Job Description
Join the Future of Intelligence at Nexus Core Systems.
Nexus Core Systems is pioneering the next generation of autonomous decision-making frameworks. As we scale our operations to meet the demands of a rapidly evolving digital landscape, we are seeking a visionary Senior AI Engineer to lead our research and deployment efforts. If you are passionate about building scalable machine learning systems and want to define the technology stack for the upcoming era, this is your opportunity to make an impact.
Why Join Us?
- Work on cutting-edge Generative AI and Large Language Model (LLM) applications.
- Competitive compensation package with equity options.
- Flexible remote-first culture with annual team retreats.
- Access to top-tier hardware and cloud infrastructure.
Key Responsibilities:
- Design, develop, and optimize state-of-the-art machine learning models and algorithms tailored for enterprise-scale deployment.
- Lead the end-to-end machine learning lifecycle, from data ingestion and feature engineering to model training, validation, and productionization.
- Collaborate closely with cross-functional teams of data scientists, software engineers, and product managers to translate business requirements into technical solutions.
- Implement robust monitoring and evaluation pipelines to ensure model performance, reliability, and fairness in production environments.
- Stay abreast of the latest advancements in AI research and integrate novel techniques into our existing architecture.
Qualifications:
- Master’s or PhD degree in Computer Science, Mathematics, Statistics, or a related field (or equivalent practical experience).
- Proven experience (5+ years) building and deploying production-grade machine learning models, particularly in Python and TensorFlow or PyTorch.
- Deep understanding of deep learning architectures, natural language processing (NLP), and computer vision.
- Strong proficiency in cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Experience with MLOps tools and version control systems (Git, MLflow).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.
Skills: Python, TensorFlow, PyTorch, NLP, LLM, MLOps, AWS, Docker, Kubernetes, Machine Learning, Data Science
Category: Information Technology
Responsibilities
- Design, develop, and optimize state-of-the-art machine learning models and algorithms tailored for enterprise-scale deployment.
- Lead the end-to-end machine learning lifecycle, from data ingestion and feature engineering to model training, validation, and productionization.
- Collaborate closely with cross-functional teams of data scientists, software engineers, and product managers to translate business requirements into technical solutions.
- Implement robust monitoring and evaluation pipelines to ensure model performance, reliability, and fairness in production environments.
- Stay abreast of the latest advancements in AI research and integrate novel techniques into our existing architecture.
Qualifications
- Master’s or PhD degree in Computer Science, Mathematics, Statistics, or a related field (or equivalent practical experience).
- Proven experience (5+ years) building and deploying production-grade machine learning models, particularly in Python and TensorFlow or PyTorch.
- Deep understanding of deep learning architectures, natural language processing (NLP), and computer vision.
- Strong proficiency in cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Experience with MLOps tools and version control systems (Git, MLflow).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.