Senior MLOps Engineer

8 Hours ago • 6-8 Years

About the job

SummaryBy Outscal

Senior MLOps Engineer with 6-8 years of experience in architecting and developing infrastructure for AI/ML at scale. Must have strong Python, SQL, AWS, CI/CD pipeline expertise, and experience deploying AI/ML services.

Description

Machine Learning Operations Engineer

Remote - Colombia

 

*ONLY CVs SUBMITTED IN ENGLISH WILL BE CONSIDERED*

 

The Opportunity: 

Anthology delivers education and technology solutions so that students can reach their full potential and learning institutions thrive. Our mission is to empower educators and institutions with meaningful innovation that’s simple and intelligent, inspiring student success and institutional growth.

 

The Power of Together is built on having a diverse and inclusive workforce. We are committed to making diversity, inclusion, and belonging a foundational part of our hiring practices and who we are as a company.

 

For more information about Anthology and our career opportunities, please visit www.anthology.com. 

 

Anthology’s data science team, Logos, is a global team that serves as a strike force to tackle the most challenging AI/ML features that require development and deployment of custom models. The team also leverages the power of our Illuminate data platform to deliver on use cases built on data from multiple Anthology products. Our cross-product data provides holistic insight into all aspects of student and institutional lifecycle. Being at the heart of the company, Illuminate and Logos play the central role in manifesting the Power of Together. If you're an experienced MLOps Engineer who wants to work on exciting projects that leverage AI/ML at scale and are excited about advancing the AI revolution, we'd love to speak with you.

 

Primary responsibilities will include:

  • Architecting and development of infrastructure to support AI/ML inference and training at scale
  • Maintenance of existing model deployments
  • Interfacing with other engineering teams from Anthology and helping them take advantage of AI/ML models in their products
  • Gathering knowledge and experience from our partners (AWS, Microsoft, Snowflake, and others)
  • Actively helping to advance our AI/ML infrastructure and toolbox
  • This role may require possible occasional travel to the USA or Europe

 

The Candidate:

Required skills/qualifications:

  • 6-8 years of experience performing MLOps, DevOps, SW Engineering or similar role
  • Ability to create robust, high-quality Python code that adheres to best practices such as thorough testing
  • Experience with SQL and data lakes
  • Experience creating and maintaining CI/CD pipelines
  • Deep knowledge of Amazon Web Services
  • Understanding of Infrastructure as Code and ability to describe AWS infrastructure using CDK
  • Ability to create and maintain complex Github workflows
  • Hands on experience of deploying and maintaining AI/ML based services
  • Fluency in written and spoken English at CEF B2 level or above

 

Preferred skills/qualifications:

  • Experience with Amazon SageMaker and Amazon Bedrock
  • Knowledge of Data Version Control and Continuous Machine Learning
  • Experience with Azure
  • Hands on experience training AI/ML models
  • Experience with Snowflake and its tools for AI/ML
  • Ability to communicate effectively with technical and non-technical audiences and ability to express complex technical ideas simply

 

This job description is not designed to contain a comprehensive listing of activities, duties, or responsibilities that are required. Nothing in this job description restricts management's right to assign or reassign duties and responsibilities at any time.

 

Anthology is an equal employment opportunity/affirmative action employer and considers qualified applicants for employment without regard to race, gender, age, color, religion, national origin, marital status, disability, sexual orientation, gender identity/expression, protected military/veteran status, or any other legally protected factor.

About The Company

Karnataka, India (On-Site)

United States (Remote)

United States (Remote)

Karnataka, India (On-Site)

Bogota, Colombia (Hybrid)

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