ML Ops Engineer

ML Ops Engineer

Req number:

R5275

Employment type:

Full time

Worksite flexibility:

Remote

Who we are

CAI is a global technology services firm with over 8500 associates worldwide and a yearly revenue of $1 billion. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients colleagues and communities. As a privately held company we have the freedom and focus to do what is rightwhatever it takes. Our tailormade solutions create lasting results across the public and commercial sectors and we are trailblazers in bringing neurodiversity to the enterprise.

Job Summary

We are seeking Machine Learning (ML) Ops Engineer you will be working with data scientists to deploy data science models to our cloud platform using ML and AWS technologies such as Athena Glue SageMaker. You will be responsible to orchestrate all the processes from data cleaning preprocessing data management auditing governance logging monitoring security model training and deployment in a production environment. You will use your expertise to provide recommendations around security cost performance reliability and operational efficiency to accelerate projects. This is a Fulltime and Remote position.

Job Description

What Youll Do

• Understand current state architecture including pain points.
• Create and document future state architectural options to address specific issues or initiatives using Machine Learning.
• Innovate and scale architectural best practices around building and operating ML workloads by collaborating with stakeholders across the organization.
• Develop CI/CD & ML pipelines that help to achieve endtoend ML model development lifecycle from data preparation and feature engineering to model deployment and retraining.
• Provide recommendations around security cost performance reliability and operational efficiency and implement them
• Provide thought leadership around the use of industry standard tools and models (including commercially available models and tools) by leveraging experience and current industry trends.
• Collaborate with the Enterprise Architect consulting partners and client IT team as warranted to establish and implement strategic initiatives.
• Make recommendations and assess proposals for optimization.
• Identify operational issues and recommend and implement strategies to resolve problems.
  

What Youll Need

• 3 years of experience in developing CI/CD & ML pipelines for endtoend ML model/workloads development.
• Strong knowledge in ML operations and DevOps workflows and tools such as Git AWS Code Build & Code Pipeline Jenkins AWS CloudFormation and others.
• Background in ML algorithm development AI/ML Platforms Deep Learning ML Operations in the cloud environment.
• Strong programming skillset with high proficiency in Python R etc.
• Strong knowledge of AWS cloud and its technologies such as S3 Redshift Athena Glue SageMaker etc.
• Working knowledge of databases data warehouses data preparation and integration tools along with big data parallel processing layers such as Apache Spark or Hadoop.
• Knowledge of pure and applied math ML and DL frameworks and ML techniques such as random forest and neural networks.
• Ability to collaborate with Data scientist Data Engineers Leaders and other IT teams.
• Ability to work with multiple projects and work streams at one time. Must be able to deliver results based upon project deadlines.
• Willing to flex daily work schedule to allow for timezone differences for global team communications.
• Strong interpersonal and communication skills.

Physical Demands

• This role involves mostly sedentary work with occasional movement around the office to attend meetings etc.
• Ability to perform repetitive tasks on a computer using a mouse keyboard and monitor.

Reasonable accommodation statement

If you require a reasonable accommodation in completing this application interviewing completing any preemployment testing or otherwise participating in the employment selection process please direct your inquiries to or (888).