Remote Senior Software Engineer, Machine Learning (NLP Focus)

Summary

Join our global team and see why it's so special to be a part of Mitratech! We are seeking a highly skilled Senior Software Engineer specializing in Machine Learning, with a focus on Natural Language Processing (NLP), to join our dynamic team.

Requirements

• ML Experimentation: A solid understanding of setting up machine learning experiments, communicating results, and managing stakeholder expectations
• Data Quality Management: Experience in verifying and ensuring data quality through comprehensive data cleaning processes
• Model Development: Proven experience in training custom models with available data and conducting rapid experimentation for proof-of-concept projects
• Technical Proficiency: Hands-on knowledge of at least one major machine learning framework, with a preference for PyTorch
• MLOps Knowledge: Familiarity with MLOps practices, including model deployment and offering machine learning models as a service, is highly desirable
• LLMs and Third-Party Services: Understanding of Large Language Models (LLMs) and third-party services, with the ability to evaluate the benefits of using these over in-house model development
• Education: A Master’s degree in Machine Learning, Computer Science with a preference for specialization in the NLP domain

Responsibilities

• Model Development: Understand business objectives and develop machine learning models to achieve these goals, complete with performance tracking metrics
• Data Management: Ensure data quality through rigorous verification and cleaning processes. Explore and visualize data to understand it thoroughly, identifying any distribution differences that could impact model performance in real-world applications
• Research and Data Acquisition: Proactively find and utilize available datasets online for model training purposes
• Strategy and Validation: Define and implement robust validation strategies for model evaluation
• Model Training and Tuning: Take charge of training models and fine-tuning hyperparameters to optimize performance
• Model Deployment: Skillfully deploy models to production environments, ensuring seamless integration and operational efficiency
• Industry Awareness: Maintain an up-to-date understanding of the latest developments in the machine learning field, with a keen eye on advancements in NLP