Manager, Applied Science, Minerva

Amazon is hiring a Manager, Applied Science, Minerva in Bengaluru, India. Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this role Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include Python, fine tuning and computer vision.
Level classifies it as a lead role.
Level lists 21,000+ other open roles at Amazon.
The role was posted in the last few days.

AI in this role

Applied Science Manager to build and lead a risk science team developing ML, NLP, and computer vision models to detect fraud and abuse.

python

fine-tuningcomputer-visionnlpmachine-learningrisk-modelingteam-management

We are looking for an Applied Science Manager to build and lead Minerva's first Risk Science team in Bengaluru. This is a hands-on role: you will collaborate with scientists in the US to set the scientific bar and advance how we detect and respond to risk across KDP and Kindle Unlimited.

Key job responsibilities
- Hire, develop, and retain a high-performing team of applied scientists across levels, and set its practices for experimentation, evaluation, reviews, publishing, and patents.

- Push the quality of production risk models higher: set the standard for how model performance is measured, and lead the deep-dive science that turns model behavior into better detection.

- Develop new and improved detection models for fraud, abuse, copyright infringement, and harmful content, using NLP, computer vision, LLMs, and behavioral and graph-based modeling.

- Partner with engineering, product, policy, and investigation teams in the US and India to turn findings into fixes, and present options, risks, and tradeoffs to senior leaders.

- Work with the US science team to divide ownership clearly and share methods across Minerva.

About the team
Kindle Direct Publishing (KDP) has empowered a new wave of self-motivated creators, tearing down barriers that once blocked writers from reaching readers. Minerva is the science and analytics organization for Amazon's Books business. We build systems for content understanding, author marketing and discovery, fraud and abuse prevention, and content risk, and we optimize manufacturing, fulfillment, and quality for Print On Demand (POD). We have mature areas and green-field opportunities, with engineering, business intelligence, and data engineering support across our areas. We are now building science teams in Bengaluru that work closely with our scientists in the US. Risk Science, a team within Minerva, keeps fraud, abuse, copyright infringement, and harmful content out of the Books catalog and programs such as Kindle Unlimited, using text, image, and behavioral data.

Basic qualifications

- 3+ years of scientists or machine learning engineers management experience
- PhD, or Master's degree and 6+ years of building machine learning models or developing algorithms for business application experience
- Excellent communication skills, capable of discussing technical details with a variety of audiences and influencing decision-making processes.
- Experience writing, reviewing, and testing production code in Python or a related language
- Experience shipping machine learning, NLP, or computer vision models to production and maintaining their quality after launch

Preferred qualifications

- Experience leading teams in the areas of fraud detection, abuse prevention, and content risk management within a digital or e-commerce environment.
- Experience with model monitoring, data drift detection, calibration, or causal analysis of model behavior
- Experience with graph-based ML, behavioral modeling, or real-time detection
- Experience with LLMs, fine-tuning, embeddings, or multimodal models
- Experience building a new team, including hiring across several levels
- PhD in computer science, machine learning, statistics, or a related quantitative field, or publications at top-tier peer-reviewed venues (for example KDD, NeurIPS, ICML, ACL, CVPR) or patents
- Experience leading teams that build with AI coding agents, with guardrails such as tests, automated review, and verifiable done criteria

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

How we rate this

Manager, Applied Science, Minerva at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Manager, Applied Science, Minerva is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in IN, KA, Bengaluru.
The job was posted on October 29, 2026.
Seniority: lead.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Fine-tuningComputer visionNLPMachine learningRisk ModelingTeam ManagementPython

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where risk modeling was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Fine-tuning, Computer vision, NLP, Machine learning, and Risk Modeling. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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