Job Description
Are you ready to shape the future of intelligent systems? Nexus AI Solutions is pioneering the next generation of Artificial Intelligence, and we are seeking a visionary Senior AI & Machine Learning Engineer to join our elite team. In this role, you won't just write code; you will architect the algorithms that define the technological landscape of 2026 and beyond.
We are looking for a thought leader who is passionate about Generative AI, Large Language Models (LLMs), and ethical AI deployment. If you thrive in a fast-paced, innovative environment and want to solve complex problems that impact millions, we want to meet you.
Why Join Us?
- Work with state-of-the-art technology stack including Python, PyTorch, and Kubernetes.
- Competitive compensation package with equity options.
- Flexible remote-first policy with a hub in San Francisco.
- Opportunity to lead research initiatives and mentor junior developers.
Responsibilities
- Model Development & Optimization: Design, train, and deploy scalable machine learning models and deep neural networks to improve product performance and user experience.
- Research & Innovation: Stay ahead of industry trends, particularly in Generative AI and LLMs, to implement cutting-edge solutions for the 2026 roadmap.
- Data Infrastructure: Build robust data pipelines and data lakes to ensure high-quality data ingestion and processing for model training.
- Production Deployment: Oversee the end-to-end ML lifecycle, from experimentation to MLOps and production monitoring.
- Collaboration: Partner with cross-functional teams including Product, Engineering, and Design to translate business requirements into technical solutions.
- Code Review & Mentorship: Maintain high code quality standards and mentor junior engineers and data scientists.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related technical field. PhD preferred.
- Experience: 5+ years of professional experience in software engineering and machine learning.
- Technical Skills: Strong proficiency in Python, TensorFlow, PyTorch, and Scikit-learn.
- Backend Knowledge: Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Deep understanding of statistical analysis, algorithms, and data structures.
- Communication: Excellent verbal and written communication skills with the ability to explain complex technical concepts to non-technical stakeholders.