Job Description
We are looking for a visionary Senior AI Engineer to join Apex Neural Systems in San Francisco. As we prepare for the next generation of AI capabilities, we need an expert to architect and deploy scalable, high-performance generative models. You will be at the forefront of the 2026 AI revolution, building the infrastructure that powers intelligent agents and autonomous systems.
Why Join Us?
Work with state-of-the-art LLMs, contribute to open-source AI ecosystems, and define the technical roadmap for a leading tech firm.
Core Responsibilities:
Architect and optimize deep learning pipelines for production environments. Collaborate with product teams to translate complex AI requirements into technical solutions. Conduct research on novel transformer architectures to improve model efficiency and accuracy. Monitor model performance and implement real-time inference optimization strategies. Mentor junior engineers and conduct code reviews to maintain high engineering standards.
Qualifications:
Master’s degree or PhD in Computer Science, Mathematics, or a related field. 5+ years of experience in machine learning engineering and deep learning. Proficiency in Python, PyTorch, and TensorFlow. Strong understanding of Natural Language Processing (NLP) and Large Language Models (LLMs). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
Responsibilities
- Lead the design and implementation of scalable ML infrastructure for 2026 AI initiatives.
- Research and fine-tune large language models to enhance domain-specific performance.
- Collaborate cross-functionally with Data Scientists and Product Managers.
- Optimize model latency and throughput for real-time applications.
- Ensure robust data governance and model security protocols are in place.
- Drive technical decision-making regarding model architecture and deployment strategies.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, AI, or a related technical field.
- Proven experience with deep learning frameworks (PyTorch/TensorFlow).
- Strong programming skills in Python and SQL.
- Experience with MLOps tools (MLflow, Kubeflow, or Vertex AI).
- Excellent problem-solving skills and ability to work in a fast-paced agile environment.
- Clear communication skills for translating technical concepts to non-technical stakeholders.