MLOPS ENGINEER @ TALENTQUELL
We are seeking a highly skilled MLOps Engineer to spearhead our cross-cloud machine learning model migration initiatives, specifically moving from GCP to Azure Databricks. The successful candidate will be responsible for building and optimizing production-grade MLOps workflows and CI/CD pipelines while implementing MLflow for meticulous model tracking and lifecycle management. You will develop scalable pipelines using Databricks and PySpark, ensuring seamless data movement and high model reliability. The budget for this position is ₹1.4 LPM.
In this role, you will also focus on performance and cost optimization of machine learning infrastructures. You will work closely with Data Science teams to enable efficient model deployment and monitoring across cloud environments. This position operates on a UK time shift (8 AM – 5 PM) and offers a remote working arrangement within India. Candidates should have a strong foundation in data engineering and pipeline orchestration to succeed in this dynamic environment.
In this role, you will also focus on performance and cost optimization of machine learning infrastructures. You will work closely with Data Science teams to enable efficient model deployment and monitoring across cloud environments. This position operates on a UK time shift (8 AM – 5 PM) and offers a remote working arrangement within India. Candidates should have a strong foundation in data engineering and pipeline orchestration to succeed in this dynamic environment.
Key Requirements
Minimum 6–8 years of professional experience in MLOps or a related technical role.
Strong expertise in Databricks and PySpark for large-scale data processing.
Hands-on experience with MLflow for tracking experiments and managing model lifecycles.
Proven proficiency in CI/CD practices and workflows using tools like GitHub Actions.
Extensive experience working with cloud platforms, specifically Microsoft Azure and GCP.
Demonstrated ability to perform cross-cloud data movement and model migration tasks.
In-depth knowledge of model deployment strategies and continuous monitoring systems.
Strong background in data engineering and the orchestration of complex pipelines.
Excellent communication and collaboration skills for working with Data Science teams.
Availability to work according to the UK shift timings from 8 AM to 5 PM.