Staff Applied Scientist

Job Summary

CPTO is looking for an Applied Scientist who is passionate about bridging the gap between AI research and large-scale production systems. In this role, you will not just apply off-the-shelf models; you will design, build, and iterate on novel algorithmic solutions to complex, ambiguous business problems.

Job Requirements

• Familiarity with the design and development of system software.
• 12+ years of hands-on experience in coding of AI/ML.
• Knowledge of Unix/Linux System Programming and Multithreaded programming.
• Expertise in algorithms, data structures, and multi-threaded programming is essential.
• Commitment to sound software engineering practices and a passion for quality.
• Proven track record of meeting tight deadlines without sacrificing quality.
• Strong communication skills, both written and oral, targeted at a wide variety of internal and external audiences.
• Ability to understand customer deployment scenarios and experience in collaborating with peer teams outside of engineering.
• Familiarity with database technologies such as NoSQL, Prometheus and datalake.
• Hands-on experience with code conversion tools like Git.
• Knowledge of software deployment - Docker/Kubernetes

Key Responsibilities:

Research & Design: Formulate complex business problems into formal mathematical frameworks
Design, experiment with, and evaluate advanced ML models, Deep Learning architectures, and statistical methods

Prototyping to Production: Write clean, maintainable, and scalable code
Own the end-to-end lifecycle of ML models, from data ingestion and training to deployment and post-launch monitoring

Scale & Optimize: Optimize model performance, latency, and resource utilization for high-throughput, low-latency production systems (e.g., distributing training, quantization, or optimizing inference graphs)

Technical Leadership: Stay at the forefront of AI research (LLMs, Retrieval-Augmented Generation (RAG), vector intelligence, multi-modal systems).
Mentor junior engineers and scientists, and foster a data-driven engineering

Education

• IC - Typically requires a minimum Bachelor/Master of Engineering in Computer Science; or equivalent experience.

• 12–15 years of hands-on experience in Data Science and related analytics disciplines.