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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI/ML Engineer

Nexus Future Systems
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
12 Mei 2026
Deadline
12 Mei 2027

Job Description

Are you ready to architect the intelligence of tomorrow? Nexus Future Systems is at the forefront of the next generation of Artificial Intelligence. We are looking for a visionary Senior AI/ML Engineer to lead our R&D initiatives, pushing the boundaries of Generative AI and Large Language Models (LLMs).

In this role, you won't just be maintaining systems; you will be building the foundational models that will define the industry landscape for years to come. You will work in a high-performance environment with top-tier researchers and engineers dedicated to solving the world's most complex computational challenges.

Why Join Us?

  • Work with state-of-the-art hardware and cloud infrastructure.
  • Competitive equity package and top-tier compensation.
  • Flexible remote-first culture with a focus on innovation.

Responsibilities

  • Model Architecture: Design, train, and deploy state-of-the-art machine learning models and deep neural networks using PyTorch and TensorFlow.
  • Optimization: Optimize model inference and training pipelines to reduce latency and increase throughput for real-time applications.
  • Research: Stay ahead of the curve by implementing cutting-edge research in Natural Language Processing (NLP) and Computer Vision.
  • Collaboration: Partner with product managers and engineering teams to translate research into scalable, production-ready features.
  • Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
  • Deployment: Manage the full ML lifecycle from data ingestion to model serving using Kubernetes and cloud-native services.

Qualifications

  • Education: MS or PhD in Computer Science, Statistics, Mathematics, or a related field (4+ years of experience considered equivalent).
  • Experience: Proven track record of building and deploying ML models at scale in a production environment.
  • Programming: Expert-level proficiency in Python and C++.
  • Frameworks: Deep understanding of PyTorch, TensorFlow, or JAX.
  • Libraries: Experience with Hugging Face, Scikit-learn, and Pandas.
  • Cloud: Hands-on experience with AWS (SageMaker, EC2) or GCP (Vertex AI).
  • Soft Skills: Excellent problem-solving abilities and strong communication skills.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP AWS Kubernetes Scikit-learn

Ready to Take This Challenge?

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