Top Companies Hiring Machine Learning Engineers in Hyderabad

Machine Learning Engineer compensation in India varies by city, company stage, and whether the role is product, platform, or growth-focused. Fixed pay is quoted in LPA (lakhs per annum); variable pay and ESOPs are common at startups. Always clarify fixed vs CTC before negotiating.

Bangalore / Hyderabad: Highest volume of tech roles; senior Machine Learning Engineer bands at top of range.
Mumbai / Delhi NCR: Strong fintech and consumer; premiums for leadership roles.
Pune / Chennai: GCC and enterprise SaaS; competitive base, lower equity upside.
Hyderabad: Factor in cost of living vs Bangalore when comparing offers.

1. Anchor with data from 3+ offers or trusted peers at the same level.
2. Negotiate fixed first; treat variable and ESOP separately.
3. Ask for signing bonus if base is capped.
4. Get the offer letter with break-up (basic, HRA, PF) before resigning.
5. If competing offers exist, share timelines, not numbers, to accelerate decisions.

CTC typically includes: Basic, HRA, special allowance, PF employer contribution, gratuity provision, and projected variable. Ask for in-hand estimate after tax. ESOPs at startups may not appear in CTC, model dilution and vesting cliff separately.

Hyderabad had 27 active Machine Learning Engineer openings as of early July 2026, according to knok jobradar. That places it third among major Indian tech hubs, behind Bangalore (165 openings) and Delhi (50), but well ahead of Mumbai (15), Pune (14), and Chennai (14).

The city's MLE market is a genuine three-way mix: Global Capability Centres (GCCs) set up by multinationals, mid-size product companies and EdTech firms, and early-stage startups. Each bucket offers a different kind of work, a different interview style, and a different growth path. Knowing which environment suits you lets you focus your search rather than spray applications everywhere.

The 10 companies below account for all named Hyderabad openings in this snapshot. Warner Bros Discovery leads with 5 open roles, more than any other single employer in this list.

GCC corner: Warner Bros Discovery, Amgen, and Cornerstone appear to run GCC-style operations in Hyderabad. Work here typically means contributing to global ML platforms rather than building India-only products. These roles tend to be more structured, come with stronger benefits, and have clearer promotion tracks. Amgen's presence is particularly notable: pharma and biotech ML work involves specialised datasets (genomics, drug discovery pipelines) that differ meaningfully from mainstream tech ML.

Product and EdTech corner: Ansrsource and ZeMoSo represent companies building their own products. ML engineers here usually own a larger slice of the pipeline, from data cleaning to model deployment. Ansrsource's EdTech focus means domain-specific work in recommendation systems, adaptive learning, and content relevance.

Startup corner: aquaexchange, perceptyne, and Ritually are the startups in this list. aquaexchange operates in the agri-tech space, which means unusual real-world datasets and genuinely unsolved ML problems. Smaller team size means you will likely wear multiple hats, but you will also ship features faster and have your name on work that matters.

The data snapshot for this role does not include salary figures, so treat what follows as directional context from publicly reported sources only. Glassdoor and levels.fyi commonly cite a wide compensation range for Machine Learning Engineers in Hyderabad, with the spread depending on years of experience, ML specialisation, and company type.

GCC vs startup pay structures: Industry surveys and publicly reported data suggest GCCs like Amgen and Warner Bros Discovery tend to offer stronger fixed pay and better structured benefits. Startups like aquaexchange or perceptyne may offer a lower base CTC but include ESOPs that could add meaningful value if the company grows. Always ask for a full breakdown: base, variable, joining bonus, ESOPs, and medical cover.

Specialisation premium: Publicly reported salary data from levels.fyi commonly shows higher compensation for engineers with hands-on MLOps, LLM fine-tuning, or production-grade model deployment experience versus those with only research or academic project exposure. Naming your specific stack clearly in your resume and interviews makes a real difference at offer time.

Hyderabad's MLE job market is smaller than Bangalore's but also less crowded with applicants. That is an advantage if you position yourself well.

Match your profile to the company type: For GCC roles at Warner Bros Discovery or Amgen, highlight experience with large-scale systems, cross-functional collaboration, and any prior global team exposure. For startups like aquaexchange or perceptyne, focus on your ability to work with messy real-world data, ship quickly, and own end-to-end ML workflows. For Infosys, structured delivery and client communication experience help.

Make your production experience visible: Many MLE candidates list projects and research papers but bury the one thing hiring managers care most about: did you actually deploy a model that people used? If yes, say so clearly in your resume summary, mention the scale, and describe the business impact in plain terms.

Pick a credible specialisation: Being a generalist is fine for junior roles, but once you have a few years in, narrowing your pitch to NLP, computer vision, recommendation systems, or MLOps makes you far easier to shortlist. Hyderabad's employer mix points to demand for MLOps (GCCs running large pipelines), pharma-domain ML (Amgen), and agri-tech data work (aquaexchange).

Keep your GitHub active: Several Hyderabad ML teams, especially at product companies and startups, look at GitHub before the first call. Even one clean, well-documented project with a working demo is worth more than a list of bullet points on a resume.

With only 27 openings active at any given time in Hyderabad, you cannot afford to miss a posting or apply late. Many MLE roles in this city fill within a couple of weeks of going live.

Apply in the first week: The further you are from the posting date, the more filtered the pile gets. Set up job alerts on LinkedIn and Naukri for 'Machine Learning Engineer Hyderabad' and check daily. If you spot a role from any company in the table above, treat it as time-sensitive.

Customise your resume per company type: A single generic resume will underperform. Keep two versions: one that leads with scale and system reliability (for GCCs), and one that leads with ownership and end-to-end delivery (for startups). Swap in the most relevant projects depending on the role.

Do not skip the cover note or LinkedIn message: For smaller companies like perceptyne or Ritually, a short, specific message to the hiring manager or founder explaining why you are interested in their particular problem can separate you from applicants who just clicked 'Apply'. Keep it under five sentences and reference the actual product or domain.

Widen your net without wasting time: Beyond the 10 companies in this list, Hyderabad has more MLE openings spread across smaller firms and newer startups that do not always surface on a single job board. knok checks 150+ job sites nightly, matches openings to your resume, applies on your behalf, and messages HR directly. At ₹2,500 a month, it is worth running in parallel while you also do your own active search.