Engineer - ML Ops
1 day ago
- Design, implement, and manageCI/CD pipelines tailored for machine learningworkflows.
- Ensure that machine learning modelsare properly versioned and deployed into production, staging, ortesting environments automatically.
- Collaboratewith data scientists and software engineers to optimize theautomation process for training, validating, and deploying machinelearning models.
- Continuously monitor theperformance and reliability of CI/CD pipelines and make adjustmentsas necessary.
- Set up environments and fullyimplement scalable machine learningoperations.
- Continuously monitor, optimize,debug and automate MLOps pipelines for increased quality andefficiency—including pipeline level, module level, andsystem-level inspection.
- Develop &maintain the infrastructure & tools that facilitate thedeployment and monitoring of our ML algorithms inproduction.
- Keep abreast of the latesttechnology trends to drive standard methodologies and stay ahead ofthe curve.
- Document and track all systems,pipelines and best practices.
Qualifications
Skillsand attributes for success
The measurement ofyour success will be based on cost savings, the impact of MLOps onbusiness revenue, the number of projects successfully completed,improvements made to existing solutions and processes, and customerNet Promoter Score (NPS).
To qualify for therole you must have
- Minimumof 3 years experience in setting up and maintaining CI/CDpipelines, preferably in a machine learningcontext.
- Strong understanding ofcontainerization and orchestration tools such as Docker andKubernetes.
- Familiarity with machine learningframeworks like TensorFlow, PyTorch, orScikit-learn.
- Proficient in scripting languagessuch as Python, Bash, or Shell for automationtasks.
Engineering
EmploymentType : Full Time
Department /Functional Area: Engineering
Experience: years
Gender: Male
Vacancy: 1
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