Job Description
Are you ready to shape the future of Artificial Intelligence?
Nexus Innovations is on the hunt for a visionary Senior AI/ML Engineer to join our elite San Francisco team. We are pioneers in applying Large Language Models (LLMs) to solve complex enterprise challenges. If you possess a deep understanding of machine learning architectures and a passion for ethical AI, we want to hear from you.
In this role, you won't just write code; you will architect the intelligence that powers our products. You will work closely with cross-functional teams of data scientists, product managers, and engineers to deploy cutting-edge solutions at scale.
Why join us?
- Competitive equity package and top-tier health benefits.
- Flexible remote-first policy with a vibrant San Francisco HQ.
- Access to the latest hardware and cloud infrastructure.
- Continuous learning opportunities and a culture of innovation.
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art generative AI models and large language models to optimize performance and accuracy.
- System Architecture: Build scalable and robust MLOps pipelines to ensure seamless deployment and monitoring of models in production environments.
- Research & Innovation: Stay abreast of the latest advancements in the AI field (e.g., Transformers, Diffusion Models) and integrate novel techniques into our product suite.
- Code Review & Mentorship: Provide technical leadership and mentorship to junior engineers and data scientists, maintaining high code quality and best practices.
- Collaboration: Partner with product teams to define AI requirements and translate business needs into technical specifications.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- Experience: 5+ years of professional experience in machine learning, deep learning, or natural language processing.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow. Strong experience with SQL and distributed computing frameworks (e.g., Apache Spark, Ray).
- Deployment: Demonstrated experience deploying models via AWS SageMaker, Kubernetes, or Docker.
- Communication: Excellent ability to communicate complex technical concepts to non-technical stakeholders.