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K7 Computing logo — K7 Computing MLOps Engineer Intern in Surat, Gujarat
K7 Computing VerifiedActively Hiring

MLOps Engineer Intern

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Location

Surat, Gujarat

Work Mode

Work from Home

Duration

2 months

Stipend

₹34,000/mo

Start Date

Immediate / Rolling

Openings

3 positions

Type

Full-time

Category

Machine Learning

Apply Now — ₹34,000/moApply on Company Website ↗

About the Internship

K7 Computing has an open MLOps Engineer Intern position in Surat for motivated freshers and final-year students. You will work on live machine learning operations projects and finish with something you can genuinely talk about in interviews. About the role As a MLOps Engineer Intern at K7…

About K7 Computing

K7 Computing offers a mentor-led MLOps Engineer Intern in Surat with live project work in machine learning, a stipend of ₹34,000/month and a Pre-Placement Offer opportunity for strong performers.
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Surat, GujaratVerified employer3 openings
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Skills Required

PythonMLflowDockerCI/CD PipelinesModel Monitoring & DriftCloud (AWS / Azure / GCP)Kubernetes BasicsFeature StoresModel VersioningLogging & Alerting

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/IT), MCA or M.Sc (Computer Science) who are based in or willing to work from Surat. You should be keen to learn Python, MLflow, Docker on real projects and able to write clearly. Freshers are welcome — no prior work experience is required, and a strong project portfolio matters more than a long CV.

Perks

Live project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionals

Interview & Selection Process

4 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Team-fit / behavioural interview with the team
  3. 3Online aptitude / domain assessment
  4. 4HR discussion — stipend, start date, expectations and offer
34,000/month

Stipend · 2 months

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Openings3 positions
Applicants0 applied
ModeWork from Home
CategoryMachine Learning
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