Job Description
Are you ready to architect the future of intelligent systems?
At Nexus Horizon AI, we are at the forefront of the Generative AI revolution. We are seeking a visionary Senior Machine Learning Engineer to join our elite team in San Francisco. You will play a pivotal role in developing, training, and deploying state-of-the-art Large Language Models (LLMs) that power the next generation of enterprise solutions.
If you are passionate about scaling AI infrastructure and solving complex data challenges, we want to hear from you.
At Nexus Horizon AI, we are at the forefront of the Generative AI revolution. We are seeking a visionary Senior Machine Learning Engineer to join our elite team in San Francisco. You will play a pivotal role in developing, training, and deploying state-of-the-art Large Language Models (LLMs) that power the next generation of enterprise solutions.
If you are passionate about scaling AI infrastructure and solving complex data challenges, we want to hear from you.
Responsibilities
- Model Development: Design, implement, and optimize deep learning models, specifically focusing on NLP and Transformer architectures.
- Production Deployment: Lead the end-to-end deployment of ML models into production environments using Docker, Kubernetes, and cloud-native infrastructure (AWS/GCP).
- Performance Optimization: Conduct rigorous testing and optimization of model inference speeds and accuracy to ensure real-time responsiveness.
- Data Engineering: Collaborate with data engineering teams to build robust data pipelines and ensure high-quality training datasets.
- Research & Innovation: Stay ahead of the curve by researching the latest academic papers and industry trends to integrate cutting-edge techniques into our stack.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Mathematics, Statistics, or a related field.
- Experience: 5+ years of professional experience in Machine Learning Engineering or Data Science.
- Tech Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX.
- Frameworks: Strong experience with Hugging Face Transformers, LangChain, or similar AI frameworks.
- Infrastructure: Solid understanding of MLOps practices, CI/CD pipelines, and cloud platforms.
- Communication: Excellent ability to communicate complex technical concepts to non-technical stakeholders.