Job Description
We are on a mission to architect the intelligent systems of 2026 and beyond. Nexus Horizon Labs is seeking a visionary Senior AI/ML Engineer to lead the development of next-generation generative models and autonomous agents. If you are passionate about pushing the boundaries of artificial intelligence and building scalable systems that solve complex real-world problems, we want to meet you.
As a key member of our R&D division, you will work in a high-performance environment focused on innovation, ethical AI, and rapid deployment. You will have the autonomy to experiment with cutting-edge architectures and the responsibility to deploy robust, production-ready solutions that define the future of our industry.
Responsibilities
- Model Architecture & Training: Design, train, and fine-tune state-of-the-art deep learning models, focusing on Large Language Models (LLMs) and multimodal systems.
- Infrastructure & MLOps: Build and maintain scalable MLOps pipelines using Kubernetes, Docker, and cloud-native technologies to ensure high availability and performance.
- Optimization & Efficiency: Implement model quantization, pruning, and distillation techniques to optimize inference speed and reduce latency for edge deployments.
- R&D Collaboration: Partner with data scientists and product engineers to translate research concepts into practical, high-impact applications.
- Ethical AI: Establish and enforce guidelines for bias mitigation, safety, and compliance in AI model outputs.
- Code Quality: Write clean, maintainable, and well-documented code while conducting rigorous code reviews and technical mentoring for junior engineers.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, Statistics, or a related technical field.
- Experience: 5+ years of professional experience in machine learning engineering or data science with a strong portfolio of deployed models.
- Programming: Expert-level proficiency in Python (PyTorch, TensorFlow, or JAX) and SQL.
- Cloud & Tools: Deep experience with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
- Mathematics: Solid understanding of linear algebra, calculus, and probability/statistics.
- Communication: Excellent verbal and written communication skills with the ability to explain complex technical concepts to diverse stakeholders.