Job Description
We are FutureScale Systems, a pioneering technology firm dedicated to shaping the future of artificial intelligence. We are currently recruiting a visionary Senior AI/ML Engineer to join our elite team working on Project 2026, a groundbreaking initiative aimed at redefining the boundaries of generative AI and autonomous systems.
In this role, you will be at the forefront of technological innovation, architecting scalable machine learning pipelines and deploying state-of-the-art neural networks. You will collaborate with world-class researchers and engineers to solve complex problems that have never been solved before. If you are passionate about the future of technology and want to build the infrastructure that powers the next generation of AI, we want to hear from you.
Why join us?
- Competitive compensation package and equity opportunities.
- Work on cutting-edge projects that will impact industries globally.
- Flexible remote and hybrid work options.
- Continuous learning and development budget.
Responsibilities
- Architecting Solutions: Lead the design and implementation of robust, scalable machine learning architectures for Project 2026, ensuring high performance and reliability.
- Model Development: Develop, train, and fine-tune complex deep learning models using state-of-the-art algorithms to solve real-world problems.
- Production Deployment: Deploy models to cloud environments (AWS/GCP) using containerization tools (Docker, Kubernetes) and MLOps best practices.
- Research & Innovation: Conduct cutting-edge research to identify new techniques, optimize existing models, and stay ahead of industry trends.
- Collaboration: Work closely with data scientists, software engineers, and product managers to integrate AI capabilities seamlessly into our products.
- Mentorship: Mentor junior engineers and conduct code reviews to foster a culture of technical excellence and continuous improvement.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Mathematics, Statistics, or a related technical field.
- Experience: Minimum of 5 years of professional experience in machine learning and deep learning engineering.
- Programming: Expert-level proficiency in Python (PyTorch, TensorFlow, Scikit-learn) and experience with C++ or Java is highly desirable.
- Cloud & DevOps: Strong experience deploying models on cloud platforms (AWS, GCP, Azure) and familiarity with CI/CD pipelines.
- Problem Solving: Proven track record of tackling ambiguous problems and delivering innovative solutions under tight deadlines.
- Communication: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.