Senior Machine Learning Engineer
Core
Own the entire lifecycle of MLOps and LLMOps, developing LLM-based solutions, agents, and multi-agent systems for a media technology team.
Role type
Senior Machine Learning Engineer (LLMOps)
Builds
LLM-based solutions, semantic layers, agent systems, and scalable ML pipelines
Domain
Media technology / Large Language Models
Deliverable
production ML models
Required skills
LLMOps, LLM fine-tuning, prompt engineering, agent and multi-agent systems development, MLOps pipelines, cloud data warehousing, Python, SQL, TensorFlow, PyTorch, MLflow, Airflow
Preferred skills
Snowflake, AWS/GCP/Azure, Spark, Dask, Master's degree or Ph.D.
Responsibilities
Develop and manage LLM-based solutions including semantic layer development and agent systems; Own end-to-end ML model development, optimization, and deployment; Ensure scalability, efficiency, and reliability of ML pipelines; Design and implement robust model monitoring and retraining strategies; Optimize model inference and performance for production environments; Collaborate with data scientists, engineers, and product teams to integrate ML solutions; Improve experimentation frameworks, model versioning, and A/B testing strategies; Ensure best practices in MLOps including automation, reproducibility, and CI/CD; Contribute to architectural decisions and improve ML infrastructure.
Seniority
Senior, hands-on IC