Zoho AI Engineering Roles for Freshers in 2026: Two Paths In

Zoho’s ML Engineer role is open to freshers with zero experience and is filled through off-campus applications; Zoho does not run campus drives.

That changes the calculus for students at Tier-2 and Tier-3 colleges: the selection filter is a written test and technical interview rounds, not your college’s placement cell or your institution’s tie-up with a recruiter. There are two distinct entry routes. One is the standard off-campus drive for BE/BTech graduates. The other is Zoho Schools of Learning, a funded two-year programme that ends in automatic full-time induction.

What Zoho’s In-House AI Actually Involves

In July 2025, Zoho launched Zia LLM, a proprietary large language model built on NVIDIA infrastructure entirely in-house. Three separately trained model variants cover the range from compact (1.3B parameters) to mid-sized (2.6B) to full (7B), with capabilities across structured data extraction, summarisation, retrieval-augmented generation, and code generation. The same announcement included 25+ ready-to-deploy Zia Agents, Zia Agent Studio (a no-code agent builder), an MCP server, and two proprietary ASR models in English and Hindi.

In February 2025, CEO Mani Vembu announced Zia Agents as an autonomous agentic platform running across 100+ Zoho products. His description of the goal: “Anyone can create capabilities, workflows, or reports in CRM with a simple prompt.”

The practical distinction for someone choosing where to apply: this is product-embedded AI engineering, not client-facing consulting work. Engineers working on Zia are involved in training, fine-tuning, and deploying real model architectures that serve customers across 100+ products. The work spans CRM, finance, HR, and customer support tools; Zia is embedded across the full Zoho product line. The skills required are substantively different from firms that consume AI APIs from a third party.

Path 1: Off-Campus Drives for BE/BTech Graduates

Zoho fills both the ML Engineer and Software Developer roles through off-campus drives. The Zoho Careers portal is where applications start; there is no campus recruitment.

Role	Experience	Work location
ML Engineer	0 to 4 years (freshers eligible)	Anywhere in Tamil Nadu
Software Developer	Freshers: 2024, 2025, 2026 pass-outs	Chennai, Coimbatore, Madurai, Salem, Tirunelveli

The ML Engineer role requires:

• Python or Java as the primary programming language
• TensorFlow, PyTorch, or Keras for model development
• NLP and Generative AI concepts
• Reinforcement Learning and LLM fundamentals
• MLOps practices and pipeline development
• Big Data tools: Spark, Hive, Hadoop, Kafka

CTC

Zoho does not publish fresher CTC for any role. Third-party aggregator estimates:

• ML Engineer: approximately 9 LPA (AmbitionBox estimate; not a Zoho-stated figure)
• Software Developer: approximately 6.5 to 8.5 LPA (AmbitionBox estimate; same caveat)

Work location for the ML Engineer role is anywhere in Tamil Nadu; Chennai is not guaranteed. The hiring sequence for both roles: written test (coding and aptitude), then technical interview rounds, then an offer.

For an overview of what the written test covers, see FACE Prep’s guide to the Zoho test pattern. For what to expect in the technical rounds, see the Zoho interview preparation guide.

Path 2: Zoho Schools of Learning

Zoho Schools of Learning (ZSL) has been running for 20 years and now operates across four Tamil Nadu campuses: Chennai, Tenkasi, Tharuvai, and Kumbakonam. According to the ZSL 20th anniversary announcement, the programme has produced 2,000+ graduates who make up over 10% of Zoho’s current workforce, with approximately 20,000 students applying each year and approximately 300 admitted across all campuses.

What ZSL offers:

• No fees of any kind
• Stipend: Rs 10,000 per month in Year 1, Rs 15,000 per month in Year 2
• Automatic full-time induction into Zoho on completion
• Campuses: Chennai, Tenkasi, Tharuvai, Kumbakonam (four campuses as of April 2025)

The School of Graduate Studies track within ZSL is specifically open to college graduates, making it a structured path for BE/BTech pass-outs who want a funded, multi-year entry into Zoho rather than an off-campus hiring cycle. The entry route is an annual aptitude and problem-solving test plus an interview. There is also a Zestober challenge in October that serves as an alternate application pathway.

One structural point worth noting: ZSL is not a placement process with a job offer at the end. It is a multi-year employment arrangement. You are paid throughout, and full-time induction follows automatically on completion. No separate hiring round at the end.

The selection ratio is competitive, but the filter is purely aptitude and problem-solving; college CGPA cutoffs and branch restrictions are not part of the published eligibility criteria. If you miss the main annual cycle, the Zestober challenge in October provides a second application window covering a similar problem-solving format.

For the off-campus drive process by comparison, see FACE Prep’s guide to the Zoho off-campus drive for software developers.

Prep Map for Both Routes

The preparation needed overlaps at the core and diverges at the ML layer:

Skill area	ML Engineer (Path 1)	ZSL (Path 2)
Aptitude (quant, logical, verbal)	Written test gate	Entrance test gate
Programming (Python or Java)	Required; specified in JD	Required; also taught within ZSL
Data structures and algorithms	Technical interview filter	Technical interview filter
ML/DL frameworks (TF, PyTorch, Keras)	Required at application	Not required at entry; taught in programme
MLOps and Big Data tools	Required for ML Engineer role	Not required at entry

For Path 1, the prep sequence is: get aptitude and DSA foundations solid first (the written test is the gate), then demonstrate ML framework experience in the technical rounds. For Path 2 (ZSL), aptitude and problem-solving are the entry filters; the programme teaches ML skills from scratch. ZSL students start from programming and algorithms fundamentals before advancing to ML-specific tooling. If you’re applying through ZSL, your prep priority is demonstrating strong reasoning on the entrance test, not ML framework knowledge you don’t yet have.

The AI Context: What Zoho’s In-House LLM Means for Applicants

Zoho’s choice to build Zia LLM internally rather than integrate a third-party API means engineers on that team need to understand what an LLM actually does from the inside: why a 1.3B parameter model is appropriate for extraction tasks versus a 7B model for generation, how retrieval-augmented generation changes output quality, and what MLOps looks like at Zoho’s scale. API-calling skills alone won’t clear the ML Engineer technical rounds.

Zoho’s bootstrapped model, with 1M+ paying customers and 32% year-on-year customer growth in 2025 per the Zoho 30th anniversary press release, means engineering roles are created because work needs doing. The ML Engineer role is listed year-round because Zia’s model development is ongoing, not because a funding round inflated headcount.

The 2026 AI roadmap for Indian engineering students covers which AI skills are worth building now and which are noise for placement-window timelines. Read it before finalising your prep focus for the ML Engineer track.

Zoho builds its own models. That means engineers there understand LLMs from the architecture up, not just from an API key. TinkerLLM is the entry-level counterpart to that kind of understanding: ₹299 puts real LLM API calls in your hands, and the micro-project you ship is what you show the next time a Zoho recruiter asks what you’ve actually built.