MLOPs Engineer

Key Skills

Aartificial intelligence, Apache Hadoop, Apache Hive, AWS, Azure, Data science techniques, DevOps, Google Cloud Platform (GCP), Infrastructure-as-code-IaC, Machine learning techniques, MLOps tools, Operations, Python Programming, RESTful, SPARK Programming

Job Description

We are looking for ML Engineers to set directions and goals with respect to the deployment and maintenance of our ML solutions.

Join us and discover a company embracing the analytical revolution, encouraging you to develop your skills while working with colleagues ready to support and inspire you.

What are we looking for?

We are looking for ML Engineers to set directions and goals with respect to the deployment and maintenance of our ML solutions. An ideal candidate would bring the following qualifications:

• Master’s degree in Computer Science or related quantitative field

• Hands-on experience in one or several of the following areas: Machine Learning, Data Engineering, Data Mining, Artificial Intelligence

• Experience in designing and developing Data Engineering pipelines across different paradigms such as batch, event-driven and streaming using relevant tools

• Experience with Microservice architecture, Models as a Service and RESTful APIs

• Experience in developing production-level ML applications

• Experience with DevOps/ML Ops principles

• Comfortable with Agile Software Development Principles

• Hands-on experience in cloud ecosystems such as Microsoft Azure, AWS, GCP

• Hands-on experience with Python; Knowledge of Hadoop, Hive, Apache Spark is a plus

What would be your key responsibilities?

• Working closely with our internal Data Scientists and Data Engineers, you’ll help design sustainable and scalable Data Science solutions. This means you’ll also partner with business stakeholders to comprehend individual use cases fully. Moreover, we’re looking to you to set up appropriate monitoring systems for ML models running in production.

Your day-to-day activities will include, but not be limited to, the following:

• Collaborate with Data Scientists and Data Engineers to design sustainable and scalable ML solutions either on a consulting basis or hands-on, depending on the use cases

• Own the monitoring of ML systems running in production

• Implementing the automation of retraining new data sets seen through in production and initiating automatics deployments

• Continuously improving best-practices around deploying and productionizing ML models

• Educating fellow Data Scientists, Data Engineers and Business Translators on the importance of the ML Engineering role

• Advocate for production level coding and best practices such as pair programming, automated testing and IAC

What can you expect from Mars?

• Work with over 130,000 like-minded and talented Associates, all guided by The Five Principles.
• Join a purpose-driven company, where we’re striving to build the world we want tomorrow, today.
• Best-in-class learning and development support from day one, including access to our in-house Mars University.
• An industry-competitive salary and benefits package, including company bonus.