FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and fine-tuning computer vision models, particularly vision-language models, for real-time industrial applications. Proficient in optimizing model performance and reliability in production environments using cloud and edge technologies.
Highest-signal resume keywords
Computer Vision Model DevelopmentFine-Tuning Vision-Language ModelsPyTorch and Multi-GPU TrainingProduction Pipeline ExperienceDocker and AWS Proficiency
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Computer VisionDeep LearningFine-Tuning VLMsPython ProgrammingModel OptimizationQuantizationDistillationPerson DetectionTransformer-Based DetectorsTemporal Grounding
Soft Skills
CollaborationPragmatic Focus
Tools & Technologies
PyTorchDockerAWSJetsonTensorRT
Industry Keywords
Industrial AutomationVideo UnderstandingReal-Time SystemsMultimodal LearningFactory Video
Tech Stack
Tools & technologiesAWSCloudDockerPythonPyTorch
About the role
Key responsibilities & impact- Own the video models at the core of Almetra's AI-powered computer vision product
- Improve the computer vision pipeline end to end, from person and hand tracking to action recognition with VLMs
- Fine-tune and evaluate vision-language models on real factory video, especially visually similar steps
- Run models reliably on video in the cloud and on edge devices in factories
- Implement checks that catch weak model results early
- Improve model speed and cost through distillation, quantization and smaller backbones
- Help shape Almetra's approach to video understanding
- Bridge research and production by turning computer vision models into robust, real-time systems for intelligent industrial automation
- Collaborate with the Head of VLM, ML team and platform engineers
Requirements
What you’ll need- Experience building computer vision and deep learning models for video, ideally used by real users
- Hands-on experience fine-tuning VLMs or large video models, such as InternVL or Qwen-VL
- Strong PyTorch and multi-GPU training skills
- Clean, reproducible Python
- Experience running models in production pipelines in the cloud and/or on edge devices
- Experience with Docker, AWS, Jetson or similar
- Pragmatic focus on reliable production performance
- Nice to have: person detection and tracking in crowded scenes
- Nice to have: transformer-based detectors such as DETR family or Grounding DINO
- Nice to have: TensorRT, quantization and inference optimization for edge
- Nice to have: temporal grounding or video captioning
- Nice to have: publications on video or multimodal learning
- Nice to have: industrial, retail or other real-world camera settings
Benefits
Comp & perks- Employee Share Options Program for all permanent employees
- Urban Sports club
- Quarterly team retreats
- Hands-on experience in an AI-first software company
- Supportive and inclusive culture
- Flexible working hours
- Open 360° feedback
- Network with professionals and leaders in the field
- Only full-time, permanent roles are eligible for stock options