Senior Software Engineer - Machine Learning

Summary

Join Mitratech, a team of technocrats building world-class products for Legal, Risk, Compliance, and HR functions. We are a globally dispersed team with a diverse and inclusive culture. We offer opportunities for individual excellence and learning. We are seeking a highly skilled Senior Software Engineer specializing in Machine Learning and Natural Language Processing (NLP). This role involves developing and deploying machine learning models, ensuring data quality, and staying current with industry advancements. The ideal candidate will have a Master's degree in a relevant field and proven experience in model development and deployment.

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
• 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

Preferred Qualifications

• 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