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Work Mode

Remote

Job Type

Full Time

Job Description

About the Company

We believe great AI comes from exceptional, human-generated data. Our work bridges the gap

between human expertise and machine intelligence—powering the next generation of AI systems

with precision and quality.


Role Overview

We are looking for skilled Software Engineers with strong command-line and systems expertise. The

ideal candidate thrives in Unix-like environments, is comfortable with containerized workflows, and

builds reliable, reproducible setups backed by clear documentation and testing.

This is an exciting opportunity to contribute to a cutting-edge AI project while enjoying flexible,

remote work arrangements.


Key Responsibilities

• Design multi-step command-line development exercises (e.g., debugging, refactoring, data

processing, build automation).

• Develop deterministic test suites and solutions.

• Containerize tasks using Docker for consistency and reproducibility.

• Write clear, detailed documentation describing objectives, steps, and requirements.


Required Qualifications

• Strong proficiency with Linux/Unix command-line tools and Bash scripting.

• Minimum 1+ years of professional software engineering experience.

• Hands-on experience with Docker and containerized development environments.


Preferred Qualifications

• Familiarity with build tools such as Make, CMake, npm, Cargo, or Gradle.

• Experience troubleshooting CI/CD pipelines or complex development setups.

• Exposure to multiple language ecosystems (Python, Go, Rust, C/C++).


Engagement Details

• Type: Contractual (1-month probation with potential full-time conversion)


• Location: Preferably Mumbai-based candidates

• Work Mode: Remote initially; hybrid setup (2–3 days a week in-office) expected next month

• Compensation: ₹75,000 – ₹85,000 per month (can go up to ₹1,00,000 based on interview

performance)


Ideal Candidate

We’re looking for individuals who are:

• Driven, proactive, and adaptable to startup environments.

• Motivated by learning and impact, not just compensation.

• Ready to build robust systems and contribute to a high-performance engineering culture.

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