Fully remote | Complete engagement job
Founded in Palo Alto by Dr. Andrew Ng and Israel Niezen, Factored helps U.S. companies build and scale world-class AI, ML, and Data teams, powered by the top 1% of LATAM talent, with a defining purpose: To empower brilliant humans, unleash their potential, and amplify their impact in the world.
At Factored, you’ll be part of a community that values learning, ownership, and authenticity, where your growth is personal and your ideas matter. We’re transparent, curious, and collaborative. We strive for excellence, celebrate diversity, encourage curiosity, and build an environment where you can truly thrive.
As a Senior Machine Learning Engineer in Computer Vision, you will design and deliver advanced vision systems that power mission-critical applications for global and Fortune 500 companies. You’ll work across deep learning, large-scale data pipelines, and high-performance infrastructure, owning models end-to-end from experimentation to production deployment.
This role is designed for engineers who think systems-level, understand the real-world constraints of ML at scale, and can turn ambiguous visual problems into high-impact, production-ready solutions. You’ll shape architectures, guide model strategy, and bring modern vision capabilities into enterprise environments where reliability, speed, and accuracy matter.
Functional Responsibilities:
- Develop and fine-tune models for tasks like image classification, object detection, segmentation, and generative modeling using TensorFlow, PyTorch, or Keras.
- Implement techniques such as resizing, normalization, data augmentation, and feature extraction to improve model performance.
- Optimize and deploy computer vision models on cloud platforms (AWS, GCP, Azure), edge devices, and specialized hardware (GPUs, TPUs).
- Use CI/CD, model versioning, and monitoring tools to ensure reliable and scalable deployment of vision models.
- Improve model speed and performance using quantization, pruning, and hardware acceleration techniques.
Qualifications:
- +5 years of hands-on experience developing and deploying machine learning models in production environments.
- Proven experience writing production-level code, with strong proficiency in Python.
- Strong Python programming skills with proficiency in deep learning frameworks (TensorFlow, PyTorch, or Keras).
- Expertise in designing, training, and fine-tuning models for: Image classification (ResNet, EfficientNet), Object detection (Faster R-CNN, YOLO, SSD) or Image segmentation (U-Net, Mask R-CNN).
- Strong understanding of image preprocessing techniques (resizing, normalization, data augmentation).
- Experience with computer vision libraries such as OpenCV and torchvision.
- Experience with transfer learning and adapting pre-trained models.
- Ability to deploy models on cloud platforms (AWS, GCP, Azure) and specialized hardware (GPUs, TPUs).
- Familiarity with MLOps tools for automating ML pipelines.
Our Benefits:
- Ownership through equity participation.
- Annual company retreat.
- Education bonus for continuous learning.
- Company-wide winter break.
- Paid time off.
- Optional in-person events and meetups.
- Tailored career roadmaps.
- High-performance culture.
Top Skills
What We Do
Factored (backed by Andrew Ng's AI Fund and deeplearning.ai) helps leading tech companies select, upskill, and build world-class data science, machine learning and AI engineering teams much faster and more cost effectively. Our engineers have been personally vetted, educated, and mentored by some of the most talented and recognized AI educators and engineers from Silicon Valley, Stanford University and deeplearning.ai.
