Machine Learning Engineer

Overview

On Site
$40,000 - $60,000
Full Time

Skills

Artificial Intelligence
Computational Linguistics
Cloud Computing
Computer Science
Collaboration
Machine Learning Operations (ML Ops)
Large Language Models (LLMs)
Natural Language Processing
Machine Learning (ML)
Multilingual
Prompt Engineering
Language Models
Google Cloud Platform

Job Details

We are seeking a highly skilled Machine Learning Engineer with a strong background in Natural Language Processing (NLP) and language-focused ML models. In this role, you will be responsible for designing, developing, and deploying ML models that understand and generate human language, power intelligent applications, and solve complex language-based problems.

Key Responsibilities:

  • Develop and fine-tune NLP models for tasks such as text classification, information extraction, summarization, question answering, and language generation.

  • Build and maintain end-to-end ML pipelines from data collection and preprocessing to training and deployment.

  • Work with large-scale language datasets (structured and unstructured) and apply statistical and deep learning methods.

  • Implement and optimize transformer-based models (e.g., BERT, GPT, T5, LLaMA).

  • Collaborate with product managers, data scientists, and engineers to integrate models into production systems.

  • Research and stay up to date with the latest advancements in NLP and machine learning.

  • Conduct error analysis and model evaluation to continuously improve model performance.

  • Write clean, modular, and well-documented code.

Required Qualifications:

  • Bachelor s or Master s degree in Computer Science, Artificial Intelligence, Machine Learning, Linguistics, or a related field.

  • 2+ years of hands-on experience in developing and deploying NLP or language-based ML models.

  • Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Hugging Face Transformers.

  • Strong knowledge of NLP techniques including embeddings, attention mechanisms, tokenization, and language modeling.

  • Experience with libraries like spaCy, NLTK, or Gensim.

  • Solid understanding of model evaluation metrics for NLP (e.g., BLEU, ROUGE, F1-score, perplexity).

  • Familiarity with RESTful APIs and deploying ML models in production environments.

Preferred Qualifications:

  • Experience with multilingual NLP or low-resource languages.

  • Familiarity with prompt engineering and large language models (LLMs).

  • Background in computational linguistics or linguistics-driven AI systems.

  • Experience with cloud platforms (AWS, Google Cloud Platform, Azure) and MLOps tools.

  • Contributions to open-source NLP/ML projects

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

About Shrinq Consulting Group INC