Job Description
Horizon 2026 Solutions is at the forefront of the technological renaissance, defining the landscape of tomorrow. We are seeking a visionary Senior AI Engineer to join our elite engineering team. In this role, you will not just build models; you will architect the future of predictive intelligence, ensuring our solutions are robust, scalable, and ready for the challenges of 2026 and beyond.
As a key player in our 2026 Roadmap initiative, you will collaborate with cross-functional teams to integrate cutting-edge Machine Learning and Deep Learning architectures into our core product suite. We value innovation, creativity, and the ability to turn complex data into actionable, human-centric insights.
Why Join Us?
- Future-Proof Technology: Work with state-of-the-art frameworks and next-gen hardware.
- Impactful Work: Your algorithms will directly influence millions of users worldwide.
- Competitive Compensation: Top-tier salary and equity packages tailored for experts.
Responsibilities
- Architect, train, and deploy scalable deep learning models for large-scale production environments.
- Research and implement novel algorithms to push the boundaries of AI capabilities for the 2026 roadmap.
- Collaborate with data scientists and product managers to translate business requirements into technical AI solutions.
- Optimize existing models for latency, throughput, and cost-efficiency in cloud environments.
- Conduct rigorous code reviews and mentor junior engineers to foster a culture of technical excellence.
- Maintain and upgrade the company's MLOps infrastructure to ensure continuous integration and deployment.
Qualifications
- Master’s degree or PhD in Computer Science, Mathematics, or a related field (or equivalent practical experience).
- Minimum of 5+ years of professional experience in Machine Learning or Artificial Intelligence engineering.
- Proficiency in Python, TensorFlow, PyTorch, and Scikit-learn.
- Strong understanding of NLP, Computer Vision, or Reinforcement Learning.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Demonstrated ability to lead technical projects and mentor teams in a fast-paced startup environment.