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Information Technology 🏢 Full Time ⭐️ Verified

Senior Machine Learning Engineer (2026 Vision)

Nexus Horizon Labs
San Francisco
Estimated Salary
USD 160.000 – USD 240.000
Live Update
22 Mei 2026
Deadline
22 Mei 2027

Job Description

Join the Future of Intelligence

Nexus Horizon Labs is pioneering the next generation of artificial intelligence architectures. We are seeking a visionary Senior Machine Learning Engineer to lead the development of scalable AI models designed for the year 2026 and beyond. You will work on cutting-edge generative models and autonomous systems that will define the future of enterprise automation.

In this role, you will bridge the gap between theoretical research and production-grade deployment, ensuring our AI solutions are robust, efficient, and ethically sound.

Responsibilities

  • Architect & Deploy: Design, build, and deploy scalable machine learning pipelines and model architectures using modern cloud infrastructure (AWS/GCP).
  • Model Optimization: Fine-tune large language models (LLMs) and transformer architectures to improve inference speed and accuracy for real-time applications.
  • Collaboration: Partner with data scientists, product managers, and software engineers to translate business requirements into technical AI solutions.
  • Research: Stay at the forefront of AI research, evaluating and integrating new techniques such as federated learning or reinforcement learning.
  • Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and innovation within the team.
  • Infrastructure: Oversee the integration of AI models into microservices and ensure high availability and fault tolerance of ML systems.

Qualifications

  • Experience: 5+ years of professional experience in software engineering or machine learning engineering.
  • Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, or JAX. Strong understanding of distributed systems and parallel computing.
  • Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related technical field.
  • Tools: Proficiency with containerization (Docker, Kubernetes) and CI/CD pipelines (GitHub Actions, Jenkins).
  • Communication: Excellent verbal and written communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
  • Problem Solving: Demonstrated ability to troubleshoot complex system issues and optimize performance bottlenecks.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning AWS Docker Kubernetes NLP Distributed Systems CI/CD

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