Machine Learning Engineer

We're looking for a Machine Learning Engineer to help us build cutting-edge AI solutions for education and research communities. You'll work at the intersection of machine learning and language, developing and deploying models that understand and generate content with cultural nuance and linguistic accuracy across various languages. This role requires deep technical expertise in ML systems.

You'll join a high-impact, compact team responsible for designing, training, and deploying machine learning models that serve diverse educational and research use cases. You'll work directly with researchers, data engineers, and product teams to bring AI capabilities from research to production.

Responsibilities

• Design, develop, and deploy machine learning models with strong performance on language tasks, including NLP, understanding, and generation.
• Fine-tune and adapt large language models, ensuring cultural and linguistic appropriateness for target regions.
• Build and maintain ML pipelines for training, evaluation, and deployment of models capable of handling diverse languages.
• Develop evaluation frameworks and benchmarks to measure model performance on complex linguistic tasks.
• Collaborate with research teams to implement state-of-the-art ML techniques and optimise model architectures.
• Work with data engineers to define data requirements and improve data quality for language model development.
• Implement monitoring and observability solutions to track model performance and data drift in production.
• Contribute to the development of multilingual and cross-lingual capabilities.
• Document model architectures, training procedures, and deployment processes.
  
  

Requirements

• 3+ years of experience in machine learning engineering, with demonstrated expertise in NLP and language models.
• Strong experience training, fine-tuning, and deploying large language models (LLMs) in production environments.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers, etc. ).
• Experience with distributed training, model optimisation, and inference at scale.
• Familiarity with cloud infrastructure (AWS, GCP, or Azure) and ML deployment tools (Docker, Kubernetes, model serving frameworks).
• Strong understanding of ML best practices, including experiment tracking, versioning, and reproducibility.
• Experience with evaluation methodologies and metrics for language models.
• Proactive about documentation, code quality, and collaborative development practices.
• Excellent communication skills in English.
  
  

Preferred Qualifications

• Experience building ML systems for education or research applications.
• Experience with multilingual and cross-lingual model development.
• Background in computational linguistics or related fields.
• Publications or contributions to ML/NLP open-source projects.
  
  

This job was posted by Chaitanya Degala from Incept Labs.