Job Description
We are seeking a visionary Senior Machine Learning Engineer to join Nebula Horizon. As a pioneer in next-generation artificial intelligence, we are building the infrastructure that powers the autonomous systems of tomorrow. If you are passionate about pushing the boundaries of what's possible with Large Language Models (LLMs) and predictive analytics, we want to meet you.
In this role, you will design, train, and deploy state-of-the-art machine learning models that directly impact millions of users. You will work in a high-performance environment with top-tier researchers and engineers, focusing on scalability, efficiency, and ethical AI development.
Why Join Us?
- Competitive compensation and equity packages.
- Flexible remote-first culture with office hubs in Austin.
- Access to cutting-edge hardware and cloud infrastructure.
- Continuous learning opportunities with industry leaders.
Ready to shape the future? Apply today.
Responsibilities
- Design, develop, and optimize state-of-the-art machine learning models and algorithms.
- Lead the end-to-end ML lifecycle, from data ingestion and preprocessing to model training, evaluation, and deployment.
- Collaborate with cross-functional teams (Data Science, Product, Engineering) to translate business requirements into technical solutions.
- Implement MLOps best practices to ensure model reliability, scalability, and monitoring in production environments.
- Research and integrate the latest advancements in Generative AI and Deep Learning architectures.
- Conduct rigorous A/B testing and performance analysis to drive continuous model improvement.
Qualifications
- Master’s or Ph.D. in Computer Science, Mathematics, Statistics, or a related field.
- Minimum of 5+ years of professional experience in machine learning engineering or data science.
- Proficiency in Python and deep frameworks such as PyTorch or TensorFlow.
- Strong experience with LLMs (Hugging Face, OpenAI API, LangChain) and fine-tuning techniques.
- Hands-on experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.