TransPerfect helps organizations streamline global operations through language and AI solutions, advanced automation, and enterprise-grade technology integrations. Our GlobalLink® technology centralizes multilingual content workflows, connects with leading CMS, CRM, PIM, and marketing systems, and reduces the manual effort required to manage content across channels.

Supported by a worldwide team of experts, we deliver accuracy, cultural relevance, and exceptional service in 200+ languages. More than 6,000 organizations rely on TransPerfect to automate processes, unify global content, and reach audiences worldwide. With 150+ offices on six continents, we combine global scale with continuous innovation to help brands grow with confidence.

About the job

We are seeking a Mid-Level AI/ML Engineer to join our client’s AI team and contribute to the development of cutting-edge intelligent systems. In this role, you’ll be responsible for designing, training, and deploying machine learning models that power innovative features across devices and services. This is an exciting opportunity to work with a global technology leader in the telecommunications sector, applying your expertise to real-world applications that impact millions of users.

Responsibilities 

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  Build, train, and maintain systems based on machine learning and natural language processing.

  
  


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  Write machine learning algorithms based on transformers.

  
  


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  Conduct experiments, evaluate model performance, and suggest improvements.

  
  


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  Prepare quick scripts to automate tasks such as metric generation, file conversions, etc., when necessary.

  
  


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  Collaborate with senior engineers to implement production-ready AI solutions.

  
  

Required Qualifications 

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  Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field.

  
  


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  5+ years of experience in developing and deploying machine learning models.

  
  


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  Experience with deep learning and statistical learning in Natural Language Processing (NLP).

  
  


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  Familiarity with text processing libraries.

  
  


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  Hands-on experience with LLM models, prompting libraries, and fine-tuning.

  
  

Programming and ML Frameworks

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  Python

  
  


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  TensorFlow

  
  


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  PyTorch

  
  


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  scikit-learn

  
  


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  XGBoost / LightGBM (common in practical ML pipelines)

  
  


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  NumPy, Pandas

  
  


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  Jupyter Notebooks

  
  

Data preprocessing & feature engineering tools

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  Version Control & CI/CD

  
  


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  Git / GitHub / GitLab

  
  


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  Jenkins

  
  

Development & Experimentation Tools

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  TensorBoard

  
  


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  Weights & Biases (W&B) or Neptune.ai

  
  


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  ONNX (optional but common for deployment/optimization)

  
  

Other Useful Skills (common for telecom/edge AI)

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  Experience with edge AI model optimization (TensorRT, CoreML, TFLite)