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MLOPS Engineer

Cogniphi

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IT - Software Development

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Job Description:

Join our team and help build the machine learning production infrastructure for our clients. As an experienced server-side developer, you will design data pipelines, develop and deploy scalable tools and services, and evaluate new technologies to improve machine learning systems’ performance, maintainability, and reliability.

Job Responsibility:

  • Designing data pipelines and engineering infrastructure to support clients’ enterprise machine learning systems at scale
  • Taking offline models from data scientists and turning them into a real machine learning production system
  • Developing and deploying scalable tools and services for clients to handle machine learning training and inference
  • Identifying and evaluating new technologies to improve the performance, maintainability, and reliability of clients’ machine learning systems
  • Applying software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
  • Supporting model development, with an emphasis on auditability, versioning, and data security
  • Facilitating the development and deployment of proof-of-concept machine learning systems
  • Communicating with clients to build requirements and track progress

Requirements:

  • Over 3 years of experience building production-quality software
  • Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent)
  • Strong software engineering skills in complex, multi-language systems
  • 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. – Kubeflow is a must and the ability to understand each framework and select the best tool for need is a must)
  • 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.)
What we offer:
  • Niche projects in Computer Vision, AI, and Telematics in multiple industry sectors
  • Platform and product implementations
  • Tier -1 technology partners and supportive management ensure individual as well as overall company growth
  • Global Work Culture
  • Psychological Safe Workplace

Additional Information:

Job Posted:
March 21, 2026

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