Job Description
The Opportunity:
We are seeking a visionary AI Infrastructure Engineer to architect the neural backbone of our next-generation generative intelligence platform. In 2026, the definition of scalability is evolving. You will be at the forefront of deploying autonomous compute clusters and optimizing latency for real-time AI inference. If you are passionate about building systems that think, this is your stage.
Why Join Us?
• Work with a team of world-class researchers and engineers.
• Access to cutting-edge quantum-ready hardware prototypes.
• Competitive equity package and remote-first flexibility.
• Shape the architecture of tomorrow.
What You'll Do:
Architect and maintain high-availability, fault-tolerant ML pipelines designed for the demands of 2026 and beyond. You will bridge the gap between theoretical AI models and production-grade infrastructure, ensuring our systems are secure, efficient, and scalable.
Responsibilities
- Design and implement scalable Kubernetes-based pipelines for distributed machine learning workloads.
- Optimize model inference latency and throughput using edge computing and serverless architectures.
- Collaborate with Data Science teams to automate model deployment (MLOps) and CI/CD workflows.
- Implement robust security protocols for data privacy and AI model protection.
- Monitor system performance using advanced observability tools to ensure 99.99% uptime.
- Research and prototype emerging hardware acceleration technologies (e.g., NPUs, TPUs).
Qualifications
- 7+ years of experience in Software Engineering or DevOps, with 3+ years specifically in Machine Learning Infrastructure.
- Deep proficiency in Python, Go, or Rust.
- Expert knowledge of containerization technologies (Docker, Kubernetes) and cloud platforms (AWS, GCP, or Azure).
- Strong understanding of neural network architectures and their computational requirements.
- Experience with distributed systems, message queues (Kafka, RabbitMQ), and data streaming.
- Excellent problem-solving skills and the ability to thrive in a fast-paced, ambiguous environment.