1

Amazon Data Annotation Jobs in New York (NOW HIRING)

... Amazon, McKinsey, Bain, Stanford, Caltech, and MIT. Learn more at www.turing.com The Role You will ... class data integrity on every project * Own quality control across the annotation lifecycle: set ...

Improve data processing , annotation workflows , and ML system efficiency * Deploy and maintain the ... High-achieving team, including ex-Amazon engineers and alumni of Bain, BCG, Goldman Sachs, and more ...

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

Improve data processing , annotation workflows , and ML system efficiency * Deploy and maintain the ... High-achieving team, including ex-Amazon engineers and alumni of Bain, BCG, Goldman Sachs, and more ...

Amazon Data Annotation information

See New York salary details

$10

$26

$48

How much do amazon data annotation jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for amazon data annotation in New York is $26.34, according to ZipRecruiter salary data. Most workers in this role earn between $18.40 and $32.59 per hour, depending on experience, location, and employer.

How much do Amazon data annotation jobs pay?

Amazon data annotation jobs typically pay between $12 and $20 per hour, depending on experience, location, and task complexity. These roles often require attention to detail and familiarity with annotation tools, and may offer flexible schedules for remote work.

What are the key skills and qualifications needed to thrive in the Amazon Data Annotation position, and why are they important?

To thrive as an Amazon Data Annotation specialist, you need keen attention to detail, accuracy, and proficiency in data labeling or annotation, often supported by a background in data entry or related fields. Familiarity with annotation tools, Amazon’s proprietary data platforms, and in some cases basic understanding of programming languages or machine learning concepts is beneficial. Strong communication skills, adaptability, and the ability to work independently or with minimal supervision help individuals excel in the role. These abilities are crucial for ensuring high-quality, reliable data that supports Amazon’s AI and machine learning initiatives.

What is an Amazon Data Annotation job?

An Amazon Data Annotation job involves labeling or tagging data such as text, images, audio, or videos to improve machine learning models. Annotators follow specific guidelines to provide accurate labels that help refine Amazon's AI systems, including Alexa and product recommendations. This work is often detail-oriented and may require understanding context, language nuances, or specific industry knowledge. The role can be full-time or contract-based and may involve remote or on-site work, depending on the project.

Does Amazon really pay you to work from home?

Amazon Data Annotation jobs are typically remote positions that pay employees for their work from home. Compensation varies based on the role and hours worked, and employees are usually paid through direct deposit on a regular schedule. These jobs often require attention to detail and familiarity with annotation tools.

What does a typical day look like for an Amazon Data Annotation specialist?

A typical day as an Amazon Data Annotation specialist involves reviewing, labeling, and annotating diverse datasets, such as images, videos, or text, using specialized software and following detailed guidelines. You may collaborate with team members or project leads to clarify instructions and ensure consistency across annotations. Periodic quality checks and feedback sessions are common, helping you refine your work and maintain high standards. While much of the work is independent, clear communication and responsiveness are important for meeting project deadlines and successfully supporting Amazon’s AI development goals.

What is annotation in Amazon?

In the context of Amazon data annotation jobs, annotation involves labeling or tagging data such as images, videos, or text to help train machine learning models. Workers use specialized tools to add accurate labels, which are essential for improving AI systems' performance. Attention to detail and understanding of the data are important for this role.

Does data annotation actually pay well?

Data annotation jobs, including roles like Amazon Data Annotation, typically offer hourly wages that are close to minimum wage or slightly above, depending on the employer and location. Pay rates can vary based on the complexity of tasks, required skills, and whether the work is freelance or full-time, but generally do not provide high salaries. Many positions are suitable for entry-level workers and may include flexible schedules or remote work options.
What are the most commonly searched types of Amazon Data Annotation jobs in New York? The most popular types of Amazon Data Annotation jobs in New York are:
What are popular job titles related to Amazon Data Annotation jobs in New York? For Amazon Data Annotation jobs in New York, the most frequently searched job titles are:
Infographic showing various Amazon Data Annotation job openings in New York as of July 2026, with employment types broken down into 95% Full Time, and 5% Contract. Highlights an 84% In-person, 5% Hybrid, and 11% Remote job distribution, with an average salary of $54,793 per year, or $26.3 per hour.

Senior Scientist, Computational Biology & Data Infrastructure

Kingdom

New York, NY • On-site

$132K - $160K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 14 days ago


Job description

OVERVIEW
Kingdom is building the world's first AI-native functional ingredients company, with $40M+ in venture funding from top investors. We've pioneered Superculture® ingredients: an entirely new class of clinically validated postbiotics, made from natural microbes, that target the root causes of unmet health needs for people and pets. We're launching one new clinically backed ingredient every year.
We're looking for a high-performing Senior Scientist, Computational Biology & Data Infrastructure, to join our small but mighty team. This is an AI-native science role: you'll own the computational backbone of Kingdom's research (the microbial genomics and AI-compatible data infrastructure that every wet-lab program depends on) and ship custom and integrated LLM tooling to automate and accelerate our work. We want a PhD-level computational biologist (or related area) who applies rigorous scientific judgment to genomic analysis, biobank strategy, and statistical methods, and is equally excited to build the systems that let everyone move faster. Fundamentally, this is a science role, with success measured by the integrity of our data, the insights our data infrastructure unlocks, and the AI tooling we deploy across our scientific platform.
Our edge starts with one of the world's largest, most diverse biobanks of proprietary microbial strains, sourced from natural foods and environmental sources. On top of it, we've built a scientific platform spanning ingredient discovery, clinical trials, and manufacturing scale-up that lets our small team outcompete companies 100X+ our size.
We're actively selling Superculture® Pet Oral and Superculture® Pet Immune to pet food and supplement brands. Less than a year in market, our ingredients are already powering dozens of products from leading pet brands, with overwhelmingly positive customer reception. One in three product launches using our ingredients has earned a #1 New Release on Amazon, and nine in ten of our customers are launching additional products with us.
Now we're scaling rapidly. We'll launch our first Superculture ingredient for humans later this year, opening up an entirely new market. And we're expanding internationally, starting with the EU/UK and China, with Australia/New Zealand and other APAC markets on the horizon.
This is a full-time, in-person role at our headquarters in Brooklyn, NY.
RESPONSIBILITIES
In this role, you'll report to the Senior Scientific Director, and will work closely with our science team & co-founders to:
Own genomic analyses and biobank strategy:
  • Run computational genomic safety analyses and author the supporting reports that underpin our regulatory and customer-facing safety documentation
  • Maintain the whole-genome sequencing pipeline: assembly of incoming sequencing data, linkage of genomes to strain records, and curation of best-available assemblies for downstream use
  • Own and operate the strain dereplication pipeline, advancing isolated colonies from primary 16S/ITS screening through unique-strain identification and entry into the biobank
  • Design and curate screening plates for downstream functional assays, including layout, strain selection, and verification of taxonomy and safety annotations

Build and own Kingdom's AI-compatible scientific data infrastructure:
  • Build AI-compatible data infrastructure for Kingdom that captures, stores, and analyzes data across a variety of modalities
  • Develop and apply statistical and computational methods to power biological insights and support wet-lab workflows, including experimental design, metric development and validation, and method onboarding, powered with new AI/agentic tools
  • Maintain the integrity of the strain database backend: tube tracking, naming conventions, and audits of our physical inventory and pipeline data to identify anomalies
  • Model complex, interrelated scientific entities (samples, experiments, runs, results, physical inventory) into a coherent schema and ontology the team can work in
  • Scope, build, and ship the data processing, analysis, and metrics that give new assays clear, validated benchmarks

COMPETENCIES & QUALIFICATIONS
  • PhD (or equivalent depth) in computational biology, bioinformatics, microbial genomics, or a related quantitative life-sciences field; ~1-3 years post-PhD
  • Domain depth in microbial genomics: whole-genome sequencing, 16S/ITS amplicon analysis, dereplication, taxonomy, and genomic safety annotation
  • Strong knowledge of statistics and quantitative methods
  • Advanced coding literacy: expert-level Python or R, proficiency with SQL, fluency with containerization for reproducible pipelines, comfort building tools that interact with third-party APIs, and strong code-quality practices (version control, testing, code review)
  • Experience designing and maintaining bio-data infrastructure: proficiency modeling complex interrelated entities and comfort establishing and communicating an ontology
  • AI-native: daily Claude Code or equivalent use, prompt fluency, comfort rebuilding research cadence around agentic tools, with experience building tooling around your own research
  • High agency: self-starter who identifies pain points, proposes a plan and solution, and drives their own learning
  • Builder mentality: comfortable with building a first version of a tool fast, and iterating to improve
  • Bias to actionable output: instinct to package findings into something concrete that unblocks decisions and moves the next step forward
  • Clear and effective written and verbal communication

WHY JOIN KINGDOM
  • Meaningful work: contribute to a category-defining biotech company at the frontier of postbiotic science.
  • Growth and learning: Kingdom's scientific AI and data-infrastructure function is still being defined, so you'll have real influence over what it becomes. Because the role supports every wet-lab program, you'll gain broader exposure to microbial science and ingredient development.
  • Ownership and autonomy: inherit a functioning biobank infrastructure and a working genomic-safety pipeline; AI data infrastructure: substantive work from day one, with substantial latitude to shape the platform. Early and sustained exposure to the Chief Science Officer.
  • Team and culture: small but mighty team that's high-performing, kind, and AI-native.

OUR VALUES
  • Solve from first principles. We have a deep-seated curiosity about the most important problems facing the business. Our nature is to dig deeply into their details, question assumptions, understand the smallest details, and drive towards the best possible solution using these insights. This makes us very effective in crafting new solutions and operating in ambiguous circumstances.
  • Collaborate with kindness. We are exceptionally low ego, and treat each other with respect, compassion, and humility. We hold one another to high standards, but do so while being deeply committed to each other's wellbeing. We invest in each other's growth, and are willing to engage in difficult conversations and deliver direct, constructive feedback when necessary.
  • Be resourceful and resilient. We figure out how to make things work, and how to accomplish our goals regardless of what stands in the way. We're keen to confront challenges together through proactive planning and scrappy methods. When things go wrong, we learn quickly from our missteps, adapt our approach, and push forward.

COMPENSATION AND BENEFITS
To build a world-class team, Kingdom is transparent and generous with our compensation package. We anchor cash salary above market-rate compensationfor your role, and go above and beyond with equity stock options, as we want everyone to be aligned with and benefit from our long-term success.
For this position, we are most actively considering candidates at the Senior Scientist level (PhD with ~1-3 years of post-PhD experience; cash salary range: $132.5K-$160K). This does not include stock options, which we'll discuss during the interview process.
Kingdom additionally offers an excellent benefits package including:
  • 100% fully-covered, best-in-class medical, vision, and dental insurance for yourself (and 95% for your spouse/family)
  • Generous and flexible PTO, in addition to 13 company-wide holidays
  • Full commuter coverage
  • Fully stocked kitchen with fruits, snacks, and beverages + weekly team lunches
  • 12-weeks fully-paid parental leave
  • 401k program with minimal fees