scalable Retrieval-Augmented Generation (RAG) architectures to enhance model accuracy and reduce hallucinations.
  • Model Optimization: Fine-tune and quantize large models for edge deployment, ensuring low-latency inference in production environments.
  • 2026 Roadmap Leadership: Collaborate with the CTO to define the technical strategy for future AI capabilities, focusing on Multimodal AI and Agentic workflows.
  • MLOps Implementation: Build and maintain CI/CD pipelines for machine learning, utilizing tools like Kubernetes, MLflow, and Docker for seamless model versioning and deployment.
  • R&D Innovation: Experiment with novel architectures and techniques (e.g., Reinforcement Learning from Human Feedback - RLHF) to improve model alignment and performance.

Qualifications

  • Deep Learning Expertise: 5+ years of experience in AI/ML, with a strong focus on deep learning frameworks (PyTorch or TensorFlow).
  • LLM Mastery: Proven experience working with Large Language Models, transformers, and attention mechanisms.
  • Programming Proficiency: Advanced proficiency in Python, SQL, and C++.
  • Mathematical Foundation: Strong understanding of linear algebra, calculus, probability, and statistics.
  • Production Experience: Demonstrated track record of deploying machine learning models to high-traffic production systems.
  • Communication: Excellent ability to translate complex technical concepts for cross-functional teams.

Required Skills

Python PyTorch TensorFlow Large Language Models LLMs Machine Learning Deep Learning MLOps Kubernetes Docker SQL NLP Generative AI Stanford NLP Hugging Face

Ready to Take This Challenge?

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