Job Description
We are building the architecture of tomorrow. Chronos 2026 is a cutting-edge research lab dedicated to developing autonomous cognitive systems for the next decade. We are seeking a visionary Senior AI Infrastructure Engineer to lead our high-performance computing initiatives. If you thrive in an environment where theoretical breakthroughs meet practical scalability, we want to meet you.
Join a team that is redefining the boundaries of Generative AI, Neural Networks, and Edge Computing. You will have the autonomy to architect systems that power our global network, ensuring speed, security, and scalability.
Why Join Chronos 2026?
- Pioneering Work: Be at the forefront of the AI revolution, working on projects that will shape the year 2026 and beyond.
- Top-Tier Compensation: Competitive salary plus equity in a high-growth unicorn.
- Unlimited PTO: We trust our experts to manage their time.
- Remote-First Culture: Work from anywhere in the US with state-of-the-art equipment provided.
Responsibilities
- Design, build, and maintain scalable distributed AI training pipelines using cloud-native technologies (AWS, GCP, or Azure).
- Optimize deep learning models for inference latency and throughput on heterogeneous hardware (GPUs/TPUs).
- Collaborate with data scientists and researchers to translate academic models into production-grade software.
- Implement robust monitoring, logging, and alerting systems to ensure system reliability and observability.
- Drive architectural decisions that balance technical debt reduction with feature velocity.
- Contribute to open-source projects and internal tooling to improve team productivity.
Qualifications
- 7+ years of experience in software engineering, with a focus on Machine Learning Infrastructure.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Strong understanding of distributed systems, message queues, and containerization (Docker, Kubernetes).
- Experience with MLOps tools such as MLflow, Kubeflow, or Sagemaker.
- Excellent problem-solving skills and ability to thrive in a fast-paced, ambiguous environment.
- Experience with large-scale data processing (Spark, Flink, or Ray).