Job Description
We are pioneering the future at Quantum Horizon Labs, and we are seeking a visionary Senior Machine Learning Engineer to lead the technical execution of Project 2026. Project 2026 is our flagship initiative designed to redefine the boundaries of autonomous decision-making and predictive analytics in a decentralized world. You will not just be building models; you will be architecting the intelligence layer for the next generation of our enterprise ecosystem.
In this pivotal role, you will collaborate with cross-functional teams of engineers, data scientists, and product strategists to deploy scalable, high-impact AI solutions. If you are passionate about pushing the envelope of what is possible in 2026 and beyond, we want to hear from you.
Responsibilities
- Architect & Deploy: Design, implement, and maintain robust machine learning pipelines and production-grade infrastructure for Project 2026 using Python and cloud-native technologies.
- Model Optimization: Drive the research and development of advanced algorithms, focusing on NLP and Computer Vision to enhance system autonomy.
- Code Quality & Standards: Establish and enforce coding standards, conduct rigorous code reviews, and mentor junior engineers to ensure architectural integrity.
- Performance Tuning: Monitor system performance, optimize latency, and scale models to handle high-throughput data streams in real-time.
- Collaboration: Work closely with product managers to translate complex business requirements into technical specifications and AI solutions.
- Innovation: Stay ahead of industry trends in AI, contributing to the internal innovation roadmap for Project 2026.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.
- Experience: 5+ years of professional experience in machine learning engineering or data science.
- Technical Stack: Proficiency in Python (PyTorch/TensorFlow), SQL, and experience with containerization (Docker/Kubernetes).
- Cloud Expertise: Demonstrated experience deploying models on AWS, GCP, or Azure.
- Problem Solving: Strong analytical skills with a proven track record of solving complex, unstructured problems.
- Communication: Excellent verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders.