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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI & Machine Learning Engineer

Nexus Future Tech
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Shape the Future of Intelligence in 2026

Are you ready to build the breakthrough AI systems of tomorrow? Nexus Future Tech is looking for a visionary Senior AI & Machine Learning Engineer to join our elite R&D division. In this pivotal role, you will architect and deploy cutting-edge Generative AI and Large Language Model (LLM) solutions that redefine industry standards.

We are not just looking for a coder; we need a thought leader who understands the rapid evolution of AI technology. If you thrive in a high-performance environment and want to push the boundaries of what is possible in 2026, this is your stage.

Responsibilities

  • Architect Advanced AI Systems: Design, train, and fine-tune large-scale neural networks and LLMs to solve complex business problems.
  • Optimize Model Performance: Implement techniques such as quantization, pruning, and distributed training to ensure models run efficiently at scale.
  • Lead R&D Initiatives: Conduct research in Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning to stay ahead of the curve.
  • MLOps Implementation: Build robust pipelines for model deployment, monitoring, and retraining using modern CI/CD practices.
  • Cross-Functional Collaboration: Partner with product managers and software engineers to integrate AI models into scalable applications.
  • Ethical AI Governance: Ensure all models adhere to fairness, transparency, and safety guidelines.

Qualifications

  • Education: Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related field.
  • Technical Expertise: 5+ years of professional experience in Machine Learning, Deep Learning, or AI Engineering.
  • Programming: Proficiency in Python and experience with frameworks such as PyTorch, TensorFlow, or JAX.
  • Model Optimization: Deep understanding of model compression, inference optimization, and cloud-based ML infrastructure (AWS, GCP, or Azure).
  • Problem Solving: Proven track record of delivering production-ready AI solutions from concept to deployment.
  • Communication: Excellent ability to translate complex technical concepts for diverse audiences.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP MLOps AWS GCP Cloud Computing Data Structures Algorithms

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