Senior ML Engineer (MLOps-focused)

Actively Hiring

Full-time Posted 4 months ago

Responsibilities

check_circle Lead and drive the deployment, lifecycle management, and monitoring of ML/DL models in all stages leading to production.
check_circle Design and implement systems for Dataset and Label Management, including versioning and integrating customer feedback into labeling workflows.
check_circle Establish and maintain a robust Model Repository/Registry that supports versioning, local inference, and model lineage.
check_circle Lead the implementation of advanced Experiment Tracking and Monitoring solutions for both Data Science and Generative AI, focusing on evaluation, data drift detection, and model reproducibility.
check_circle Own model serving and inference systems—including autoscaling, A/B testing, canary rollouts, and latency/cost optimization for production models.
check_circle Enable specialized infrastructure for Generative AI capabilities, including tagging tools, prompt management, and LLM testing services.
check_circle Drive operational excellence by improving tool deployment usability and implementing granular cost visibility across projects and environments.
check_circle Developing reusable components such as standardized data loaders, CI/CD pipelines, and automated workflows for tasks like model retraining.
check_circle Collaborate directly with Data Scientists and the rest of the Data Platform Engineering team to productionize ML/DL models developed for cloud environments.

check_circle Flexible work arrangements.
check_circle 15 working days per year as Non-Operational Allowance for personal recreation, fully compensated.
check_circle Health insurance.
check_circle Public holidays.
check_circle Truly competitive salary.
check_circle Supportive HR and management team.

Remote Ai Machine Learning Mlops