Job Description
Apex Neural Systems is pioneering the next generation of Artificial Intelligence solutions. We are looking for a visionary Senior AI Engineer to join our elite team in San Francisco. In this role, you will architect and deploy scalable machine learning models that solve complex problems and drive our product roadmap toward a 2026-ready future.
As a key technical leader, you will bridge the gap between research and production, ensuring our models are not only accurate but also ethical, efficient, and compliant with industry standards.
Why Join Us?
- Work on cutting-edge Generative AI and Large Language Models (LLMs).
- Competitive equity package and benefits.
- Flexible remote-first culture with a vibrant SF office.
Key Responsibilities
- Design, train, and deploy end-to-end deep learning models for NLP and Computer Vision applications.
- Optimize model inference latency and resource efficiency for cloud and edge deployment.
- Collaborate with product managers and data scientists to translate business requirements into technical architecture.
- Implement rigorous testing, validation, and monitoring pipelines to ensure model reliability.
- Stay ahead of the curve on emerging AI trends to guide the company's strategic direction through 2026.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related technical field.
- 5+ years of professional experience in AI/ML engineering, with a strong portfolio of deployed models.
- Expert proficiency in Python, PyTorch, and TensorFlow.
- Deep understanding of MLOps, CI/CD pipelines, and containerization (Docker/Kubernetes).
- Experience with cloud platforms (AWS, GCP, or Azure) and vector databases.
Responsibilities
- Design, train, and deploy end-to-end deep learning models for NLP and Computer Vision applications.
- Optimize model inference latency and resource efficiency for cloud and edge deployment.
- Collaborate with product managers and data scientists to translate business requirements into technical architecture.
- Implement rigorous testing, validation, and monitoring pipelines to ensure model reliability.
- Stay ahead of the curve on emerging AI trends to guide the company's strategic direction through 2026.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related technical field.
- 5+ years of professional experience in AI/ML engineering, with a strong portfolio of deployed models.
- Expert proficiency in Python, PyTorch, and TensorFlow.
- Deep understanding of MLOps, CI/CD pipelines, and containerization (Docker/Kubernetes).
- Experience with cloud platforms (AWS, GCP, or Azure) and vector databases.