Job Description
Are you ready to build the intelligence of tomorrow? Nexus Horizon Systems is seeking a visionary Senior AI/ML Engineer to lead our next-generation research initiatives. As we pivot towards 2026-era technologies, we need a hands-on expert to architect scalable machine learning solutions that redefine industry standards.
In this role, you will not just implement existing algorithms; you will push the boundaries of what is possible, working on cutting-edge Large Language Models (LLMs), generative AI, and predictive analytics platforms. Join a team where your code will power the future of automation and decision-making.
Why Join Us?
- Impactful Work: Deploy AI solutions that affect millions of users globally.
- Future-Proof: Work on technologies that define the roadmap for 2026 and beyond.
- Top-Tier Compensation: Competitive salary, equity package, and comprehensive benefits.
Responsibilities
- Model Architecture & Development: Design, train, and optimize complex deep learning models, specifically focusing on LLMs and NLP pipelines.
- System Scalability: Engineer robust MLOps pipelines to ensure models are scalable, efficient, and production-ready.
- Data Strategy: Lead the data engineering process, including data ingestion, cleaning, and feature engineering for high-dimensional datasets.
- Research & Innovation: Stay at the forefront of AI research, evaluating new libraries and frameworks to improve system performance.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
- Cross-Functional Collaboration: Partner with product managers and software engineers to translate business requirements into technical AI solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, Statistics, or a related quantitative field.
- Technical Expertise: Deep proficiency in Python, PyTorch, TensorFlow, or JAX.
- Experience: 5+ years of experience in building production-level AI/ML systems.
- Tools: Extensive experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Algorithms: Strong grasp of statistical analysis, optimization algorithms, and neural network architectures.
- Problem Solving: Proven track record of solving complex engineering challenges with elegant, efficient code.