Job Description
Join the Future of Intelligence at Innovate 2026
Innovate 2026 is at the forefront of the AI revolution, building next-generation Large Language Models and generative AI solutions that redefine human-machine interaction. We are seeking a visionary Senior AI Engineer to join our elite engineering team in San Francisco. If you are passionate about pushing the boundaries of what is possible with machine learning and deep learning, we want to hear from you.
In this role, you will not just implement existing models; you will architect and optimize proprietary algorithms that power our core products. You will work in a high-performance environment with the freedom to experiment, innovate, and lead technical initiatives.
Why Innovate 2026?
- Impact: Work on projects that will be used by millions globally.
- Equity: Competitive stock options package.
- Flexibility: Hybrid work model with a focus on results.
- Resources: Access to the latest GPUs and cloud infrastructure.
Responsibilities
- Design, develop, and deploy state-of-the-art machine learning models and algorithms.
- Lead the end-to-end ML lifecycle, from data ingestion and feature engineering to model training, evaluation, and production deployment.
- Optimize existing models for speed, scalability, and energy efficiency.
- Collaborate with cross-functional teams of researchers, product managers, and engineers to translate business requirements into technical solutions.
- Mentor junior engineers and conduct code reviews to maintain high engineering standards.
- Stay abreast of the latest research in NLP, Computer Vision, or Reinforcement Learning to integrate cutting-edge techniques.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related technical field (PhD preferred).
- 5+ years of professional experience in software engineering or machine learning.
- Strong proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
- Extensive experience with Large Language Models (LLMs), RAG pipelines, and fine-tuning techniques.
- Deep understanding of MLOps tools and cloud platforms (AWS, GCP, or Azure).
- Experience with SQL, distributed systems, and high-availability architectures.
- Excellent problem-solving skills and a passion for clean, maintainable code.