Software Engineer

Ethara AI’s interview process typically starts with a timed aptitude test, followed by a technical interview that probes Python proficiency, data manipulation concepts, and basic AI knowledge. The final HR round evaluates communication skills and cultural fit. Candidates report a moderate difficulty level, with interviewers focusing on practical problem‑solving rather than theoretical depth. Preparing with real‑world data projects and practicing coding challenges greatly improves success chances.

Ethara AI promotes a collaborative, learning‑first environment where junior members are mentored by senior AI professionals. The company emphasizes work‑life balance, flexible timings, and regular knowledge‑sharing sessions, enabling employees to grow both technically and personally.

Eligibility criteria: - Degree: Currently pursuing or completed B.Tech, B.E., M.Tech, or equivalent in Computer Science, Electronics, Electrical, Information Technology, or related streams. - Branch: Any engineering or science discipline with a strong foundation in programming and data handling. - Academic Performance: Minimum aggregate of 60% (or CGPA 6.0/10) in the most recent qualifying examination. - Year of Passing: Open to candidates graduating in 2025, 2026, or 2027. - Backlog Policy: No active backlogs at the time of application; candidates with cleared backlogs may be considered. - Additional: Must possess a valid government‑issued ID (Aadhaar) and be able to provide 10th and 12th mark sheets.

Round 1: Online aptitude and logical reasoning test → Round 2: Technical interview focusing on data handling, Python, and basic AI concepts → Round 3: HR interview to assess cultural fit and career aspirations

Ethara AI is an emerging AI and data services firm headquartered in India, known for creating high‑quality, domain‑specific datasets that power Large Language Model (LLM) fine‑tuning. The company bridges the gap between academic research and real‑world AI deployments, partnering with startups, research labs, and enterprise customers to deliver data that is clean, annotated, and ready for model training. Ethara AI’s mission is to democratize access to premium AI data, enabling innovators across sectors—healthcare, finance, education, and more—to build smarter, more reliable AI solutions. The organization prides itself on a culture of continuous learning, where fresh talent works alongside seasoned AI engineers, data scientists, and domain experts. The role advertised through the Candidate Nomination Form is essentially an entry‑level opportunity for fresh graduates and final‑year students to join Ethara AI’s data‑centric teams. While the posting does not specify a traditional job title, the underlying responsibilities align with those of a Data Annotation Engineer or Junior Data Engineer. Candidates will be expected to contribute to the end‑to‑end data pipeline: collecting raw data, cleaning and preprocessing it, performing annotation and labeling tasks, and ensuring compliance with data privacy standards. The position offers exposure to cutting‑edge AI projects, allowing candidates to see how curated datasets directly impact model performance. Key responsibilities include: 1. Gathering and organizing raw data from diverse sources such as web crawls, public repositories, and client‑provided datasets. 2. Cleaning, normalizing, and validating data to meet quality benchmarks. 3. Performing manual and semi‑automated annotation using industry‑standard tools. 4. Collaborating with AI researchers to understand domain‑specific labeling requirements. 5. Maintaining detailed documentation of data workflows and versioning. 6. Conducting exploratory data analysis to identify gaps or biases. 7. Assisting in the development of data augmentation scripts. 8. Ensuring strict adherence to data security and confidentiality policies. 9. Participating in regular team stand‑ups and knowledge‑sharing sessions. 10. Continuously learning new tools and techniques in data engineering and AI. The tech stack at Ethara AI includes Python, Pandas, NumPy, SQL, and annotation platforms such as Prodigy or Labelbox. Familiarity with cloud storage (AWS S3, GCP) and basic machine‑learning libraries (TensorFlow, PyTorch) is advantageous. The growth path is clearly defined: junior contributors can progress to Data Engineer, then to Senior Data Engineer or AI Data Specialist, with opportunities to lead project teams or move into AI research support roles. Joining Ethara AI provides a unique chance to work on impactful AI datasets, gain mentorship from industry experts, and build a portfolio that showcases real‑world AI data engineering experience.