Compensation
Salary undisclosedDescription
About Plix
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.
Responsibilities
- 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
Requirements
- 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
Preferred Qualifications
- 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
Stack
PythonPyTorchGPULLMsComputer VisionSpeech RecognitionMachine LearningTensorFlowMultimodal
- Posted
- Jan 24, 2025
- Last seen
- Jul 4, 2026
- First seen
- Jul 4, 2026
