Job Description
We are on a mission to redefine the boundaries of autonomous systems and we are looking for a visionary Senior AI/ML Engineer to join Project 2026. As a key player in our elite engineering team, you will architect the neural networks and machine learning pipelines that power our next-generation aerospace and technology solutions.
In this high-impact role, you will bridge the gap between theoretical research and real-world application, ensuring our systems are not only smart but scalable, secure, and robust. If you are passionate about the future of technology and want to leave a lasting legacy in the industry, we want to hear from you.
Why Join Us?
- Impactful Work: Directly contribute to the technologies that will define the next decade of autonomous travel.
- Top-Tier Compensation: Competitive salary, equity package, and comprehensive benefits.
- Flexible Environment: Remote-first culture with occasional opportunities for in-person collaboration.
Responsibilities
- Design, develop, and deploy state-of-the-art machine learning models and deep neural networks for complex data environments.
- Collaborate with cross-functional teams (software engineers, data scientists, and product managers) to translate business requirements into technical solutions.
- Optimize and scale existing algorithms to improve inference speed and accuracy under real-world constraints.
- Conduct rigorous code reviews and mentor junior engineers to maintain the highest standards of engineering excellence.
- Stay at the forefront of AI research and evaluate emerging technologies (e.g., Transformers, Reinforcement Learning) for integration.
- Monitor system performance and implement best practices for MLOps and model governance.
Qualifications
- Master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
- Minimum of 5 years of professional experience building and deploying production-grade machine learning systems.
- Strong proficiency in Python, C++, and frameworks such as TensorFlow, PyTorch, or Keras.
- Extensive experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Deep understanding of data structures, algorithms, and software design patterns.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.