ML Engineer at Celestial AI — Career Guide 2026
Role Overview
As an ML Engineer at Celestial AI, you will play a crucial role in developing and optimizing machine learning models that leverage or contribute to the company's groundbreaking photonic interconnect technology. This role involves working at the intersection of hardware and software, designing ML solutions that can fully exploit the ultra-high bandwidth and low-latency capabilities of optical interconnects to accelerate AI workloads. You will be instrumental in pushing the boundaries of what's possible in AI infrastructure and performance.
Key Responsibilities
- Develop and implement machine learning models for optimizing data flow and resource allocation in photonic interconnect systems.
- Design and evaluate ML algorithms for performance prediction, fault detection, and anomaly identification within complex hardware architectures.
- Collaborate with hardware engineers and researchers to integrate ML solutions directly into the design and operation of optical interconnects.
- Build scalable data processing pipelines for large datasets generated by hardware simulations and real-world system telemetry.
- Contribute to the research and development of novel ML techniques tailored for high-performance computing and AI accelerators.
Required Skills
- Strong programming skills in Python, with experience in C++ being a significant advantage.
- Proficiency with ML frameworks like TensorFlow or PyTorch and experience with numerical computing libraries (e.g., NumPy, SciPy).
- Solid understanding of machine learning fundamentals, including supervised, unsupervised, and reinforcement learning.
- Experience with large-scale data processing and distributed computing (e.g., Spark, Dask).
- Familiarity with hardware-software co-design, computer architecture, or high-performance computing concepts is highly desirable.
Interview Process
The interview process for an ML Engineer at Celestial AI is typically rigorous, spanning 5-6 rounds. It generally begins with a recruiter screen, followed by a technical phone screen focusing on coding and ML fundamentals. Subsequent stages include a deep dive into machine learning theory, system design (potentially involving hardware-aware ML), a behavioral interview, and an on-site (virtual) loop with various team members, including ML engineers, hardware architects, and research scientists. Expect questions on performance optimization, data-intensive ML, and distributed systems.
Salary & Compensation
ML Engineers at Celestial AI can expect a competitive salary range of $170,000 to $280,000 annually. This compensation package typically includes a strong base salary, significant equity (stock options or RSUs), and a comprehensive benefits package covering health, dental, vision, and a 401(k) plan. Given the company's innovative and high-growth nature, equity components can form a substantial part of the total compensation, reflecting the potential for significant financial upside.
Why Join Celestial AI
Joining Celestial AI offers a unique opportunity to work at the cutting edge of AI infrastructure. You'll be part of a team revolutionizing how AI models communicate and process data, directly influencing the next generation of AI supercomputers. The company provides an intellectually stimulating environment where you can solve incredibly complex problems with a tangible impact on technological advancement. This role is ideal for those passionate about hardware-accelerated AI and pushing the boundaries of performance and efficiency.
Tips for Applicants
- Highlight Hardware-Aware ML: Emphasize any experience or interest in optimizing ML for specific hardware, custom accelerators, or high-performance computing environments.
- Showcase Distributed Systems Skills: Demonstrate your ability to work with large datasets and distributed ML training/inference, as scalability is key.
- Understand Photonic Interconnect: Research Celestial AI's core technology and be prepared to discuss how ML can contribute to or benefit from optical interconnects.