MLOps Engineer

Remote
Contracted
LATAM Technology
Mid Level

About Fusemachines

Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic and more than 250 full-time employees) Fusemachines seeks to bring its global expertise in AI to transform companies around the world.

About the role

This is a remote, full-time consulting position (contract).

Responsibilities

  • Design the data pipelines and engineering infrastructure to support our clients’ enterprise machine learning systems at scale
  • Design the data pipelines and engineering infrastructure to support our clients’ enterprise machine learning systems at scale
  • Build and turn offline models into a real machine learning production system
  • Develop and deploy scalable tools and services for our clients to handle machine learning training and inference
  • Identify and evaluate new technologies to improve performance, maintainability, and reliability of our clients’ machine learning systems
  • Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
  • Support model development, with an emphasis on auditability, versioning, and data security
  • Facilitate the development and deployment of proof-of-concept machine learning systems
  • Communicate with clients to build requirements and track progress

Qualifications

  • 3+ years experience building production-quality software.
  • Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent)
  • Proficiency in AWS compatible ML Technologies – AWS - Sage maker
  • Experience with cloud stacks, e.g. AWS and Infrastructure as Code e.g. Terraform Experience
  • Fluency in Python
  • Comfort with Linux administration
  • Experience working with cloud computing and database systems
  • Experience building custom integrations between cloud-based systems using APIs
  • Experience developing and maintaining ML systems built with open source tools
  • Experience developing with containers and Kubernetes in cloud computing environments
  • Familiarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.)
  • Ability to translate business needs to technical requirements
  • Strong understanding of software testing, benchmarking, and continuous integration
  • Exposure to machine learning methodology and best practices
  • Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.

Education

  • Bachelor's or Master's degree and/or equivalent professional experience

Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

 

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