MLOps Engineer Senior

4 дн. назад

SeniorRemote

machine learningmlopsdeploymentmonitoringscaling

Responsible for deploying, monitoring, and scaling machine learning solutions in production with a focus on MLOps best practices.

🚀 Join Our Data Products and Machine Learning Development Remote Startup! 🚀   Mutt Data is a dynamic startup committed to crafting innovative systems using cutting-edge Big Data and Machine Learning technologies.   We’re looking for a MLOps Engineer Senior to help take our expertise to the next level. If you consider yourself a data nerd like us, we’d love to connect! 🐶🚀   You'll be responsible for industrializing, deploying, monitoring, and scaling Machine Learning solutions in production, ensuring MLOps best practices, traceability, reliability, and operational excellence across the full model lifecycle. This role works closely with Data Scientists, Data Engineers, and business stakeholders, playing a key role in turning ML models into robust, production-grade systems.

 Industrialize, deploy, and scale Machine Learning models into production environments.
Design and maintain training, inference, and retraining pipelines end-to-end. 
 Build and maintain CI/CD pipelines for ML workflows, ensuring smooth and reliable releases. Implement and manage model tracking, versioning, and registry using MLflow. 
Develop and expose APIs for model serving, ensuring performance and scalability.
Orchestrate workflows and jobs on Databricks (Workflows, Jobs, Repos). 
Containerize ML applications with Docker and support deployment on Kubernetes-based infrastructure. Implement model governance and versioning practices to ensure traceability across the ML lifecycle. 
Collaborate closely with Data Scientists, Data Engineers, and business stakeholders to align technical solutions with business needs. 
Promote MLOps best practices and modern ML architecture across the team.

Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.
Amazon Web Services
Astronomer
Databricks
📊 We are Data Nerds
🤗 We are Open Team Players
🚀 We Take Ownership
🌟 We Have a Positive Mindset
Advanced Python and SQL. 
Experience with Spark / PySpark. 
Solid experience with CI/CD pipelines and Git. 
Experience with MLflow (tracking, registry, and deployment). 
Experience with Docker and working knowledge of Kubernetes concepts.
Experience with Azure Cloud.
Experience implementing model monitoring and observability practices.
Strong understanding of MLOps and ML architecture principles.
Experience deploying models to production at scale.