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Capabilities

Every capability employers ask for — and who pays for it

68 capabilities named in job postings across 17 roles, and the few you need on the way. The number on each row is the strongest ask: the share of one role's postings that name it. Not a list of everything that exists — a list of what is being hired for.

Cloud, deployment & production

7 capabilities

Secure keys, auth and data in AI apps

Secrets management, IAM least privilege, OAuth, tenant isolation, audit logs.

~8hintermediateasked for by 1 role
Strongest askAI Security Engineer98%

Troubleshoot and support AI systems in production

Own L1-L3 tickets for an AI product or platform: read logs and traces, reproduce model and API failures, follow the runbook, escalate with a clean root-cause note and close within SLA.

~24hbeginnerasked for by 1 role
Strongest askAI Support Engineer88%

Deploy an AI service to the cloud

Ship an LLM/ML API on Cloud Run / AWS Lambda-ECS / Azure with HTTPS, env config and logs.

~12hintermediateasked for by 6 roles
Strongest askAI Support Engineer72%

Automate builds, tests and deploys with CI/CD

GitHub Actions pipelines that test, build images and deploy on merge.

~6hintermediateasked for by 5 roles
Strongest askAI Quality Assurance / GenAI Test Engineer63%

Containerize an application with Docker

Write Dockerfiles, compose services, manage env/secrets, publish images.

~9hbeginnerasked for by 3 roles
Strongest askMachine Learning Engineer35%

Run workloads on Kubernetes

Deployments, services, scaling, and GPU scheduling basics for model serving.

~15hadvancedasked for by 2 roles
Strongest askMachine Learning Engineer35%

Use managed AI platforms (Bedrock / Vertex / Azure AI Foundry)

Provision models, manage IAM, use platform features (knowledge bases, guardrails, agents) on one hyperscaler.

~12hintermediateasked for by 3 roles
Strongest askAI Support Engineer16%

Machine learning & data science

8 capabilities

Build image models (detection/classification)

OpenCV + pretrained CNN/YOLO fine-tuning for a practical vision task.

~20hintermediateasked for by 2 roles
Strongest askComputer Vision Engineer99%

Train and evaluate classical ML models

Scikit-learn workflow: features, train/test split, cross-validation, metrics, overfitting.

~40hintermediateasked for by 6 roles
Strongest askMachine Learning Engineer99%

Build and train neural networks in PyTorch

Tensors, autograd, training loops, transfer learning, GPU usage.

~40hintermediateasked for by 3 roles
Strongest askComputer Vision Engineer83%

Operate an ML pipeline (train → register → serve → monitor)

MLflow/SageMaker/Vertex pipelines, model registry, batch/online serving, drift monitoring.

~25hadvancedasked for by 2 roles
Strongest askMachine Learning Engineer66%

Fine-tune an open LLM (LoRA/QLoRA)

Prepare instruction data, run PEFT fine-tuning on a small model, evaluate against the base.

~20hadvancedasked for by 1 role
Strongest askMachine Learning Engineer25%

Forecast time series

Seasonality, ARIMA/Prophet/gradient boosting, backtesting for demand/finance use cases.

~12hintermediatenot named in any job posting yet — on the map, not on any path

Build a recommendation or ranking model

Collaborative filtering, embeddings-based retrieval, offline ranking metrics.

~15hintermediatenot named in any job posting yet — on the map, not on any path

Solve NLP tasks (classification, NER, similarity)

Tokenization, transformers via Hugging Face, fine-tune small encoders for classification/NER.

~20hintermediatenot named in any job posting yet — on the map, not on any path

Product, business & communication

10 capabilities

Apply responsible-AI and data-protection basics

Bias, transparency, consent, DPDP Act/GDPR basics, model documentation.

~6hbeginnerasked for by 8 roles
Strongest askAI Governance & Compliance Analyst100%

Discover and scope AI product opportunities

Identify where models add value, assess feasibility/data readiness, write an AI PRD with success metrics.

~15hintermediateasked for by 1 role
Strongest askAI Product Manager100%

Run a customer discovery → POC → pilot loop

Scope a POC with a client, build/adapt it fast, demo it, handle objections, hand over to production.

~20hadvancedasked for by 3 roles
Strongest askAI Solutions / Pre-sales Engineer88%

Explain how LLMs work and where they fail

Tokens, context, hallucination, RAG vs fine-tuning, cost drivers — well enough to make decisions with engineers.

~8hbeginnerasked for by 11 roles
Strongest askAI Search Optimization Specialist87%

Design and deliver AI training sessions

Turn a GenAI or ML topic into a session plan — slides, a hands-on lab and an assessment — and deliver it to a classroom or corporate cohort, tracking completion in an LMS.

~20hbeginnerasked for by 1 role
Strongest askAI Technical Trainer / Instructor85%

Translate business requirements into an AI solution design

Discovery, BRD/FRD, process mapping, solution architecture diagrams and success criteria.

~15hintermediateasked for by 5 roles
Strongest askAI Solutions / Pre-sales Engineer75%

Communicate AI trade-offs to stakeholders

Write and present clearly about risk, cost, timelines and limitations; run demos and reviews.

~8hbeginnerasked for by 10 roles
Strongest askAI Solutions / Pre-sales Engineer70%

Define quality metrics and eval plans for AI features

Choose offline/online metrics, design human-rating rubrics, set launch bars for AI features.

~10hintermediateasked for by 2 roles
Strongest askAI Product Manager56%

Deliver technical demos and answer RFPs

Build demo environments, tailor narratives per persona, write technical responses to RFP/RFI.

~10hintermediateasked for by 2 roles
Strongest askAI Solutions / Pre-sales Engineer42%

Prototype an AI feature without an engineering team

Build a clickable/working prototype with no-code tools, prompt playgrounds or AI coding assistants.

~10hbeginnerasked for by 1 role
Strongest askAI Product Manager25%

Annotation, quality & human feedback

7 capabilities

Label data accurately against guidelines

Read a labeling spec, apply it consistently (text/image/audio), flag ambiguous cases.

~6hbeginnerasked for by 1 role
Strongest askAI Data Annotator / Labeling QA94%

Audit label quality and compute agreement

Sampling, inter-annotator agreement, error taxonomies, feedback to annotators.

~8hintermediateasked for by 1 role
Strongest askAI Data Annotator / Labeling QA78%

Annotate and evaluate in an Indian language

Be the native-language expert on a dataset: label, transcribe, rate and culturally adapt content in Hindi, Tamil, Bengali, Malayalam or another Indian language, and judge whether a model's output is fluent, accurate and culturally appropriate for that audience.

~8hbeginnerasked for by 1 role
Strongest askAI Data Annotator / Labeling QA59%

Evaluate AI outputs as a domain expert

Use professional expertise (healthcare, BFSI, law, software, geospatial) to judge whether a model's answer is correct in that field, and write a rationale a non-expert reviewer can follow. This is what separates low-paid labelling from expert evaluation work.

~10hintermediateasked for by 2 roles
Strongest askAI Data Annotator / Labeling QA34%

Evaluate and rank model responses (RLHF / preference data)

Compare responses for helpfulness, accuracy, safety; write rationales; follow rubrics.

~9hbeginnerasked for by 2 roles
Strongest askAI Data Annotator / Labeling QA32%

Write labeling guidelines and evaluation rubrics

Turn a vague quality goal into a rubric with examples and edge cases that others can apply.

~8hintermediateasked for by 4 roles
Strongest askAI Data Annotator / Labeling QA19%

Work in annotation tools (Label Studio / CVAT / Labelbox)

Set up projects, hotkeys, bounding boxes/segmentation/NER, export formats.

~6hbeginnerasked for by 2 roles
Strongest askAI Data Annotator / Labeling QA13%

Shares are per role: the percentage of that role's job postings in India that name any skill mapped to the capability. Counting rules are on the methodology page; the full table is open data. Prefer to start from a job? All 17 roles →