Machine Learning Engineer
emagineSweden6 days ago
Full-timeEngineering, Information Technology
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Machine Learning Engineer (focused on QUAIL + MAP integration)
Focus on these products:
QUAIL. Building and applying ML models for language evaluation, quality scoring, and multimodal translation workflows.
MAP (Multilingual AI Platform). It is a platform to translate content at scale using AI. MAP is designed to help efficiently localize and internationalize content for users in different languages and regions.
Core Skills
Expertise in NLP and LLMs (prompting, fine-tuning, evaluation). QUAIL depends on LLM-as-a-judge scoring frameworks.
Experience with quality evaluation frameworks: (we have the rubrics designed, but it would be good if they have experience designing rubrics for language formatting; building evaluation APIs)
Experience with data engineering for ML: collecting, cleaning, and structuring multilingual corpora for benchmarking.
Comfort with MLOps: deploying models into production, monitoring drift, ensuring cost-efficiency.
Nice-to-Haves
Familiarity with MT evaluation: BLEU, COMET, MQM, or newer LLM-based scoring methods.
Applied work in speech and multimodal ML: transcription (STT), speech isolation, diarization, TTS, dubbing.
Ability to design scalable evaluation pipelines: run automated evaluations at segment/file/content level across multiple languages.
Experience with human-in-the-loop evaluation workflows (sampling, quality control).
Knowledge of cultural/linguistic nuances in translation (since QUAIL will measure “fit for purpose” quality).
Job Posting Start Date: 2025-12-15
Job Posting End Date: 2026-06-14
Focus on these products:
QUAIL. Building and applying ML models for language evaluation, quality scoring, and multimodal translation workflows.
MAP (Multilingual AI Platform). It is a platform to translate content at scale using AI. MAP is designed to help efficiently localize and internationalize content for users in different languages and regions.
Core Skills
Expertise in NLP and LLMs (prompting, fine-tuning, evaluation). QUAIL depends on LLM-as-a-judge scoring frameworks.
Experience with quality evaluation frameworks: (we have the rubrics designed, but it would be good if they have experience designing rubrics for language formatting; building evaluation APIs)
Experience with data engineering for ML: collecting, cleaning, and structuring multilingual corpora for benchmarking.
Comfort with MLOps: deploying models into production, monitoring drift, ensuring cost-efficiency.
Nice-to-Haves
Familiarity with MT evaluation: BLEU, COMET, MQM, or newer LLM-based scoring methods.
Applied work in speech and multimodal ML: transcription (STT), speech isolation, diarization, TTS, dubbing.
Ability to design scalable evaluation pipelines: run automated evaluations at segment/file/content level across multiple languages.
Experience with human-in-the-loop evaluation workflows (sampling, quality control).
Knowledge of cultural/linguistic nuances in translation (since QUAIL will measure “fit for purpose” quality).
Job Posting Start Date: 2025-12-15
Job Posting End Date: 2026-06-14
Key Skills
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