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SMC Global Securities logo — SMC Global Securities MLOps Engineer Intern in Hyderabad, Telangana
SMC Global Securities VerifiedActively Hiring

MLOps Engineer Intern

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Location

Hyderabad, Telangana

Work Mode

Work from Home

Duration

2 months

Stipend

₹41,000/mo

Start Date

Immediate / Rolling

Openings

1 positions

Type

Full-time

Category

Machine Learning

Apply Now — ₹41,000/moApply on Company Website ↗

About the Internship

Start your career in ML platform and operations with SMC Global Securities as a MLOps Engineer Intern in Hyderabad. You will sit with a working team, use the same tools and systems they do, and own a defined piece of work from day one. About the role As a MLOps Engineer Intern at SMC Global…

About SMC Global Securities

SMC Global Securities offers a mentor-led MLOps Engineer Intern in Hyderabad with live project work in machine learning, a stipend of ₹41,000/month and a Pre-Placement Offer opportunity for strong performers.
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Hyderabad, TelanganaVerified employer1 opening
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Skills Required

KubeflowMLflowCI/CD for AIDocker / KubernetesModel Monitoring & Drift DetectionPythonFeature StoresModel Registry & VersioningCloud ML PlatformsInfrastructure as Code

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/IT), MCA or M.Sc (Computer Science / Data Science) who are based in or willing to work from Hyderabad. You should be keen to learn Kubeflow, MLflow, CI/CD for AI 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

Pre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionalsInternship CertificateLetter of Recommendation

Interview & Selection Process

2 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Online aptitude / domain assessment
41,000/month

Stipend · 2 months

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Openings1 positions
Applicants12 applied
ModeWork from Home
CategoryMachine Learning
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