Machine Learning Engineer
SweedFull Time
Mid-level (3 to 4 years)
Candidates should have 2-5 years of experience in data annotation operations, ML data workflows, or software/data engineering. Proficiency in Python scripting for automation and data handling (JSON, JSONL, CSV) is required. Experience with annotation tooling, AWS S3, cloud-based storage pipelines, multi-stage annotation workflows, or model-in-the-loop systems is highly preferred. Familiarity with telemetry systems, GenAI/LLM training environments, or RLHF pipelines is a bonus. Strong communication skills are necessary.
The GenAI Annotation Operations Engineer will set up, test, and maintain UI configurations for annotation tasks, and build and adapt Python-based automation scripts for annotation pipelines, data processing, logging, and telemetry. They will collaborate with researchers, engineers, PMs, and annotators to gather requirements and design workflows, owning projects end-to-end from requirement gathering through delivery of annotated datasets. Responsibilities include tracking progress, managing risks, implementing corrective actions, troubleshooting issues related to UI, pipelines, and data formatting, documenting workflows, and supporting annotation operations across varied data types with a focus on LLMs and GenAI training.
AI-powered talent recruitment solutions
Sustainable Talent is dedicated to modernizing the recruitment field, leveraging AI technology for efficient real-time recruiting, staff augmentation, and providing both full-time and contract roles. This company stands out as a bridge for talent in startups and established industry leaders, ensuring top companies are matched with the best individuals. Their commitment to cutting-edge technology and a focus on sustainable talent retention makes it an ideal workplace for those interested in the forefront of HR tech and innovative staffing solutions.