Unisys is Hiring AI Engineering Intern | Bangalore | M.Tech Students/Graduates

Job Description

There's a critical eligibility restriction worth putting at the top of this post: this internship is explicitly for 𝐅𝐢𝐧𝐚𝐥-𝐲𝐞𝐚𝐫 𝐌.𝐓𝐞𝐜𝐡 𝐬𝐭𝐮𝐝𝐞𝐧𝐭𝐬 𝐨𝐫 𝐫𝐞𝐜𝐞𝐧𝐭 𝐌.𝐓𝐞𝐜𝐡 𝐠𝐫𝐚𝐝𝐮𝐚𝐭𝐞𝐬 — this is not open to B.Tech/BE students, unlike most fresher internships covered on this site. If you have a bachelor's degree only, this specific listing states you're not eligible, regardless of your AI/ML skill level.

Setting that eligibility restriction aside, this is one of the more genuinely advanced and hands-on AI engineering roles covered on this site — the listing explicitly frames itself as 𝐛𝐮𝐢𝐥𝐝𝐞𝐫-𝐟𝐨𝐜𝐮𝐬𝐞𝐝, emphasizing that interns will spend time "designing, implementing, and hardening real systems rather than working from theory." Combined with the requirement for 𝐬𝐨𝐥𝐢𝐝 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐨𝐟 𝐡𝐨𝐰 𝐭𝐨 𝐛𝐮𝐢𝐥𝐝 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 and the harnesses around them, including 𝐨𝐫𝐜𝐡𝐞𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧, 𝐭𝐨𝐨𝐥𝐢𝐧𝐠, 𝐞𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧, and 𝐠𝐮𝐚𝐫𝐝𝐫𝐚𝐢𝐥𝐬, this is a genuinely production-oriented AI engineering internship.

What distinguishes this from other AI internships covered: the work explicitly involves taking prototypes through to 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐫𝐞𝐚𝐝𝐲, 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞-𝐝𝐞𝐩𝐥𝐨𝐲𝐚𝐛𝐥𝐞 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 — meaning you'd be doing genuine engineering hardening work such as 𝐭𝐞𝐬𝐭𝐢𝐧𝐠, 𝐫𝐞𝐥𝐢𝐚𝐛𝐢𝐥𝐢𝐭𝐲, and 𝐝𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐫𝐞𝐚𝐝𝐢𝐧𝐞𝐬𝐬, not just building experimental proof-of-concepts. This requires practical software engineering discipline layered on top of AI/ML knowledge, a combination that's genuinely uncommon even among strong AI students.

Our Take:

- 𝐆𝐨𝐨𝐝 𝐟𝐨𝐫: Final-year M.Tech students or recent M.Tech graduates in Computer Science/AI-ML with genuine hands-on experience building 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 and comfort with production engineering practices like testing, evaluation, and deployment

- 𝐍𝐨𝐭 𝐢𝐝𝐞𝐚𝐥 𝐟𝐨𝐫: B.Tech/undergraduate students — explicitly ineligible per this listing's stated requirement; also not ideal for those with only theoretical AI coursework and no hands-on agent-building experience

- 𝐒𝐞𝐥𝐞𝐜𝐭𝐢𝐨𝐧 𝐝𝐢𝐟𝐟𝐢𝐜𝐮𝐥𝐭𝐲: High — the M.Tech-only eligibility already narrows the pool significantly, and the required depth in 𝐚𝐠𝐞𝐧𝐭 𝐨𝐫𝐜𝐡𝐞𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧, 𝐞𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧, 𝐠𝐮𝐚𝐫𝐝𝐫𝐚𝐢𝐥𝐬, and production deployment is genuinely advanced even within that narrower pool

- 𝐂𝐚𝐫𝐞𝐞𝐫 𝐭𝐫𝐚𝐣𝐞𝐜𝐭𝐨𝐫𝐲: commonly leads into 𝐀𝐈 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫, 𝐌𝐋 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫, or 𝐀𝐩𝐩𝐥𝐢𝐞𝐝 𝐀𝐈 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 roles with genuine production deployment experience

𝐂𝐨𝐦𝐩𝐞𝐧𝐬𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐧𝐭𝐞𝐱𝐭: Unisys hasn't disclosed a stipend for this role. AI Engineering internships requiring M.Tech-level qualifications at established global IT companies in Bangalore typically range around ₹30,000–₹50,000/month, based on general market data for comparable advanced AI/ML internships — this is an estimate only.

𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲: Since the listing explicitly asks for public projects or GitHub links to showcase work, make sure you have a genuinely presentable project ready — ideally one that goes beyond model training to include some 𝐝𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 or 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧 element, such as an API wrapper, testing/evaluation harness, or agent orchestration logic, since that directly matches the 𝐛𝐮𝐢𝐥𝐝𝐞𝐫-𝐟𝐨𝐜𝐮𝐬𝐞𝐝 framing.

Roles & Responsibilities

The responsibilities center on taking AI work from experimental to production-grade — a genuine end-to-end builder role rather than isolated research or prototyping work.

- Collaborate with domain experts to convert existing AI pipelines into functional prototypes

- Take promising prototypes through to production-ready projects for enterprise deployment

- Build and iterate on AI agents and supporting harnesses, including orchestration, tooling, evaluation, and guardrails, to make them reliable and testable

- Contribute to engineering practices that keep systems robust, maintainable, and deployable at scale

Qualifications & Eligibility

A hard, explicitly stated restriction — worth confirming eligibility before applying.

- Final-year M.Tech students or recent M.Tech graduates only

- Computer Science, AI/ML, or a related field

- Ability to work in-office and collaborate closely with a cross-functional team

Skills Required

Genuinely advanced technical requirements reflecting the production-focused nature of the role.

- Solid understanding of building AI agents and their supporting harnesses (orchestration, tooling, evaluation, and guardrails)

- Strong programming fundamentals with an empirical, hands-on approach to debugging

- Nice to have: Public projects or GitHub links showcasing your work

- Nice to have: Exposure to cloud platforms such as Azure, AWS, or GCP

- Nice to have: Experience deploying or operating software in enterprise environments