onsite
Senior Engineer, Machine Learning
Senior Engineer, Machine Learning
As a Senior Machine Learning Engineer, you will design, develop, and optimize ML models for NLP, generative AI, and LLM applications. You will be responsible for building and deploying AI-powered solutions at scale, automating complex workflows, and maintaining end-to-end ML pipelines using scalable, serverless, and cloud-native architectures.
About the role
Job Description
- Design, develop, and optimise machine learning models for natural language processing (NLP), generative AI, and large language model (LLM) applications.
- Build and deploy AI-powered solutions at scale, automating complex workflows and extracting actionable insights from structured and unstructured text data.
- Develop and maintain end-to-end ML pipelines for data preprocessing, feature engineering, model training, evaluation, and deployment, using scalable, serverless, and cloud-native architectures.
- Architect production-ready ML systems that follow MLOps best practices, ensuring reliability, scalability, and cost-efficiency through auto-scaling and fault isolation features.
- Build robust data pipelines for processing and integrating enterprise text data from multiple sources.
- Champion privacy-first and security-first approaches in all ML workflows, ensuring compliance with enterprise data protection standards.
Successful Candidate Requirements
- 8+ years of experience in machine learning, AI, or deep learning, with hands-on expertise in NLP, generative AI, and LLMs.
- Proficiency in transformer-based and generative AI architectures with experience deploying models at scale.
- Strong programming skills in Python (preferred).
- Experience with ML frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers.
- Proven track record in building and deploying ML solutions in cloud and serverless environments (AWS, GCP, Azure), with experience in cloud-native AI services.
- Familiarity with containerisation (Docker, Kubernetes), orchestration, and automated model training, evaluation, and monitoring pipelines.