Senior ML Engineer: MLOps & Production (PySpark)

G10X Pte Ltd; Greater London; On-site; GBP 90,000 - 135,000; Full time

Job summary

G10X Pte Ltd in Greater London seeks a Senior Machine Learning Engineer focused on deploying and operating ML/DL models in production. You will design, deploy, and monitor production ML systems with strong MLOps practices.

Responsibilities include building end-to-end MLOps workflows using PySpark and Databricks, productionizing DL models, and collaborating with Data Scientists, Data Engineers and stakeholders to deliver scalable, reliable ML solutions for multimodal data.

Qualifications

• 5+ years of experience in ML / ML Engineering.
• Hands-on MLOps and production ML deployment experience.
• PySpark and Databricks experience required.
• Experience deploying Deep Learning models to production.
• Strong knowledge of the end-to-end MLOps lifecycle.
• Experience with multimodal data (CV + text + metadata or similar).

Responsibilities

• Design, deploy, and operationalize ML/DS models in production.
• Build end-to-end MLOps workflows covering training, validation, deployment, monitoring, versioning, and retraining.
• Develop scalable data and ML pipelines using PySpark and Databricks.
• Productionize DL models and support scalable inference.
• Collaborate with data scientists, ML engineers, data engineers and stakeholders to deliver production-ready ML solutions.
• Ensure ML systems are scalable, reliable, and maintainable for production environments.

Skills

MLOps

Production ML

End-to-end ML

Multimodal data

Embeddings & vector DB

Cloud platforms

Tools

PySpark

Databricks

MLflow

Kubernetes

CI/CD

Model serving

ML monitoring

Job description

G10X Pte Ltd in Greater London seeks a Senior Machine Learning Engineer focused on deploying and operating ML/DL models in production. You will design, deploy, and monitor production ML systems with strong MLOps practices.

Responsibilities include building end-to-end MLOps workflows using PySpark and Databricks, productionizing DL models, and collaborating with Data Scientists, Data Engineers and stakeholders to deliver scalable, reliable ML solutions for multimodal data.