software engineer

ai engineer

ai/ml engineer (entry position) Jobs in New York

ai/ml engineer (entry position)

machine learning engineer - fraud risk Jobs in New York

machine learning engineer - fraud risk

software engineer (backend) Jobs in New York

software engineer (backend)

machine learning engineer

Rain

<div><h2 class="jobSectionHeader">About the Company</h2>
Rain makes the next generation of payments possible across the globe. We&rsquo;re a lean and mighty team of passionate builders and veteran founders. Our infrastructure makes stablecoins usable in the real-world by powering card transactions, cross-border payments, B2B purchases, remittances, and more. We partner with fintechs, neobanks, and institutions to help them launch solutions that are global, inclusive, and efficient. You will have the opportunity to deliver massive impact at a hypergrowth company that is funded by some of the top investors in fintech, crypto, and SaaS, including Sapphire Ventures, Norwest, Galaxy Ventures, Lightspeed, Khosla, and several more. If you&rsquo;re curious, bold, and excited to help shape a borderless financial future, we&rsquo;d love to talk.<h2 class="jobSectionHeader">
Our Ethos</h2>
We believe in an open and flat structure. You will be able to grow into the role that most aligns with your goals. Our team members at all levels have the freedom to explore ideas and impact the roadmap and vision of our company.<h2 class="jobSectionHeader">
About the Team</h2>
The fraud risk management team at Rain creates sophisticated, scalable risk mitigation solutions to protect our customers and deliver a low-friction experience. We achieve this by maintaining transaction and lifecycle event monitoring, building alerts to speed fraud detection and response, and creating risk rules and strategies powered by ML models. We are a pillar of the business, supporting new products and ensuring their success. Rain&rsquo;s next-generation payment technology introduces new fraud vectors that require holistic, end-to-end thinking, strong data fundamentals, and fraud management savvy to combat.<h2 class="jobSectionHeader">
What you&rsquo;ll do</h2><ul><li>
Architect and build scalable ML systems for fraud detection, anomaly detection, and behavioral analysis</li><li>
Develop and maintain end-to-end ML pipelines: data ingestion, feature engineering, model training, deployment, and continuous monitoring</li><li>
Design and implement low-latency, real-time decision systems partnering with fraud risk data scientists, integrating with transaction or behavioral data streams</li><li>
Own ML infrastructure, including model versioning, automated retraining, and safe deployment strategies (e.g., shadow, rollback).</li><li>
Build robust monitoring and alerting for model performance, latency, data quality, and drift</li><li>
Lead experimentation on model explainability, drift detection, and adversarial robustness for fraud prevention use cases</li><li>
Develop tooling and processes to improve the effectiveness and speed of the ML development lifecycle</li><li>
Partner with platform teams to meet strict SLAs for availability, latency, and accuracy</li><li>
Collaborate closely with talented engineers, data scientist and compliance teams across Rain</li><li>
Work in a fast-paced environment on a rapidly growing product suite.</li><li>
Solve complex problems at the intersection of ML systems, data, and reliability</li></ul><h2 class="jobSectionHeader">
What we're looking for</h2><ul><li>
5+ years of experience building ML systems in production; at least 2+ in fraud, risk, or anomaly detection domains</li><li>
A degree in Computer Science, Engineering, Statistics, Applied Math, or a related technical field</li><li>
Proven track record designing and maintaining ML models at scale</li><li>
Advanced proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)</li><li>
Strong understanding of supervised/unsupervised learning, anomaly detection, and statistical modeling</li><li>
Ability to work autonomously, manage ambiguity, and collaborate closely with data scientists to translate analytical models into robust fraud prevention systems</li><li>
Experience developing, validating, and productionalizing predictive real-time and offline fraud detection models using supervised and unsupervised ML techniques.</li><li>
Experience collaborating with cross-functional teams to prioritize, scope, and deploy MLI solutions at scale</li></ul><h2 class="jobSectionHeader">
Nice to have, but not mandatory</h2><ul><li>
Domain expertise in banking, payments, or transaction monitoring</li><li>
Experience with graph-based or network-level fraud detection techniques</li><li>
A graduate degree in Computer Science, Engineering, Statistics, Applied Math, or a related technical field</li><li>
Experience fine-tuning or adapting generative AI / large language models for pattern generation or synthetic data augmentation (in partnership with data science)</li><li>
Knowledge of model governance, bias mitigation, and regulatory compliance in fraud contexts</li></ul><h2 class="jobSectionHeader">
Things that enable a fulfilling, healthy, and happy experience at Rain:</h2><ul><li>
Unlimited time off Unlimited vacation can be daunting, so we require Rainmakers to take at least 10 days off.</li><li>
Flexible working We support a flexible workplace. If you feel comfortable at home, please work from home. If you&rsquo;d like to work with others in an office, feel free to come in. We want everyone to be able to work in the environment in which they are their most confident and productive selves. New Rainmakers will receive a stipend to create a comfortable home environment.</li><li>
Easy to access benefits For US Rainmakers, we offer comprehensive health, dental, and vision plans for you and your dependents, as well as a 100% company subsidized life insurance plan.</li><li>
Retirement goalsPlan for the future with confidence. We offer a 401(k) with a 4% company match.</li><li>
Equity plan We offer every Rainmaker an equity option plan so we can all benefit from our success.</li><li>
Rain Cards We want Rainmakers to be knowledgeable about our core products and services. To support this mission, we issue a card for our team to use for testing.</li><li>
Health and Wellness High performance begins from within. Rainmakers are welcome to use their card for eligible health and wellness spending like gym memberships/fitness classes, massages, acupuncture - whatever recharges you!</li><li>
Team summits Summits play an important role at Rain! Time spent together helps us get to know each other, strengthen our relationships, and build a common destiny. Expect team and company off-sites both domestically and internationally.</li></ul>
Compensation Range: $187K - $258.7K</div>

Machine Learning Engineer - Fraud Risk

Millennium Management

<div><div><div>Job Description</div></div><div><div><div><div>
AI Engineer
We are working on different areas where AI/ML can help portfolio managers, researchers, risk managers, and other functions. Some examples are: enabling traders/researchers to consume vast amounts of research and literature by organizing, summarizing information, sometimes in near real-time; doing quantitative modeling to price instruments, modeling demand and supply of commodities and other fundamentals; modeling weather, optimizing algorithmic execution of trades; modeling and building simulations of risk.
The AI/ML work spans usage of LLMs, deep learning, reinforcement learning and other ML techniques. The work also requires building AI/ML infrastructure for data wrangling, building feature stores, building frameworks for deployments, measurements, re-training, etc.
We are seeking a AI/ML SWE who has experience with LLMs, deep learning, reinforcement learning as well as an interest and ability to keep up with advancements in AI/ML. The candidate should also be strong in software engineering and be comfortable with AI/ML experimentation and productionization.
Key Responsibilities<ul><li>
Engage and collaborate with business stakeholders, quants, and other market researchers to deeply understand the problem space.</li><li>
Experiment, iterate, productionize AI/ML solutions.</li><li>
Build supporting data and AI/ML infrastructure and tools.</li></ul>
Required Skills and Qualifications<ul><li>
Bachelor&rsquo;s degree in Computer Science or a related field</li><li>
5+ years of professional experience with python</li><li>
Strong knowledge of the latest advancements in AI and machine learning.</li><li>
Strong fundamentals in computer science.</li><li>
Proficiency in Python and at least 1 other language such as Java, C++, C#, etc.</li><li>
Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud).</li><li>
Experience with using LLMs and with techniques such as prompt engineering, PEFT, fine-tuning, etc.</li><li>
Ability to build and evaluate AI models and tools using quantifiable metrics.</li><li>
Excellent problem-solving skills and ability to work independently as well as part of a team.</li><li>
Strong communication skills to effectively collaborate with developers and other stakeholders.</li><li>
Adaptable and willing to work in a start-up-like environment within a major institution.</li></ul>
Preferred Qualifications<ul><li>
Advanced degree in Computer Science, AI, Machine Learning, or a related field.</li><li>
Experience in developing AI solutions for financial institutions.</li><li>
Knowledge of additional programming languages and frameworks.</li></ul><div><div><div><div><div><div>
The estimated base salary range for this position is $175,000 to $250,000, which is specific to New York and may change in the future. Millennium pays a total compensation package which includes a base salary, discretionary performance bonus, and a comprehensive benefits package. When finalizing an offer, we take into consideration an individual&rsquo;s experience level and the qualifications they bring to the role to formulate a competitive total compensation package.</div></div></div></div></div></div></div></div></div></div></div>

AI Engineer

Pragmatike

<div>
 
 Location:
 
 Cambridge, MA (Eastern Time / UTC -4) ﻿
 
 Relocation package available
 
 
 
 
 Relocation package:
 
 Available
 
 
 
 Start date:
 
 ASAP
 
 
 
 Languages:
 
 English (required)
 
 
 
 About The Role
 
 
 
 Pragmatike is hiring on behalf of a fast-growing AI startup recognized as a
 
 Top 10 GenAI company by GTM Capital
 
 , founded by
 
 MIT CSAIL researchers
 
 .
 
 
 We are looking for an
 
 AI/ML Engineer (Entry Position)
 
 to join a growing AI engineering team building and deploying real-world AI systems used by
 
 Fortune 500 customers
 
 . You will work closely with senior AI, ML, and platform engineers on the development, optimization, and deployment of machine learning models in production environments.
 
 
 This role is intended for engineers with
 
 early professional experience
 
 who already have hands-on exposure to applied machine learning and want to grow quickly by working on real, production-scale AI systems.
 
 
 
 What Youll Do
 
 
 
 <ul>
 <li>
 Build, train, and evaluate machine learning models in collaboration with senior engineers
 </li>
 <li>
 Contribute to deploying ML models into production systems
 </li>
 <li>
 Work with structured and unstructured datasets to support training and inference pipelines
 </li>
 <li>
 Improve model performance, reliability, and scalability through experimentation
 </li>
 <li>
 Implement and maintain ML code primarily in Python
 </li>
 <li>
 Monitor model behavior and assist in debugging production issues
 </li>
 <li>
 Participate in model iteration, validation, and performance analysis
 </li>
 <li>
 Collaborate with backend and platform teams to integrate AI components into products
 
 
 </li>
 </ul>
 
 What Were Looking For
 
 
 
 <ul>
 <li>
 Bachelors or Masters degree in Computer Science, Engineering, Mathematics, or a related field
 </li>
 <li>
 2+ years of professional experience working on AI, ML, or data-driven systems (industry, research, or applied internships)
 </li>
 <li>
 Excellent academic background, including strong grades and demonstrated university-level achievements
 </li>
 <li>
 Evidence of academic or professional excellence, such as scholarships, honors, awards, competitive programs, or impactful projects
 </li>
 <li>
 Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics)
 </li>
 <li>
 Hands-on experience with ML libraries such as PyTorch, TensorFlow, or scikit-learn (required)
 </li>
 <li>
 Strong proficiency in Python
 </li>
 <li>
 Strong problem-solving skills and the ability to work independently
 
 
 </li>
 </ul>
 
 Bonus Points
 
 
 
 <ul>
 <li>
 Experience with deep learning, LLMs, or modern AI architectures
 </li>
 <li>
 Experience working with real-world, noisy datasets in production
 </li>
 <li>
 Familiarity with cloud platforms (AWS, GCP, or Azure)
 </li>
 <li>
 Exposure to MLOps tools, model deployment, or monitoring
 </li>
 <li>
 Publications, research experience, or participation in AI/ML competitions
 
 
 </li>
 </ul>
 
 Why This Role Will Pivot Your Career
 
 
 
 <ul>
 <li>
 Learn from MIT CSAIL&ndash;founded leadership and experienced AI engineers
 </li>
 <li>
 Work on AI systems deployed to Fortune 500 customers
 </li>
 <li>
 Apply strong academic and early professional experience to high-impact AI problems
 </li>
 <li>
 Clear growth path toward mid-level and senior AI engineering roles
 </li>
 <li>
 Join a well-funded, fast-growing AI startup with strong technical ambition
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Competitive salary &amp; equity options
 </li>
 <li>
 Sign-on bonus
 </li>
 <li>
 Health, Dental, and Vision
 </li>
 <li>
 401(k)
 
 
 </li>
 </ul>
 ﻿
 
 
 
 
 Pragmatike
 
 is an Equal Opportunity Employer and is committed to providing equal employment opportunities to all applicants without discrimination. We recruit on behalf of our clients and prohibit discrimination and harassment based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.We are committed to a fair and inclusive hiring process. We process your personal data solely for recruitment purposes, in accordance with applicable privacy laws, and maintain reasonable safeguards to protect your information. Your data may be shared with our client(s) for hiring consideration, but will not be disclosed to third parties outside of the recruitment process.
 
 
 
</div>

AI/ML Engineer (Entry Position)

Cohere

<div>
 
 Who are we?
 
 
 
 Our mission is to scale intelligence to serve humanity. We&rsquo;re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.
 
 
 We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what&rsquo;s best for our customers.
 
 
 Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.
 
 
 Join us on our mission and shape the future!
 
 
 
 Why this role?
 
 
 
 As an Evaluation Frontend Software Engineer, you will play a key role in helping us make modelling decisions based on experimental outcomes for our large language models (LLMs). Your primary focus will be on building tools to enable easy visualization and analysis of model evaluations which are stored in a central database. You will work closely with cross-functional teams, including researchers and engineers, to surface the insights that are necessary for the future development of our models.
 
 
 This role combines expertise in statistics, data science, frontend development and data visualization. If any of these topics sound interesting to you, we encourage you to apply.
 
 
 
 Please Note: We have offices in London, Paris, Toronto, San Francisco, and New York, but we also embrace being remote-friendly! There are no restrictions on where you can be located for this role.
 
 
 
 
 As a Evaluation Frontend Software Engineer You Will
 
 
 
 <ul>
 <li>
 Design tools and visualizations that enable researchers and engineers to compare and analyse hundreds of model evaluations. This includes both data visualization tools, as well as statistical tools to extract signal from the noisy signals we get.
 </li>
 <li>
 Develop an understanding of the relative merits and limitations of each of our model evaluations, as well as suggest new facets of model evaluation.
 
 
 </li>
 </ul>
 
 You May Be a Good Fit If You Have
 
 
 
 <ul>
 <li>
 Extremely strong software engineering skills.
 </li>
 <li>
 Strong statistical skills and experience evaluating scientific experiments related to data collection and model performance.
 </li>
 <li>
 Prior experience building front-end visualization systems and dashboards.
 </li>
 <li>
 Familiarity with ML systems evaluations.
 </li>
 <li>
 Proficiency in programming languages such as Python and ML frameworks (e.g., PyTorch, TensorFlow, JAX).
 </li>
 <li>
 Excellent communication skills to collaborate effectively with cross-functional teams and present findings.
 </li>
 <li>
 One or more papers at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).
 
 
 </li>
 </ul>
 If some of the above doesn&rsquo;t line up perfectly with your experience, we still encourage you to apply!
 
 
 We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.
 
 
 
 Full-Time Employees At Cohere Enjoy These Perks
 
 
 
 🤝 An open and inclusive culture and work environment
 
 
 🧑&zwj;💻 Work closely with a team on the cutting edge of AI research
 
 
 🍽 Weekly lunch stipend, in-office lunches &amp; snacks
 
 
 🦷 Full health and dental benefits, including a separate budget to take care of your mental health
 
 
 🐣 100% Parental Leave top-up for up to 6 months
 
 
 🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
 
 
 🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
 
 
 ✈️ 6 weeks of vacation (30 working days!)
</div>

Software Engineer, Evaluation Frontend

Oscar Health

<div>Hi, we're Oscar. We're hiring a Data Scientist II to join our Data team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves&mdash;one that behaves like a doctor in the family.

About the role:

Oscar's data team is focused on pushing our understanding of this complex landscape of health insurance. Insurance companies sit on a trove of data that is both broad and deep, spanning financial claims, clinical medical records, and rich product interaction data from our members. Connecting the dots across these datasets gives us unique insight into how the healthcare system functions and allows us to improve care coordination, better manage risk, build higher-performing provider networks, and create a standout consumer experience in our product.

As a Data Scientist II, you will partner closely with our Market P&amp;L, Tech and Legal teams to develop models and tooling to better understand Oscar's medical costs across its networks. You will develop a deep understanding of healthcare reimbursement and use various data sources to inform negotiations, establish reimbursement for out-of-network providers, and help manage medical costs for Oscar members.

You will report into the Senior Data Scientist.

Work Location: This position is based in our New York City office, requiring a hybrid work schedule with 3 days of in-office work per week. Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid

Pay Transparency: The base pay for this role is: $131,200 - $172,200 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, company equity grants, and annual performance bonuses.

Responsibilities:
<ul>
<li>Responsible for the creation, implementation, and maintenance of data pipelines. This includes ensuring the accuracy, reliability, and timeliness of data flow with the support of a manager.</li>
<li>Support upkeep and enhancement of our models. This involves regular model testing, validation, and refinement to ensure the models remain effective and up-to-date with the latest industry standards and practices.</li>
<li>Develop advanced analytics and validation checks on data and statistical model outputs under the review of a manager at critical points. This includes identifying potential issues, anomalies, or inconsistencies in the data, and implementing corrective measures to ensure the integrity of our models and analyses.</li>
<li>Collaborate closely with data leaders and business teams to enhance overall data processes. This involves understanding their needs and requirements, providing them with the necessary data support, and working together to develop strategies and solutions that improve our risk adjustment processes and outcomes.</li>
<li>Ensures processes and policies are aligned with departmental strategies and roadmaps</li>
<li>May mentor junior data scientists and/or analysts</li>
<li>Compliance with all applicable laws and regulations</li>
<li>Other duties as assigned</li>
</ul>
Requirements:
<ul>
<li>3+ years of industry or other quantitative technical fields (which may include academia).</li>
<li>2+ years of work experience working with SQL, R, and/or Python to query, manipulate and analyze data</li>
<li>2+ years experience building data models, using more advanced analytics methods, statistical modeling, and/or data processing</li>
</ul>
Bonus points:
<ul>
<li>Masters degree in a quantitative or technical field</li>
<li>Knowledge of or previous work experience in health care or health insurance</li>
</ul><div>
This is an authentic Oscar Health job opportunity. Learn more about how you can safeguard yourself from recruitment fraud here.

At Oscar, being an Equal Opportunity Employer means more than upholding discrimination-free hiring practices. It means that we cultivate an environment where people can be their most authentic selves and find both belonging and support. We're on a mission to change health care - an experience made whole by our unique backgrounds and perspectives.

Pay Transparency: Final offer amounts, within the base pay set forth above, are determined by factors including your relevant skills, education, and experience. Full-time employees are eligible for benefits including: medical, dental, and vision benefits, 11 paid holidays, paid sick time, paid parental leave, 401(k) plan participation, life and disability insurance, and paid wellness time and reimbursements.

Artificial Intelligence (AI): Our AI Guidelines outline the acceptable use of artificial intelligence for candidates and detail how we use AI to support our recruiting efforts.

Reasonable Accommodation: Oscar applicants are considered solely based on their qualifications, without regard to applicant's disability or need for accommodation. Any Oscar applicant who requires reasonable accommodations during the application process should contact the Oscar Benefits Team (accommodations@hioscar.com) to make the need for an accommodation known.

California Residents: For information about our collection, use, and disclosure of applicants' personal information as well as applicants' rights over their personal information, please see our Privacy Policy.</div></div>

Data Scientist II: Networks and Contracts

Unify

<div><h2 class="jobSectionHeader">About Unify</h2>
Unify was founded in 2023 by Austin Hughes and Connor Heggie. Prior to Unify, Austin led Ramp&rsquo;s growth product team focused on new customer acquisition, and Connor was a machine learning research engineer at Scale AI. The rest of our team comes from companies like Airbnb, Spotify and Retool.
Our mission is to build the first system-of-action for go-to-market teams, starting with an end to end platform powering warm outbound. Today, outbound sales is dominated by cold, mass outreach that floods people's inboxes and converts to deals at a tiny rate. We&rsquo;re building a platform to power warm outbound, allowing go-to-market teams to get in touch with the right people at the exact time they&rsquo;re looking for a solution.
We scaled ARR 5x in 2025, and are already serving customers like Cursor, Perplexity, Together.AI, Justworks, Flock Safety, and more. We&rsquo;re a high energy, high intensity team and we&rsquo;ve raised $58M from Thrive, Emergence, OpenAI, Battery and others. Come join us in changing how go-to-market works.<h2 class="jobSectionHeader">
About the Role</h2>
Unify is building the system of action for go-to-market teams, and we believe growth should be engineered. We&rsquo;re looking for a Head of Growth to architect and scale the growth engine that powers Unify&rsquo;s next phase of growth.
This is a role reporting directly to our CEO Austin Hughes with full ownership of pipeline generation and self-serve revenue. Austin previously was a growth leader at Ramp. You&rsquo;ll run growth like a product team - roadmaps, experiments, velocity, and metrics - not a collection of one-off tactics. You&rsquo;ll scale our existing channels 10x, and incubate new ones.
Your mandate is ambitious and clear: create overwhelming demand for Unify, scale pipeline 4x+ over the next year, and build a durable growth machine that compounds.<h2 class="jobSectionHeader">
What You&rsquo;ll Do</h2><ul><li>
Own growth outcomes end-to-end
Own pipeline generation and self-serve revenue goals, and be accountable for results at the exec and board level.</li><li>
Run growth like a product team
Establish an experimentation-driven culture with clear hypotheses, fast iteration cycles, and rigorous measurement.</li><li>
Scale and incubate new channels
Build, scale, and optimize growth across automated outbound, inbound, PLG, paid, AEO/SEO, and incubate new channels.</li><li>
Be a power user of Unify and a partner to our product team
Dogfood Unify daily and act as a critical voice in improving onboarding, activation, conversion, and self-serve monetization. Partner deeply with Product to turn insights into shipped improvements.</li><li>
Drive demand for our new self-serve offering
Own the strategy and execution to make self-serve revenue 20%+ of net new cohorts, while staying tightly aligned with sales to avoid cannibalization.</li><li>
Build and lead the growth org
Hire, develop, and retain a world-class growth team. Set clear ownership, high standards, and a culture of accountability and learning.</li></ul><h2 class="jobSectionHeader">
What You&rsquo;ll Need</h2><ul><li>
5&ndash;10 years of experience in growth, marketing, or PLG roles at high-growth technology companies.</li><li>
Deep expertise in 2+ growth channels or surface areas (e.g. outbound, PLG, paid, SEO, lifecycle, partnerships), with the ability to delve into new channels.</li><li>
Proven track record of building a winning growth team over multiple years.</li><li>
Strong experience running an experiment-driven growth team and running growth more like a product team than a traditional marketing team.</li><li>
Demonstrated ability to hire and lead high-performing, high-velocity teams and develop strong functional leaders.</li><li>
Systems-oriented, execution-biased, and comfortable making high-conviction decisions with imperfect data.</li><li>
Fluency with modern growth, analytics, and GTM tooling (e.g. Unify). Dashboarding and data analysis should be core competencies.</li></ul><h2 class="jobSectionHeader">
Additional Information</h2>
The annual salary range for this role is $220,000-$275,000, with a target equity package and comprehensive benefits, including medical, dental, vision, and 401(k) options. This position is onsite in either San Francisco, CA, or New York City, NY, offering the invaluable opportunity to work closely with a talented team in a dynamic, high-energy environment. Being in-person enables real-time collaboration, fosters creative problem-solving, and strengthens the connections that drive innovation and impact. You'll be at the center of our fast-paced operations, contributing to a culture that values engagement, growth, and teamwork.</div>

Head of Growth

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
The Sponsored Products and Brands (SPB) team at Amazon Ads is transforming advertising through generative AI technologies. We help millions of customers discover products and engage with brands across Amazon.com and beyond. Our team combines human creativity with artificial intelligence to reinvent the entire advertising lifecycle&mdash;from ad creation and optimization to performance analysis and customer insights. 
 
We develop responsible AI technologies that balance advertiser needs, enhance shopping experiences, and strengthen the marketplace. Our team values innovation and tackles complex challenges that push the boundaries of what's possible with AI. 
 
Join us in shaping the future of advertising. 
 
Key job responsibilities 
This role will redesign how ads create personalized, relevant shopping experiences with customer value at the forefront. Key responsibilities include: 
 
<ul><li>Design and develop solutions using GenAI, deep learning, multi-objective optimization and/or reinforcement learning to transform ad retrieval, auctions, whole-page relevance, and shopping experiences.</li><li>Partner with scientists, engineers, and product managers to build scalable, production-ready science solutions.</li><li>Apply industry advances in GenAI, Large Language Models (LLMs), and related fields to create innovative prototypes and concepts.</li><li>Improve the team's scientific and technical capabilities by implementing algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling.</li><li>Mentor junior scientists and engineers to build a high-performing, collaborative team.</li></ul> 
A day in the life 
As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced&mdash;elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon&rsquo;s rich data and the world&rsquo;s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science. 
 
About the team 
The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon&mdash;such as product detail pages, the homepage, and store-in-store pages&mdash;to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack&mdash;from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences&mdash;all designed to deliver meaningful value.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>3+ years of building machine learning models for business application experience</li><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Strong foundation in GenAI, large language models, machine learning, deep learning, probabilistic modeling, and/or optimization.</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Demonstrated expertise in Generative AI technologies, including foundation models, LLMs, and model customization for specific business applications</li><li>Hands-on experience building ads ranking, retrieval, recommendation, or personalization systems that operate at web scale</li><li>Technical proficiency in advanced AI approaches such as multi-modal modeling, few-shot learning, retrieval-augmented generation (RAG), or reinforcement learning from human feedback (RLHF)</li><li>Track record of designing and implementing online experimentation frameworks, including A/B testing methodologies and performance metrics for advertising or e-commerce</li><li>Proven ability to translate complex technical concepts into clear explanations for diverse audiences, from engineers to executives</li><li>Deep knowledge of computational advertising fundamentals, including auction mechanisms, advertising economics, and advertiser success metrics</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
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&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
 
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Senior Applied Scientist, Sponsored Products and Brands, Off-Search

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