Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
Role Overview
We're looking for a Machine Learning / Computer Vision Data Labeler to support customers' onboarding and build high-quality training datasets for our computer vision products used in manufacturing environments. This role sits at the intersection of ML data operations and light product/customer work—you'll help us understand what customers do on the factory floor, collect and analyze representative sample data from each station, and translate real-world processes into clear labeling instructions and reliable datasets.
This is not a super-senior role, but it does require strong ownership, attention to detail, and comfort working with highly confidential customer data.
Duration: 3-6 months with possibility of extension
Commitment: Full-time
Model: EOR
Location: 100% Remote -
Interview Process: Intro Call + 2 Client Interviews
Key Responsibilities
Role Overview
We're looking for a Machine Learning / Computer Vision Data Labeler to support customers' onboarding and build high-quality training datasets for our computer vision products used in manufacturing environments. This role sits at the intersection of ML data operations and light product/customer work—you'll help us understand what customers do on the factory floor, collect and analyze representative sample data from each station, and translate real-world processes into clear labeling instructions and reliable datasets.
This is not a super-senior role, but it does require strong ownership, attention to detail, and comfort working with highly confidential customer data.
Duration: 3-6 months with possibility of extension
Commitment: Full-time
Model: EOR
Location: 100% Remote -
Interview Process: Intro Call + 2 Client Interviews
Key Responsibilities
- Coordinate and execute sample data capture across all manufacturing stations, ensuring coverage of real-world variation
- Work with our on-site implementation team to validate camera setup outputs (camera position, field of view, recording settings, connectivity, sample clips/images)
- Organize, clean, and curate datasets (images/video), including selecting representative samples, filtering unusable footage, and documenting capture conditions
- Perform data labeling/annotation for computer vision tasks (e.g., classification, object detection, segmentation, defect tagging, action/process step labeling—depending on the use case)
- Create and maintain labeling taxonomies and annotation guidelines that are consistent, scalable, and easy for others to follow
- Run quality checks (spot checks, consistency reviews, edge-case handling) and partner with ML/Engineering to continuously improve label quality
- Conduct lightweight exploratory analysis on incoming datasets (e.g., distributions, coverage gaps, common failure modes, ambiguity hot-spots)
- Flag data issues early (missing stations, misaligned camera views, insufficient examples, inconsistent definitions) and propose fixes
- Provide structured feedback to ML and product teams: what data we have, what we're missing, and what will improve model performance
- Support customer onboarding by learning what the client does, mapping their workflow/stations, and translating their needs into data/labeling requirements
- Communicate clearly with internal stakeholders and occasionally with customers to align on labeling definitions, success criteria, timelines, and data handling expectations
- Document processes, station definitions, and dataset decisions so teams can move fast and stay aligned
- Work with sensitive/secret customer manufacturing data and follow strict security policies (access control, secure transfer/storage, need-to-know practices, and customer-specific handling requirements)
- 1-4 years of experience in a role involving data labeling/annotation, ML data operations, computer vision datasets
- Working knowledge of computer vision fundamentals (classification vs detection vs segmentation; what labels are used for; why consistency matters)
- Experience with labeling tools such as CVAT, Labelbox, V7, Supervisely, or similar (or the ability to learn quickly)
- Comfort working with data formats/workflows (e.g., CSV/JSON annotations, COCO-style formats, dataset folders, basic versioning concepts)
- Strong written and verbal communication skills; able to explain labeling decisions and customer workflows clearly
- Professional maturity and discretion—ability to handle highly confidential customer data
- German language ok, strong communication in English preferred
- Exposure to manufacturing environments (industrial processes, station-based workflows, quality inspection)
- Familiarity with camera systems / video capture pipelines (e.g., frame rate, resolution trade-offs, lighting impacts, field of view)
- Work in a fully remote environment
- Opportunity to work on cutting-edge AI projects with leading LLM companies