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Information Technology 🏢 Full Time ⭐️ Verified

Lead AI Engineer (Project 2026)

QuantumLeap Technologies
Austin
Estimated Salary
USD 180.000 – USD 240.000
New
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

The Future is Now. QuantumLeap Technologies is pioneering the Project 2026 initiative, a cutting-edge AI ecosystem designed to redefine human-machine interaction. We are seeking a visionary Lead AI Engineer to architect scalable, high-performance machine learning systems that will power our platform through the decade ahead.

In this pivotal role, you will lead a team of data scientists and engineers in building the infrastructure for autonomous decision-making. If you are passionate about pushing the boundaries of generative AI, computer vision, and predictive analytics, we want to hear from you.

Why Join Us?

  • Work on mission-critical AI infrastructure.
  • Competitive compensation and equity packages.
  • Flexible remote-first culture with top-tier benefits.

Responsibilities

  • Architectural Leadership: Design and implement scalable ML pipelines and cloud infrastructure using AWS or GCP.
  • Model Optimization: Lead the research and development of state-of-the-art deep learning models to improve accuracy and reduce latency.
  • Team Mentorship: Mentor junior engineers and data scientists, fostering a culture of continuous learning and innovation.
  • Project 2026 Roadmap: Define technical roadmaps and best practices for the upcoming 2026 release cycle.
  • Collaboration: Partner with product managers and stakeholders to translate business requirements into technical solutions.
  • Production Deployment: Oversee the deployment, monitoring, and maintenance of models in production environments.

Qualifications

  • Education: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
  • Experience: 7+ years of experience in software engineering, with at least 3+ years in machine learning engineering.
  • Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or similar deep learning frameworks.
  • Cloud Expertise: Strong experience with cloud platforms (AWS, Azure, or GCP) and containerization tools (Docker, Kubernetes).
  • Problem Solving: Demonstrated ability to solve complex technical challenges and optimize system performance.
  • Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.

Required Skills

Python Machine Learning PyTorch TensorFlow AWS GCP Docker Kubernetes Deep Learning AI Architecture System Design

Ready to Take This Challenge?

Make sure your resume is ready. Submit your application now before the deadline.

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