JOB DESCRIPTION
Job Summary:

As an Associate MLOps Engineer, you will play a crucial role in supporting the development and deployment of machine learning models in our organization. You will be responsible for working closely with the machine learning and data science teams to build, deploy, and monitor machine learning models, while also assisting in the management of production systems. You will have the opportunity to learn from experienced MLOps professionals and gain hands-on experience with cutting-edge technologies, including cloud computing services and containerization technologies such as Docker and Kubernetes.

The successful candidate will be a self-motivated individual with strong problem-solving and analytical skills. You should be comfortable working independently in a fast-paced environment and possess excellent communication and teamwork skills. You will be responsible for assisting in the implementation of MLOps best practices and continuously learning and implementing new tools and techniques. Additionally, you will provide technical support for the data science team and be involved in improving and optimizing the deployment pipeline for machine learning models.

This is an exciting opportunity for a motivated individual who is passionate about machine learning and eager to work with a team of skilled professionals. The role of Associate MLOps Engineer offers a challenging and rewarding career path with room for growth and advancement within the organization.

Key Responsibilities:

• Assist in building, testing and deploying machine learning models

• Collaborate with the data science team to implement MLOps best practices

• Monitor model performance and identify potential issues

• Help to improve and optimize the deployment pipeline for machine learning models

• Assist with the management and configuration of production systems

• Continuously learn and implement new MLOps tools and techniques

• Provide technical support for the data science team

Key Qualifications:

Experience designing, deploying, and administering a Kubernetes cluster

Experience with Google Cloud Platform services such as GCE, GKE, Storage

Must understand the Scrum Agile methodology and have worked on a Scrum team

Strong background in Python

Tech stack:

• Python programming


• GKE, Kubernetes, Containerization, GCR


• Background in Spark is a plus


• Apache Airflow


• Terraform (Coding modules)


• DevOps fundamentals

EOE M/F/Disability/Vets

LOCATION San Francisco, CA, USA FULL TIME/PART TIME Full time Current LS&Co Employees, apply via your Workday account.