Job Description
FutureScale Inc. is at the forefront of the AI revolution, developing next-generation neural networks that power the world's most advanced data platforms. We are seeking a visionary Senior AI/ML Engineer to join our elite team in Seattle and help define our roadmap for 2026 and beyond.
In this role, you will be responsible for architecting scalable machine learning systems, optimizing deep learning models for production environments, and leading the technical strategy for our core AI infrastructure. You will collaborate with world-class researchers and product engineers to build intelligent solutions that solve complex, real-world problems.
If you are passionate about pushing the boundaries of artificial intelligence and want to work in a high-impact environment, we want to hear from you.
Responsibilities
- Architect and Deploy: Design, implement, and maintain scalable machine learning pipelines and production-grade AI models using Python, TensorFlow, and PyTorch.
- Model Optimization: Optimize existing models for latency, throughput, and accuracy to ensure high performance in real-time applications.
- Data Engineering: Collaborate with data scientists and engineers to preprocess large datasets, handle feature engineering, and ensure data quality and integrity.
- MLOps: Implement and manage CI/CD pipelines for machine learning, automating model training, validation, and deployment processes.
- Research & Innovation: Stay abreast of the latest advancements in AI research (e.g., Transformers, GNNs) and evaluate their applicability to our product suite.
- Technical Leadership: Mentor junior engineers, conduct code reviews, and establish best practices for AI development within the organization.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related technical field.
- Experience: 5+ years of professional experience in software engineering, machine learning, or artificial intelligence.
- Programming: Strong proficiency in Python and experience with deep learning frameworks (TensorFlow, PyTorch, Keras).
- Systems: Solid understanding of distributed systems, cloud computing (AWS/GCP/Azure), and containerization technologies (Docker, Kubernetes).
- Mathematics: Strong background in linear algebra, calculus, and probability/statistics.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.