Job Description
Are you ready to define the technological landscape of 2026? Apex Future Systems is seeking a visionary Senior AI Engineer to join our elite research and development team. We are building the next generation of intelligent autonomous systems and we need a leader who can bridge the gap between cutting-edge research and scalable production code.
In this role, you won't just write code; you will architect the future. You will work directly with CTOs and Product Leads to deploy generative AI solutions that redefine user experiences. If you are passionate about Large Language Models (LLMs), Computer Vision, and the ethical implications of AI, this is the opportunity you have been waiting for.
Why join us?
- Competitive base salary and equity package.
- Flexible remote-first culture with HQ in San Francisco.
- Access to the latest hardware and cloud infrastructure.
- Continuous learning budget and conference attendance.
Responsibilities
- Design, implement, and optimize complex machine learning models for real-time applications.
- Lead the architecture of data pipelines and MLOps workflows to ensure model reliability and scalability.
- Conduct original research to push the boundaries of current AI capabilities.
- Collaborate with cross-functional teams (Product, Design, Engineering) to translate business needs into technical AI solutions.
- Mentor junior engineers and conduct technical code reviews to maintain high standards of excellence.
- Stay ahead of industry trends in AI safety, fairness, and efficiency.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of professional experience in AI/ML engineering, with at least 2 years in a senior role.
- Expert proficiency in Python, PyTorch, TensorFlow, and scikit-learn.
- Deep experience with LLMs (e.g., GPT-4, LLaMA, Claude) and RAG architectures.
- Strong understanding of cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Proven track record of deploying models that handle high traffic and latency requirements.