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Senior ML/MLOps Engineer

unlimited holidays
Remote: 
Full Remote
Contract: 
Experience: 
Mid-level (2-5 years)
Work from: 

Offer summary

Qualifications:

3 years of experience in software engineering, Good knowledge of Python and its ecosystem for ML applications, Understanding of microservices and common architectural patterns, Experience with containerized applications using Docker and any testing framework..

Key responsabilities:

  • Design, develop, and deploy ML-powered systems
  • Maintain and improve ML systems over time
  • Collaborate with ML researchers to ensure system functionality
  • Work with the infrastructure team to maintain system stability and address issues.

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SANDBX Scaleup https://www.sandbx.co
51 - 200 Employees
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Job description

SANDBX is looking for an ML/MLOps Engineer.

As MLE/MLOps you will be responsible for developing and maintaining ML-powered services. You will work closely with cross-functional teams and help bridge the gap between the algorithms/models developed by ML Researchers and other systems that utilize them.

Responsibilities:

  • Design, develop, and deploy ML-powered systems
  • Maintain and improve such systems over time
  • Work closely with ML researchers to make sure the systems are functioning correctly and utilize efficient tooling
  • Work closely with the infra team to maintain the stability of the systems, identify and help address possible issues with underlying environments

Requirements

  • 3 years of experience in software engineering
  • Good knowledge of Python and its ecosystem, specifically related to ML applications and their deployment (e.g. knowing how to take a model developed by researchers  and convert it into a live deployment)
  • Understanding of microservices and common architectural patterns used alongside them
  • Experience using any REST framework (FastAPI preferably, but anything similar will do)
  • Familiarity with Linux and its ecosystem of CLI tools
  • Experience with writing containerized applications using Docker
  • Experience with any testing framework
  • Understanding of DevOps principles (CI/CD, infrastructure-as-code)
  • Experience with deploying any ML-based app
  • willingness to learn and being open to new tools/approaches/tech stacks
  • Good communication skills
  • Effective communication in English
  • Understanding the general computational requirements of common ML algorithms
  • Experience using (one of) k8s/docker-compose/any major cloud provider

Would be a plus:

  • Understanding observability, metrics, alerts
  • Data engineering skills
  • Any prior MLE/ML research experience
  • Experience with any MLOps tools (like MLFlow, Pachyderm, KubeFlow, DVC, etc)
  • Familiarity with kubectl for debugging issues with k8s-based deployments

Benefits

We offer:
- Market competitive salary
- Small but highly skilled, technically savvy and passionate team
- Open, honest and inclusive culture
- Unlimited vacations and sick days
- Benefits&perks

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Willingness To Learn
  • Communication

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