Job Description
The Future is Now at Quantum Horizon Labs
We are pioneering the next generation of artificial intelligence, building systems designed to revolutionize industries by the year 2026. As a Senior AI/ML Engineer, you will not just write code; you will architect the cognitive backbone of our future products. We are looking for a visionary engineer who thrives on solving complex problems and pushing the boundaries of what is possible in Machine Learning and Deep Learning.
Why Join Us?
- Work on cutting-edge technology that defines the roadmap for 2026.
- Competitive compensation and equity packages.
- Flexible remote and hybrid work options.
- Access to state-of-the-art computing resources and research.
Responsibilities
- Architect & Scale: Design, develop, and deploy scalable machine learning pipelines and infrastructure using modern cloud technologies (AWS/GCP).
- R&D Leadership: Lead research initiatives in Generative AI, Natural Language Processing (NLP), and Computer Vision to prepare for the 2026 product launch.
- Model Optimization: Optimize large language models for latency, throughput, and cost efficiency in production environments.
- Collaboration: Partner with product managers and data scientists to translate business requirements into technical solutions.
- Code Quality: Establish and enforce best practices for code quality, testing, and CI/CD workflows.
- Mentorship: Mentor junior engineers and contribute to the technical growth of the AI team.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Mathematics, or a related field.
- Experience: 5+ years of professional experience in software engineering or machine learning.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Strong understanding of distributed systems.
- Cloud Mastery: Experience with cloud platforms (AWS/GCP/Azure) and containerization tools (Docker, Kubernetes).
- Mathematics: Solid foundation in linear algebra, calculus, and statistics.
- Problem Solving: Ability to debug complex issues and optimize system performance under pressure.