Machine Learning Engineer — Multilingual Data
Remote (world)
- Pay
- Pay not listed
- Work setting
Remote stated — work setting source
Listed location: Remote (world)
Read the full posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Research — team source
Department: Research
From the employer’s posting
What you’ll work on
Full postingDesign, build and maintain large-scale multilingual datasets across high- and low-resource languages
Develop pipelines for collection, cleaning, normalization, deduplication and labeling
Implement quality filters using statistical, heuristic, and model-based methods
Analyze dataset bias, coverage gaps, and failure modes across regions and scripts
Support training, fine-tuning, and distillation workflows with multilingual data
From the employer’s posting
Design, build, and maintain large-scale multilingual datasets across high- and low-resource languages
Develop data pipelines for collection, cleaning, normalization, deduplication, and labeling
Implement quality filters using statistical, heuristic, and model-based methods
Analyze dataset bias, coverage gaps, and failure modes across regions and scripts
Support training, fine-tuning, and distillation workflows with high-quality multilingual data
Tools in this posting
- Python
- Spark
Source — Tool mentions in context
- Solid understanding of NLP fundamentals (tokenization, embeddings, language modeling) - Experience building scalable data pipelines (Python, Spark, Ray, or similar) - Familiarity with Unicode, scripts, tokenization challenges, and language-specific quirks
Posting record
Report an errorOpen 4 monthsWe first saw this listing 142 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 2, 2026 · 142 days ago
- Recorded sightings
- 80
- Last seen by us
- Oct 21, 2026
- Employer says posted
- Jan 22, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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Job description
We’re looking for a Machine Learning Engineer to own and scale our multilingual data pipeline—from sourcing and curation to evaluation and continuous improvement. You’ll work closely with researchers and infra engineers to ensure our models perform robustly across languages, scripts, and cultural contexts.
This role sits at the intersection of data, research, and production ML and is ideal for someone who cares deeply about data quality, linguistic diversity, and model generalization beyond English.
What You’ll Do
Design, build, and maintain large-scale multilingual datasets across high- and low-resource languages
Develop data pipelines for collection, cleaning, normalization, deduplication, and labeling
Implement quality filters using statistical, heuristic, and model-based methods
Work with researchers to define language coverage, benchmarks, and evaluation metrics
Analyze dataset bias, coverage gaps, and failure modes across regions and scripts
Support training, fine-tuning, and distillation workflows with high-quality multilingual data
Continuously iterate on datasets based on model performance and real-world usage
What We’re Looking For
3+ years of experience as an ML Engineer, Applied Scientist, or similar role
Strong experience working with multilingual or non-English datasets
Solid understanding of NLP fundamentals (tokenization, embeddings, language modeling)
Experience building scalable data pipelines (Python, Spark, Ray, or similar)
Familiarity with Unicode, scripts, tokenization challenges, and language-specific quirks
Comfort collaborating with researchers and translating research needs into production systems
Nice to Have
Experience with low-resource languages or multilingual benchmarks (e.g. FLORES, XTREME)
Exposure to LLM training, fine-tuning, or distillation
Linguistics background or experience working with native language experts
Contributions to open-source datasets or ML tooling
Experience with data quality evaluation at scale
Why Join
Real ownership over a core differentiator of the product
Work on models used globally, not just in English-speaking markets
Small, high-caliber team with deep ML and systems experience
Competitive compensation + meaningful equity at Series A stage
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Remote (world)
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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