KASHII UPDATEZ Everyday Student Requirements & Python Coding Tutorials by Python Kashi
JD #2913
Applications open Internship

Graduate Engineer Trainee (GET)

Eoje

  • Mumbai, Gurgaon, Chennai, Hyderabad, Kolkata
  • β‚Ή3 LPA
  • Fresher (0-1 Yrs)
  • Posted Today
HR
Recruiter contact
Recruiter / hiring contact
No public email in this post. Use a source-linked contact instead.

About the role

Black Box is a fast‑growing Indian IT services and solutions provider that specializes in end‑to‑end infrastructure, networking, and audio‑visual (AV) deployments for enterprise customers. With over a decade of experience, the company has built a reputation for delivering reliable, secure, and future‑ready technology platforms across sectors such as banking, retail, education, and healthcare. Its culture emphasizes continuous learning, hands‑on project exposure, and a collaborative environment where fresh talent can quickly move from classroom concepts to real‑world implementations.

The Graduate Engineer Trainee (GET) program is designed for recent graduates who are eager to start a career in IT infrastructure. Trainees will be placed in one of Black Box’s major delivery hubs – Mumbai, Gurgaon, Chennai, Hyderabad, or Kolkata – and will work under senior engineers on live client projects. The role offers a balanced mix of on‑site installation, lab‑based configuration, and documentation tasks, providing a solid foundation for a long‑term career in networking, data‑center operations, and cybersecurity.

Key Responsibilities

  • Assist in the design, installation, and commissioning of structured cabling, ELV, and AV systems for client sites.
  • Configure and troubleshoot routers, switches, firewalls, and wireless access points in enterprise networks.
  • Support day‑to‑day operations of data‑center environments, including server provisioning and storage management.
  • Perform basic cybersecurity checks, patch management, and vulnerability assessments under guidance.
  • Monitor network performance using tools like SolarWinds, PRTG, or Nagios and raise alerts for any anomalies.
  • Prepare technical documentation, as‑built drawings, and project status reports for internal and client review.
  • Coordinate with vendors, project managers, and customers to ensure timely delivery of milestones.
  • Participate in knowledge‑sharing sessions and internal training workshops to stay updated on emerging technologies.
  • Contribute to the testing and validation of cloud‑based solutions and virtualization platforms.
  • Support the rollout of IT‑infrastructure upgrades and migrations across multiple locations.

Tech Stack: TCP/IP, Cisco/Juniper networking, Windows Server, Linux, VMware, basic AWS/Azure concepts, Structured Cabling Standards (TIA/EIA), Microsoft Office Suite, and fundamental scripting (Bash/Python).

Growth Path: Successful trainees can progress to roles such as Network Engineer, Systems Engineer, Cybersecurity Analyst, or Project Engineer within 1‑2 years. Black Box also offers certifications (CCNA, CompTIA Security+, ITIL) and encourages participation in industry conferences, ensuring a clear upward trajectory.

Why Join Black Box? The company provides a vibrant learning ecosystem, exposure to multi‑disciplinary projects, and a supportive mentorship model. Freshers receive a competitive CTC of β‚Ή3 LPA, comprehensive onboarding, and the chance to work on cutting‑edge infrastructure that powers some of India’s largest enterprises.

The emphasis on local hiring and the possibility of travel to client sites further enriches the professional experience.

Eligibility & process

Who can apply

Eligible candidates must have completed any of the following qualifications: Diploma Engineering, B.Sc., BCA, BCS, MCA, or M.Sc. Preferred engineering streams include Computer Engineering, Information Technology, Electronics & Telecommunication, Electronics Engineering, Electrical Engineering, and Instrumentation Engineering. Minimum aggregate of 60% (or CGPA 6.0/10) is preferred. Candidates should belong to the 2023‑2026 graduating batches. Backlog policy: maximum one active backlog at the time of joining; all backlogs must be cleared within six months of joining.

Skills & stack

Computer Networks Ip Technologies Windows Os Linux Os Cybersecurity Cloud Computing Structured Cabling Elv Systems

Selection process

  1. Round 1: Online Aptitude Test (Logical Reasoning, Quantitative, English)
  2. Round 2: Technical Interview (Networking concepts, OS fundamentals, scenario‑based questions)
  3. Round 3: HR Interview (fitment, communication, willingness to travel)

Prep kit

19 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Computer Networks, Ip Technologies, Windows Os, Linux Os, Cybersecurity, Cloud Computing, Structured Cabling, Elv Systems) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion Eoje Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 4
What is the bias-variance tradeoff and how do you prevent overfitting? Answer
Model answer: High bias leads to underfitting (oversimplified model), high variance leads to overfitting (captures noise). Mitigate using L1/L2 Regularization, Dropout, Cross-Validation, and data augmentation.
Explain the difference between Precision, Recall, and F1-Score. Answer
Model answer: Precision = TP / (TP + FP) (correctness of positive predictions). Recall = TP / (TP + FN) (coverage of actual positives). F1-Score is the harmonic mean of Precision and Recall.
How does Gradient Descent work and what is the role of Learning Rate? Answer
Model answer: It optimizes loss functions by iteratively moving weights in the direction of negative gradient. A large learning rate may overshoot the minimum; a small rate causes slow convergence.
What is the difference between Supervised, Unsupervised, and Self-Supervised learning? Answer
Model answer: Supervised uses labeled data (X -> y). Unsupervised finds hidden patterns in unlabeled data (clustering/PCA). Self-supervised generates labels from input data (e.g. masked language modeling in BERT/Transformers).
Behavioural & HR questions 3
Why do you want to join Eoje as a Graduate Engineer Trainee (GET)?
Highlight Eoje's market reputation, recent tech innovations, and how your skills in Computer Networks directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Eoje β‚Ή3 LPA
Recruiter Resume Apply
Chat Chat with Kashii