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Information Technology 🏢 Full Time ⭐️ Verified

AI/ML Engineer (2026 Vision)

FutureTech Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Join FutureTech Labs at the forefront of 2026's technological revolution! We're seeking visionary AI/ML Engineers to build the intelligent systems that will define the next decade. As a key innovator in our Austin R&D hub, you'll develop cutting-edge machine learning solutions for autonomous systems, predictive analytics, and human-AI collaboration interfaces. Our culture combines agile methodologies with deep technical exploration, offering competitive equity packages, unlimited learning stipends, and flexible hybrid work arrangements. Shape the future with us!

Responsibilities

  • Design and implement scalable ML pipelines for autonomous decision-making systems
  • Research and prototype next-gen AI architectures for 2026-era applications
  • Collaborate with cross-functional teams to integrate ML models into production systems
  • Develop ethical AI frameworks ensuring responsible deployment of autonomous technologies
  • Lead innovation sprints on human-AI interaction paradigms for 2026 workplace ecosystems
  • Optimize model performance for edge computing environments in IoT networks
  • Document technical specifications and present breakthrough findings to executive stakeholders

Qualifications

  • 5+ years experience in production-level ML/AI development with Python, TensorFlow, and PyTorch
  • Expertise in computer vision, NLP, or reinforcement learning for autonomous systems
  • Published research or proven experience in ethical AI frameworks and bias mitigation
  • Strong background in MLOps and cloud-native deployment (AWS/GCP/Azure)
  • PhD or Master's in Computer Science, AI, or related quantitative field preferred
  • Portfolio demonstrating 2026-relevant projects (autonomous systems, human-AI interfaces)
  • Experience with federated learning and edge computing architectures
  • Certification in responsible AI development (e.g., Google's ML Fairness)

Required Skills

Machine Learning TensorFlow PyTorch Computer Vision NLP Reinforcement Learning MLOps Ethics in AI Cloud Computing Python Autonomous Systems Human-AI Interaction Edge Computing Federated Learning

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