Data Scientist Machine Learning Engineer

We are looking for a Data Scientist / Machine Learning Engineer to support the development and validation of a multilingual machine learning pipeline focused on classifying email traffic and customer-reported samples.

The ideal candidate will combine strong data preparation and engineering skills with hands-on experience in machine learning, supervised classification, model training, and evaluation

. Experience working with NLP and multilingual datasets is highly desirable.

Location: Remote – LATAM

Working Hours: 8:00 AM – 5:00 PM Romania Time (UTC+3)=Colombia: 12:00 AM – 9:00 AM COT

Candidates in other countries should consider the equivalent local time.

Key Responsibilities

• Collect and prepare raw email traffic and customer-reported samples across multiple languages.

• Normalize and translate multilingual datasets into a common format suitable for model training.

• Build reproducible data preparation and machine learning pipelines.

• Train and fine-tune machine learning classifiers using labeled datasets.

• Conduct experimentation and optimize model performance.

• Evaluate models using holdout datasets and detailed performance analysis.

• Analyze false positives and false negatives and identify opportunities for improvement.

• Perform language-specific quality checks and overall model validation.

• Document project methodology, progress, experiments, and results throughout the engagement.

• Work closely with the client to deliver a validated model ready for production deployment.

Requirements

• Strong experience in Data Science and/or Machine Learning Engineering

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• Strong data engineering and data preparation experience, particularly with collection, normalization, and transformation of datasets.

• Hands-on experience with machine learning model training, tuning, and experimentation

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• Experience evaluating classifier performance and conducting false-positive/false-negative analysis

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• Experience building reproducible ML workflows and pipelines.

• Ability to clearly document technical methodology, progress, and results.

• Strong analytical and problem-solving skills.

Nice to Have

• Experience with NLP (Natural Language Processing)

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• Experience working with multilingual datasets

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• Experience with supervised classification workflows.

• Experience working with email data or similar text-based datasets.