Job Description
Are you ready to define the technological landscape of the future? Nova Horizon Systems is seeking a visionary Senior AI/ML Engineer to join our elite team. As we accelerate towards our 2026 roadmap, we need a technical expert to build robust, scalable artificial intelligence systems that solve complex global challenges.
Our mission is to integrate cutting-edge AI into everyday workflows, and we are looking for a leader who can bridge the gap between theoretical research and practical application. You will be working in a collaborative environment where your code directly impacts millions of users.
Why Join Us?
- Work on next-generation Large Language Models (LLMs) and Generative AI.
- Competitive compensation package with equity options.
- Comprehensive health, dental, and vision insurance.
- Flexible remote-first work culture with quarterly in-person team retreats.
Responsibilities
- Lead the end-to-end lifecycle of machine learning models, from research and prototyping to deployment at scale using Kubernetes and Docker.
- Architect high-performance neural networks and deep learning frameworks tailored for enterprise needs.
- Collaborate closely with product managers and data scientists to define technical requirements and roadmaps.
- Optimize algorithms for speed, accuracy, and efficiency, ensuring low latency in real-time applications.
- Establish best practices for code quality, testing, and documentation within the engineering team.
- Mentor junior engineers and conduct code reviews to foster a culture of continuous improvement.
- Stay ahead of industry trends in AI, contributing thought leadership to internal and external technical blogs.
Qualifications
- PhD or Master's degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- 8+ years of professional experience in machine learning engineering, preferably in the fintech or healthcare sectors.
- Deep expertise in Python, PyTorch, TensorFlow, and scikit-learn.
- Experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (MLflow, Kubeflow).
- Strong understanding of statistical analysis, data modeling, and experimental design.
- Excellent communication skills with the ability to translate complex technical concepts to non-technical stakeholders.
- Proven track record of shipping production-ready AI products.