Senior Machine Learning Engineer

Machine Learning EngineerMachine Learning EngineerFull TimeRemoteSeniorTeam 166Since 2019Company Site

Location

Worldwide

Posted

23 days ago

Salary

0

Seniority

Senior

No structured requirement data.

Job Description

Senior Machine Learning Engineer

Factored

Role Description 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) - 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. 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.

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Senior AIOps Engineer I

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The exclusive club for international entrepreneurs

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