Job Description
We are looking for a visionary Senior AI & Machine Learning Engineer to join our elite team in San Francisco. As we prepare for the technological landscape of 2026 and beyond, you will be at the forefront of developing next-generation artificial intelligence systems that solve complex global problems.
In this role, you will design, train, and deploy scalable machine learning models that drive our core product innovation. You will work in a fast-paced, collaborative environment with a focus on ethical AI, deep learning, and real-time data processing. If you are passionate about the future of technology and want to build systems that will define the industry standard for 2026, we want to hear from you.
Why Join Us?
- Work on cutting-edge AI research and development.
- Competitive compensation and equity package.
- Flexible remote-first culture with premium office amenities.
- Professional development budget for conferences and certifications.
Responsibilities
- Design, develop, and optimize deep learning algorithms for large-scale data processing.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to define AI requirements.
- Implement MLOps pipelines to ensure the scalability and reliability of deployed models.
- Conduct thorough research and stay updated on the latest advancements in AI, including Large Language Models (LLMs) and generative AI.
- Monitor model performance in production and perform A/B testing to drive continuous improvement.
- Mentor junior engineers and contribute to code reviews and architectural discussions.
- Ensure all AI systems adhere to ethical guidelines and regulatory standards.
Qualifications
- Master’s or Ph.D. in Computer Science, Machine Learning, or a related technical field (or equivalent practical experience).
- Minimum of 5+ years of professional experience in AI/ML engineering, with a strong portfolio of deployed projects.
- Proficiency in programming languages such as Python, TensorFlow, PyTorch, or JAX.
- Strong understanding of data structures, algorithms, and software engineering best practices.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
- Proven ability to translate complex business requirements into technical AI solutions.
- Excellent problem-solving skills and the ability to thrive in a high-pressure, agile environment.