Job Description
Architecting the Intelligence of Tomorrow
At Nexus Horizon, we aren't just predicting the future; we are building it. We are seeking a visionary Senior AI Engineer to join our core team and help define the 2026 Roadmap for our next-generation generative AI platform. You will work at the intersection of deep learning, NLP, and scalable cloud architecture to solve complex problems that define the era of autonomous systems.
Why Join Us?
- Impactful Work: Your code will directly influence how millions of users interact with AI.
- Innovation First: We invest heavily in R&D, giving you the freedom to experiment with cutting-edge models.
- Top-Tier Team: Collaborate with PhDs and industry veterans from FAANG.
Responsibilities
- Lead the end-to-end development of large-scale machine learning models and neural networks.
- Optimize existing models for latency, throughput, and inference costs to meet 2026 production standards.
- Collaborate with product teams to translate business requirements into technical AI solutions.
- Design and implement MLOps pipelines for automated training, evaluation, and deployment.
- Stay ahead of the curve by researching and integrating emerging AI architectures and algorithms.
- Mentor junior engineers and conduct code reviews to maintain high technical standards.
Qualifications
- 5+ years of experience in Machine Learning, Deep Learning, or AI Engineering.
- Proficiency in Python, PyTorch, or TensorFlow.
- Strong understanding of NLP, LLMs, or Computer Vision architectures.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Proven track record of deploying models to production environments.
- BS, MS, or PhD in Computer Science, Mathematics, or a related technical field.
Responsibilities
- Lead the end-to-end development of large-scale machine learning models and neural networks.
- Optimize existing models for latency, throughput, and inference costs to meet 2026 production standards.
- Collaborate with product teams to translate business requirements into technical AI solutions.
- Design and implement MLOps pipelines for automated training, evaluation, and deployment.
- Stay ahead of the curve by researching and integrating emerging AI architectures and algorithms.
- Mentor junior engineers and conduct code reviews to maintain high technical standards.
Qualifications
- 5+ years of experience in Machine Learning, Deep Learning, or AI Engineering.
- Proficiency in Python, PyTorch, or TensorFlow.
- Strong understanding of NLP, LLMs, or Computer Vision architectures.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Proven track record of deploying models to production environments.
- BS, MS, or PhD in Computer Science, Mathematics, or a related technical field.