Member of Technical Staff - Machine Learning at Plix (San Mateo, CA)Member of Technical Staff - Machine Learning

Plix is a seed-stage startup with Stanford roots, supported by Samsara, Verkada, and Sequoia Capital. We are building the world’s first intelligent body cameras to provide real-time situational alerts to improve safety, security, and operational efficiency.

Position Overview As a Founding Member of our Technical Staff, you will play a pivotal role in shaping the architecture, implementation, and deployment of our AI-driven vision. You’ll lead efforts to deploy and fine-tune state-of-the-art machine learning models and computer vision pipelines, build robust ML infrastructure, and ensure we remain at the forefront of multimodal AI advancements. We value quick experimentation, collaborative problem-solving, and the ability to transform vision into product. This role is ideal for someone passionate about mentoring and fostering a growth mindset in the early stages of Plix’s journey.

• Deploy machine learning and computer vision models on cloud infrastructure and fine-tune for performance
• Design scalable infrastructure for model versioning, monitoring, and automated updates to ensure reliability and performance
• Analyze data, refine prompts, and improve model accuracy for video and image processing tasks
• Research the latest multimodal and computer vision advancements to integrate into our workflows
• Foster a collaborative engineering culture and help to define best practices

• Strong programming skills and proficiency in Python
• Experience with libraries such as OpenCV, and frameworks like TensorFlow or PyTorch for vision-related tasks
• Experience deploying and optimizing pre-trained machine learning and computer vision models
• Video Analysis: Experience in video pre-processing, object detection, activity recognition, and other computer vision techniques
• Collaboration & Communication: Strong communication skills with the ability to mentor, foster collaboration, and translate vision into practical solutions

• Experience working with or deploying video and/or multimodal large language models (LLMs) for tasks such as captioning, summarization, or question answering
• Experience working with or deploying transcription models for video or audio data (e.g., Whisper, Speech-to-Text APIs)
• Knowledge of deploying and managing GPU-backed systems for large-scale ML and computer vision workloads
• Interest or experience in management roles, with a focus on mentoring and team building