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Information Technology 🏢 Full Time ⭐️ Verified

AI/ML Engineer - Future Tech Visionary

Nexus Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
14 Mei 2026
Deadline
14 Mei 2027

Job Description

Join Nexus Innovations at the forefront of technological evolution as we pioneer solutions for 2026 and beyond. We seek an AI/ML Engineer to architect intelligent systems that redefine human-machine interaction. In this pivotal role, you'll leverage cutting-edge frameworks to develop adaptive algorithms, driving breakthroughs in autonomous systems and predictive analytics. Our dynamic R&D environment fosters cross-functional collaboration with quantum computing specialists and neuroscientists to create tomorrow's technological paradigms.

Competitive compensation includes equity, comprehensive benefits, and dedicated innovation time for personal projects. We champion a culture of intellectual curiosity and rapid prototyping, where your ideas can transform industries.

Responsibilities

  • Design and implement scalable machine learning pipelines for next-gen autonomous systems
  • Develop adaptive AI models using reinforcement learning and federated learning techniques
  • Collaborate with quantum computing teams to hybridize classical and quantum algorithms
  • Architect ethical AI frameworks aligned with 2026 regulatory standards
  • Lead cross-functional workshops to translate business challenges into technical solutions
  • Contribute to open-source projects advancing explainable AI methodologies
  • Prototype neural interfaces for human-AI symbiosis applications

Qualifications

  • MS/PhD in Computer Science, AI, or related field with 5+ years industry experience
  • Expertise in PyTorch/TensorFlow and distributed training architectures
  • Published research in reinforcement learning or neuro-symbolic AI
  • Proficiency with MLOps tools (Kubeflow, MLflow) and cloud deployment (AWS/GCP)
  • Demonstrated experience building ethical AI frameworks with bias mitigation
  • Strong background in probabilistic modeling and Bayesian inference
  • Portfolio showcasing deployed AI systems handling >10M daily interactions

Required Skills

Python PyTorch TensorFlow Reinforcement Learning Quantum Computing MLOps Neural Interfaces Ethical AI Distributed Systems Bayesian Inference

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