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HDFC Securities logo — HDFC Securities MLOps Engineer Intern in Rajkot, Gujarat
HDFC Securities VerifiedActively Hiring

MLOps Engineer Intern

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Location

Rajkot, Gujarat

Work Mode

In Office

Duration

2 months

Stipend

₹19,000/mo

Start Date

Immediate / Rolling

Openings

12 positions

Type

Full-time

Category

Machine Learning

Apply Now — ₹19,000/moApply on Company Website ↗

About the Internship

Start your career in machine learning operations with HDFC Securities as a MLOps Engineer Intern in Rajkot. 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 HDFC Securities, your…

About HDFC Securities

HDFC Securities offers a mentor-led MLOps Engineer Intern in Rajkot with live project work in machine learning, a stipend of ₹19,000/month and a Pre-Placement Offer opportunity for strong performers.
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Rajkot, GujaratVerified employer12 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 Rajkot. 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

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

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
19,000/month

Stipend · 2 months

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Openings12 positions
Applicants0 applied
ModeIn Office
CategoryMachine Learning
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