Job Description
We are Nexus Future Systems, a cutting-edge technology firm pioneering the next generation of Artificial Intelligence solutions. As we gear up for our 2026 product roadmap, we are seeking a visionary Senior AI/ML Engineer to lead our research and deployment initiatives.
In this pivotal role, you will be at the forefront of integrating Generative AI, Large Language Models (LLMs), and predictive analytics into enterprise-grade applications. You will not only build scalable models but also define the technical standards for our engineering team. If you are passionate about solving complex problems and shaping the future of tech, we want to hear from you.
Key Highlights:
- Work on high-impact projects that define the industry standard for 2026.
- Competitive compensation and equity package.
- Flexible remote/hybrid work options in the SF Bay Area.
Responsibilities
- Model Development: Design, train, and fine-tune advanced machine learning and deep learning models using Python, PyTorch, and TensorFlow.
- Infrastructure & MLOps: Build and maintain robust CI/CD pipelines, containerization strategies (Docker/Kubernetes), and cloud infrastructure on AWS or GCP.
- System Optimization: Optimize model inference for low-latency requirements in real-time production environments.
- Research & Innovation: Stay ahead of emerging trends in AI (e.g., Agentic AI, Multimodal models) and experiment with new algorithms to improve product performance.
- Collaboration: Partner with product managers, data scientists, and software engineers to translate business requirements into technical specifications.
- Code Quality: Conduct thorough code reviews and mentor junior engineers to maintain high engineering standards.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, Statistics, or a related technical field.
- Experience: 5+ years of professional experience in machine learning engineering and software development.
- Programming: Expert proficiency in Python, SQL, and experience with C++ or Java is a plus.
- Frameworks: Deep understanding of PyTorch, TensorFlow, Scikit-learn, or Hugging Face Transformers.
- Cloud Mastery: Strong hands-on experience with cloud platforms (AWS/GCP/Azure) and managed ML services.
- Soft Skills: Excellent communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.