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GenAI & MLOps Jobs in India: AI Match Scores for LLM & Platform Roles
GenAI hiring in India exploded faster than job titles could standardize — ML engineer, GenAI engineer, MLOps IC, applied scientist, LLM platform — often with overlapping but unequal stack bars. FeedbackAI ranks GenAI and MLOps listings by AI match score: skills met vs missing, experience level, work mode, and salary band fit. Company pages add Glassdoor ratings, salary benchmarks, and interview notes when enriched. Upload your resume, browse /jobs and Career Insights for rising GenAI tags, and apply where match scores and pay realism align — PRACTICE assessments are optional, not a gate to seeing listings.
Why keyword search fails for GenAI/MLOps
Filtering "GenAI jobs Bengaluru" returns roles that mention ChatGPT once alongside unrelated full-stack or data analyst postings.
Match scoring compares your resume to each job's required ML stack and seniority — separating research-heavy applied scientist loops from product MLOps ownership when listing data supports it.
Signals that move your GenAI/MLOps match score
- Model stack — Python, PyTorch/TensorFlow, Hugging Face, fine-tuning, evaluation.
- GenAI product — RAG, LangChain/LlamaIndex, prompt engineering, guardrails, latency/cost tradeoffs.
- MLOps/platform — Kubernetes, CI/CD for models, feature stores, observability, AWS/GCP ML services.
- Experience depth — shipped models vs notebooks-only; on-call for production ML when role requires it.
- Compensation fit — expected salary vs role band when benchmark data exists.
Use Career Insights + company pages together
Rising skills on /career-insights show aggregate employer demand for GenAI tags — use trends to upskill, match scores to prioritize applications today.
On /companies, check salary tables for ML titles and interview difficulty when enriched before committing to multi-week loops.
Related: salary and interview intel
Pay bands by seniority — compare expected salary to enriched medians: https://www.feedbackai.live/blog/bengaluru-pay-bands-by-seniority and https://www.feedbackai.live/blog/salary-benchmarks-matched-jobs-india
Interview loops and prep time — https://www.feedbackai.live/blog/company-interview-process-india and https://www.feedbackai.live/blog/interview-difficulty-company-fit-india
Honest boundaries
Match scores rank fit — not offers or model access. Not every employer is fully enriched. We do not invent culture or salary data. Optional PRACTICE does not replace employer formal assessments.
Frequently asked questions
- How does FeedbackAI match GenAI and MLOps roles?
- Match scores weigh ML/GenAI stack (Python, PyTorch/TensorFlow, LLM tooling, RAG, MLOps/Kubernetes), years of experience, location, work mode, and salary band fit — not buzzword keyword spam.
- Does FeedbackAI list LLM engineer and MLOps titles separately?
- Yes where synced — ML Engineer, MLOps Engineer, GenAI Engineer, Applied Scientist, LLM Platform Engineer, and related IC listings across India hubs and remote.
- Do I need a PhD to rank well on GenAI roles?
- Not automatically. Match scores weight demonstrated stack depth and experience level from your resume — research credentials help when listed but are not the only signal.
- Can I see salary benchmarks for ML and MLOps roles?
- Where Glassdoor salary enrichment exists, match explainability can show median bands by title — compare against your expected pay before long loops.
- Are assessments required to browse GenAI job matches?
- No. Matched jobs are visible after signup. PRACTICE mode is optional; employers may attach formal assessments separately.
Upload your resume and browse AI-ranked ML roles with skill gaps and company context.
See GenAI & MLOps Matches — FreeSee live GenAI and MLOps tags from active job listings on Career Insights.
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