Job Description
Join the Future of Intelligence.
Are you a visionary engineer ready to architect the next generation of artificial intelligence systems? Nexus Innovations is seeking a world-class Senior AI Engineer to lead the development of scalable machine learning models that power our enterprise solutions. If you are passionate about pushing the boundaries of Large Language Models (LLMs), Natural Language Processing, and Computer Vision, we want to hear from you.
We offer a competitive compensation package, equity opportunities, and the chance to work on cutting-edge technology in the heart of the Silicon Valley.
Responsibilities
- Model Development & Training: Design, train, and fine-tune advanced deep learning models using Python and TensorFlow/PyTorch to solve complex business problems.
- System Optimization: Optimize inference pipelines for low-latency, high-throughput performance in production environments.
- Research & Innovation: Stay abreast of the latest research in AI/ML and implement state-of-the-art techniques to improve model accuracy.
- Collaboration: Work closely with cross-functional teams of data scientists, software engineers, and product managers to translate business requirements into technical solutions.
- Deployment: Manage the full ML lifecycle, including data ingestion, model training, validation, and deployment via CI/CD pipelines.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, Statistics, or a related field.
- Experience: Minimum of 5+ years of professional experience in software engineering or machine learning.
- Technical Skills: Proficiency in Python (Pandas, NumPy, Scikit-learn), deep learning frameworks (PyTorch, TensorFlow), and SQL.
- Specialization: Strong experience with LLMs (Hugging Face, OpenAI API), RAG architectures, or Generative AI is highly preferred.
- Infrastructure: Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
- Problem Solving: Demonstrated ability to tackle unstructured problems and derive actionable insights from large datasets.