Staff Machine Learning Engineer

• Lead the development and optimization of advanced machine learning models.
• Oversee the preprocessing and analysis of large datasets.
• Deploy and maintain ML solutions in production environments.
• Collaborate with cross-functional teams to integrate ML models into products and services.
• Monitor and evaluate the performance of deployed models, making necessary adjustments.

Minimum Qualifications:

• 5+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
• Extensive experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.

Additional Responsibilities & Preferred Qualifications:

• Experience owning end-to-end ML model lifecycles, including training, evaluation, deployment, monitoring, and retraining in production environments.
• Strong hands-on experience with MLOps best practices and platforms, such as experiment tracking, model versioning, and automated training/deployment pipelines (e.g., MLflow, Kubeflow, Airflow, SageMaker, Vertex AI).
• Experience building and scaling LLM- and GenAI-based systems, including fine-tuning, inference optimisation, prompt management, and retrieval-augmented generation (RAG) pipelines.
• Proven ability to design scalable, reliable, and cost-efficient ML inference systems, with familiarity in containerisation, orchestration, and infrastructure-as-code (Docker, Kubernetes, Terraform).
• Experience with large-scale data processing and distributed systems (e.g., Spark) and integrating ML solutions into complex production architectures.
• Understanding of Responsible AI practices (explainability, fairness, robustness, compliance) and demonstrated technical leadership or mentorship influencing ML architecture and standards.