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Software Engineer ( Machine Learning Ops )

Ntst · Bengaluru, India

How to use this kit

Ground every answer in facts on this page and the original listing. We never invent Glassdoor-style reviews or salaries that are not in our data.

Interview prep

Expect system-design and requirements questions: feasibility under constraints, collaborating with managers and engineers on interfaces, and how you would install, modify, or maintain software systems. Be ready to discuss MLOps concerns—deployment, reliability, and stakeholder communication—using concrete past work.

Fit summary

Strong fit if you enjoy building and operating software systems end-to-end, translating user needs into designs, and coordinating installs and changes with cross-functional teams. On-site in Bengaluru; thin company DATA means culture and stack details need employer confirmation.

Day in the role

As a Software Engineer (Machine Learning Ops) at Ntst, a typical day centers on productionizing ML systems: clarifying requirements with analysts and product owners, assessing feasibility under time and cost limits, coordinating installs and changes, and aligning with engineers on interfaces, performance, and operational constraints.

Skills to emphasize

FAQ from this listing

Is this role remote?

No. The listing marks remote as 0, with location Bengaluru, India.

What occupation family does this map to?

DATA maps it to software developers (SOC 15-1252.00), including analysis, design, and installation tasks.

Where can I learn for free?

CERTS lists free or free-to-learn paths from freeCodeCamp, Saylor, CS50, and Microsoft Learn.

Occupation tasks (O*NET)

Public-domain labor data — prepare examples for 2–3 of these.

O*NET source

Company facts (cached)

Website: ntst.com

Public cache only — not an employee review.

Role overview (listing rewrite)

Ntst invites applications for a Software Engineer ( Machine Learning Ops ) based in Bengaluru, India. This full-time opportunity centres on building reliable systems that take machine learning models from development into stable production use. About the Role The Software Engineer ( Machine Learning Ops ) position at Ntst in Bengaluru, India places you at the intersection of software engineering and operational machine learning Workflows. You will help create and sustain the platforms that train, deploy and monitor models while working closely with cross-functional colleagues. Ntst is hiring for this role and offers a supportive team environment. Full-time colleagues in this capacity play an essential part in keeping machine learning services performant and reproducible for internal users. What You'll Do Design and implement automated pipelines that support model training, packaging and release cycles Collaborate with data science and platform teams to productionise machine learning solutions reliably Establish continuous integration and delivery practices tailored to machine learning artefacts and data Monitor live model performance, set up logging and alerting, and address operational issues promptly Improve infrastructure components so that machine learning workloads remain scalable and cost-efficient Document processes and shared tooling so that other engineers can adopt consistent MLOps standards Qualifications Solid background as a software engineer with practical exposure to machine learning operations Strong skills in Python and familiarity with common machine learning libraries and frameworks Hands-on knowledge of container technologies, orchestration systems and cloud-native services Understanding of version control for code, models and datasets together with reproducible experiment methods Ability to communicate clearly with peers and contribute effectively within a Bengaluru-based team Interest in keeping pace with evolving MLOps practices and tooling Why Join Ntst Ntst is hiring for this role and offers a supportive team environment. As a Software Engineer ( Machine Learning Ops ) in Bengaluru, India you will grow your expertise while delivering systems that matter to the organisation and its users. Apply Today To apply, complete your application directly on this page, or you'll be redirected to the employer's application platform to finish submitting there.

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Questions to ask them

Generated for personal interview prep · 2026-07-17 UTC · getajob.ai