Design, develop, and deploy machine learning models for classification, prediction, anomaly detection, and intelligent automation.
Build and maintain scalable data pipelines for model training, evaluation, and real time /batch inference.
Optimize ML models and pipelines for performance, scalability, reliability, and cost efficiency.
Collaborate with cross functional teams to integrate ML solutions into core platform features and services.
Conduct model experimentation, evaluation, and iteration using quantitative metrics and A/B testing as needed.
Implement model observability, monitoring, and drift detection to ensure production reliability.
Stay current with advancements in machine learning, AI, and LLM technologies, and apply them to product use cases.

5+ years of experience in machine learning engineering or data science roles
Strong proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow, Scikit learn)
Experience building and operating data processing workflows (batch or streaming) and working with cloud platforms (AWS, Azure, or GCP)
Solid understanding of machine learning algorithms, statistics, and model evaluation techniques
Familiarity with containerization and orchestration technologies (Docker, Kubernetes)
Hands on experience with Large Language Models (LLMs), including fine tuning, prompt engineering, and deployment
Knowledge of text embedding models, and vector databases for Retrieval Augmented Generation (RAG) systems
Strong problem-solving skills and the ability to collaborate effectively in Agile teams
Highly motivated, adaptable, and eager to learn new technologies.

Staff Machine Learning Engineer

Key skills