Job Description
Are you ready to define the technological landscape of 2026? Apex Neural Systems is seeking a visionary Senior AI/ML Engineer to lead our next-generation generative intelligence initiatives. In this pivotal role, you will not just build models; you will architect the future of human-machine interaction.
Based in the heart of San Francisco's tech district, you will work with a world-class team pushing the boundaries of what is possible with Large Language Models (LLMs), autonomous agents, and predictive analytics. If you are passionate about ethical AI, scalable architecture, and have a knack for solving complex problems, we want to hear from you.
Why Join Us?
- Impact: Directly influence products used by millions globally.
- Equity: Competitive equity package in a Series D-funded unicorn.
- Flexibility: Hybrid work model with fully remote options.
- Benefits: Top-tier health coverage, 401k matching, and continuous learning stipends.
We are looking for someone who thrives in ambiguity and possesses the technical prowess to turn abstract concepts into production-ready reality.
Responsibilities
- Architect & Deploy: Design, develop, and deploy state-of-the-art machine learning models and AI agents at scale using Python, PyTorch, and TensorFlow.
- Model Optimization: Fine-tune and optimize large language models (LLMs) for performance, latency, and cost efficiency in real-world applications.
- System Integration: Collaborate with cross-functional teams (Product, Engineering, Data Science) to integrate AI capabilities into core product features seamlessly.
- Research & Innovation: Stay ahead of the curve by researching emerging AI trends, including multi-modal models and reinforcement learning, and prototype new solutions.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and continuous learning within the engineering team.
- Infrastructure: Work closely with MLOps engineers to build robust CI/CD pipelines and data pipelines ensuring data integrity and model reproducibility.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field (PhD preferred).
- Experience: 5+ years of professional experience in software engineering or machine learning, with at least 2 years focused on AI/ML research or production systems.
- Technical Skills: Proficiency in Python, SQL, and experience with deep learning frameworks (PyTorch, TensorFlow, or JAX).
- AI Expertise: Deep understanding of NLP, LLMs, or Computer Vision architectures.
- Software Engineering: Strong understanding of software design patterns, distributed systems, and cloud infrastructure (AWS, GCP, or Azure).
- Problem Solving: Proven track record of tackling complex, ambiguous problems and delivering scalable solutions under tight deadlines.