MLOPs Engineer

Key Skills

Aartificial intelligence, Agile methodologies, AWS, Azure, Data Mining, DevOps, Google Cloud Platform (GCP), Machine learning techniques, MLOps tools, Python Programming, Software Development

Job Description

What are we looking for?

We are looking for ML Engineers to set directions and goals with respect to 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 designing sustainable and scalable Data Science driven solutions. This means you’ll also partner with business stakeholders to fully comprehend individual use cases. 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

If this sounds like you, we’d love to hear from you!

Job Segment: Data Science, Decision Science, Machine Learning, And Artificial Intelligence

Mars is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. If you need assistance or an accommodation during the application process because of a disability, it is available upon request. The company is pleased to provide such assistance, and no applicant will be penalized as a result of such a request.