AI Product Manager – KAI (KGeN)

Weblink: https://kgen.io/, KAI: https://kai.kgen.io/

Location: Bangalore, India

Team: KAI – Training & Evaluation

Role Overview

We are hiring a Product Manager focused on AI data platforms, speech workflows, and scalable voice data systems.

This role involves building structured data production pipelines, annotation tooling, and QA systems for frontier AI companies.

You will work closely with engineers and TPMs to solve real operational challenges in data collection, tagging, and delivery.

This is not a PRD-only role.

You will research business problems, identify workflow bottlenecks, and work directly with engineers to design and ship tooling that improves data quality, speed, and reliability.

You’ll think outside-in — from the perspective of clients, data collectors, and annotators — and continuously improve systems that power AI training datasets.

Key Responsibilities

• Define and improve data collection → annotation → QA → delivery workflows
• Translate client requirements into structured execution plans
• Identify inefficiencies in contributor and annotator systems
• Work with engineers to build internal automation and tooling
• Track metrics like acceptance rate, QA scores, turnaround time

Model Evaluation & Quality Systems

• Define dashboards, leaderboards, and reporting for model performance.
• Work with ML Research Engineers to establish metrics like IoU, mAP, WER, CER, DER, BLEU, and ROUGE.
• Use model evaluation insights to shape feature decisions and fallback logic.

Technical Product Requirements

• Manage backlog, sprints, and cross-functional delivery with engineering.
• Define KPIs for quality, turnaround time, model performance, and cost per task.

Data-Driven Decisions

• Use SQL/BigQuery/Athena and dashboards to analyze quality, throughput, and performance.
• Identify bottlenecks and opportunities for automation or ML enhancement.
• Validate feature impact using metrics-based analysis.

Required Qualifications

• 2-6 years of product management experience, with at least 1+ years in AI/ML-driven products.
• Strong understanding of core ML concepts (classification, detection, embeddings, multimodal models, model evaluation).

Hands-on experience with annotation tools such as:

• Label Studio
• SuperAnnotate
• Labelbox
• Encord
• CVAT
• Experience defining and shipping workflow-heavy or operations-heavy products.
• Working knowledge of SQL and data analysis tools.
• Experience working with ML engineers or applied research teams.

Preferred Experience

• Managed or built workflows for annotation, quality control, or HITL pipelines.
• Experience designing consensus systems, reviewer pipelines, or routing logic.
• Familiarity with HuggingFace, OpenAI, or cloud-based ML platforms.
• Exposure to multimodal data (images, audio, text, video).
• Previous startup or fast-moving tech environment experience.

What Success Looks Like

• Measurable reduction in annotation cost through model-assisted workflows.
• Improved accuracy and throughput for annotation teams.
• Smooth end-to-end workflows supporting thousands of annotators.
• Timely delivery of high-impact AI features aligned with KAI’s roadmap.