Member of Technical Staff - Infrastructure
Location: San Mateo
Department: Engineering
Location Type: IN_OFFICE
Employment Type: FULL_TIME
- Iterate with our founding team on the design and implementation of development processes for the SaaS and Machine Learning infrastructure solution, and subsequent iterations of the software
- Debug, improve, and optimize Plix’s software and infrastructure to enable a reliable, performant, and scalable software ecosystem
- Help to define and champion engineering standards and processes
- Stay up-to-date on the latest technologies and AI research and migrate to the latest infrastructure types when needed
- Mentor and manage junior engineers as we grow to create a collaborative, inclusive environment
- Exceptional programming skills in Python, comfortable working with Kubernetes, Docker, and other related frameworks
- Experience working with cloud computing offerings like AWS and GCP, specifically with services like GCS/S3, GCE/EC2, GKE, Container Registries, etc.
- Experience with SQL and no-SQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra) and web servers (e.g., Apache, Nginx)
- Successful track record or demonstration of aptitude with deployment of distributed systems and infrastructure
- Capable of working with a high level of autonomy and responsibility in a rapidly changing environment with dynamic objectives
- Experience building a zero to one SaaS backend infrastructure solution
- Excellent communication skills and ability to turn vision into running software
- Demonstrated record of working hard, being a trustworthy teammate, and holding yourself and others to high standards
- A passion for collaboration and working with teams
- Familiarity with interfacing with secure/private customer data, especially video
- Experience working with computer vision libraries like OpenCV and FFmpeg
- Experience with deployment of GPU backend systems and infrastructure
- Experience deploying and managing TensorFlow or Torch models at scale
- Advanced machine learning knowledge for training and building new models, especially related to large language models (LLMs)
- Prior management experience and/or interest to grow into a leadership role
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