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

ai/ml engineer (entry position)

associate machine learning engineer Jobs in New York

associate machine learning engineer

client services intern

digital influencer intern Jobs in New York

digital influencer intern

machine learning engineer - fraud risk Jobs in New York

machine learning engineer - fraud risk

machine learning intern

Software Engineer, Machine Learning

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)

PitchBook

<div><div>At PitchBook, a Morningstar company, we are always looking forward. We continue to innovate, evolve, and invest in ourselves to bring out the best in everyone. We're deeply collaborative and thrive on the excitement, energy, and fun that reverberates throughout the company.

Our extensive learning programs and mentorship opportunities help us create a culture of curiosity that pushes us to always find new solutions and better ways of doing things. The combination of a rapidly evolving industry and our high ambitions means there's going to be some ambiguity along the way, but we excel when we challenge ourselves. We're willing to take risks, fail fast, and do it all over again in the pursuit of excellence.
If you have a good attitude and are willing to roll up your sleeves to get things done, PitchBook is the place for you.</div>

About the Role:

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other's words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us!

PitchBook's Associate Machine Learning Engineer is responsible for using machine learning, statistical modeling, and Natural Language Processing (NLP) to collect a high-volume of data for the PitchBook Platform and surface insights for the capital markets. This role requires curiosity and a strong desire to learn. A strong motivation to succeed is critical and everyone has the opportunity to shape the long-term direction of our team.

Primary Job Responsibilities:
<ul>
<li>Use natural language processing (NLP) and machine learning techniques to create novel views of private industry data</li>
<li>Analyze and extract features from large amounts of unstructured data, determine most relevant features, and use clustering algorithms to drive insight into the data</li>
<li>Analyze textual data such as articles and conversations to identify novel signals of private company performance</li>
<li>Work closely with Product and Engineering teams to establish scalable, efficient, and automated processes for large scale data analyses and models</li>
<li>Contribute to thought leadership on Data Science and Machine Learning best practices by staying informed of current trends in industry</li>
<li>Support the vision and values of the company through role modeling and encouraging desired behaviors</li>
<li>Participate in various company initiatives and projects as requested</li>
</ul>
Skills and Qualifications:
<ul>
<li>Bachelor's degree in Computer Science, Machine Learning, Statistics, or related field</li>
<li>Experience in a similar role in a production environment</li>
<li>Experience or exposure with natural language processing (NLP)</li>
<li>Experience or exposure with Python, R, or other relevant programming frameworks</li>
<li>Experience or exposure in using SQL for data extraction</li>
<li>Strong communication and data presentation skills</li>
<li>Strong problem-solving ability</li>
<li>Ability to communicate complex analysis in a clear, precise, and actionable manner</li>
<li>Experience working closely a with software development team(s) a plus, but not required</li>
<li>Financial services, investment, banking, venture capital and/or private equity knowledge, but not required</li>
<li>Must be authorized to work in the United States without the need for visa sponsorship now or in the future</li>
</ul>
Benefits + Compensation at PitchBook:

Physical Health
<ul>
<li>Comprehensive health benefits</li>
<li>Additional medical wellness incentives</li>
<li>STD, LTD, AD&amp;D, and life insurance</li>
</ul>
Emotional Health
<ul>
<li>Paid sabbatical program after four years</li>
<li>Paid family and paternity leave</li>
<li>Annual educational stipend</li>
<li>Ability to apply for tuition reimbursement</li>
<li>CFA exam stipend</li>
<li>Robust training programs on industry and soft skills</li>
<li>Employee assistance program</li>
<li>Generous allotment of vacation days, sick days, and volunteer days</li>
</ul>
Social Health
<ul>
<li>Matching gifts program</li>
<li>Employee resource groups</li>
<li>Subsidized emergency childcare</li>
<li>Dependent Care FSA</li>
<li>Company-wide events</li>
<li>Employee referral bonus program</li>
<li>Quarterly team building events</li>
</ul>
Financial Health
<ul>
<li>401k match</li>
<li>Shared ownership employee stock program</li>
<li>Monthly transportation stipend</li>
</ul>
<ul><li>Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.</li></ul>

Compensation
<ul>
<li>Annual base salary: $110,000-$150,000</li>
<li>Target annual bonus percentage: 7.5%</li>
</ul>
Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments&mdash;those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices&mdash;that simply can't be replicated remotely. This role is expected to be in the office 5 days a week.

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-MS1

#LI-Onsite</div>

Associate Machine Learning Engineer

<div><div>At PitchBook, a Morningstar company, we are always looking forward. We continue to innovate, evolve, and invest in ourselves to bring out the best in everyone. We're deeply collaborative and thrive on the excitement, energy, and fun that reverberates throughout the company.

Our extensive learning programs and mentorship opportunities help us create a culture of curiosity that pushes us to always find new solutions and better ways of doing things. The combination of a rapidly evolving industry and our high ambitions means there's going to be some ambiguity along the way, but we excel when we challenge ourselves. We're willing to take risks, fail fast, and do it all over again in the pursuit of excellence.
If you have a good attitude and are willing to roll up your sleeves to get things done, PitchBook is the place for you.</div>

About the Role:

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other's words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us!

As a Senior Machine Learning Engineer (MLE) on the AI &amp; ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook's wealth of structured and unstructured data including reports, news, and other textual content. This role requires deep technical expertise in advanced data analytics and machine learning, as well as a hands-on approach to designing, building, and optimizing ML solutions that power user-facing features on the PitchBook Platform.

You will be deeply involved in the end-to-end development and operationalization of ML models, including their architecture, training, deployment, and ongoing maintenance. Your focus will span across natural language processing (NLP), generative AI (GenAI), large language models (LLMs), and scalable data systems. You will be expected to tackle complex technical challenges, contribute to architectural decisions, and collaborate closely with other engineers, data scientists, and product managers to ensure that your work aligns with business goals and AI/ML strategy.

Your contributions will help unlock unique value for PitchBook customers by improving the speed, discoverability, quality, and quantity of insights available on the platform. This includes developing models that can infer meaning and structure from millions of discrete data sources, and applying ML to enrich our datasets with predictive and generative intelligence. As a senior engineer, you will take ownership of key technical components and ensure that our systems meet the highest standards of performance, reliability, and security.

Primary Job Responsibilities:
<ul>
<li>Deliver high-impact AI and ML capabilities that drive insight generation on the PitchBook Platform. Ensure your work contributes to broader business goals and is aligned with the team's strategic priorities</li>
<li>Provide hands-on expertise in designing, building, and deploying AI/ML models and services with a focus on NLP, summarization, semantic search, classification, and prediction. Contribute to the development of scalable, high-performance systems that meet production-grade reliability and efficiency standards</li>
<li>Support a culture of technical excellence by mentoring peers, sharing knowledge, and participating in code and design reviews. Promote innovation and continuous improvement through collaborative engineering practices</li>
<li>Build and optimize models that leverage classifiers, transformers, LLMs, and other NLP techniques to generate meaningful insights from structured and unstructured data. Integrate these models into the broader AI/ML infrastructure in collaboration with partner teams</li>
<li>Collaborate with engineering, product management, and data collection teams to ensure models are informed by high-quality data and support strategic product goals</li>
<li>Explore and experiment with emerging technologies, methodologies, and tools in the fields of GenAI, NLP, and search. Translate research findings into practical solutions that enhance PitchBook's AI capabilities</li>
<li>Contribute to best practices in model transparency, monitoring, evaluation, and compliance. Help maintain high standards of security, data integrity, and responsible AI use across your projects</li>
<li>Participate in the technical evaluation of candidates and help onboard new team members by contributing to documentation, pairing, and knowledge-sharing practices</li>
<li>Apply principles from Agile, Lean, and Fast-Flow methodologies to support efficient model development and deployment cycles</li>
<li>Support the vision and values of the company through role modeling and encouraging desired behaviors</li>
<li>Participate in various company initiatives and projects as requested</li>
</ul>
Skills and Qualifications:
<ul>
<li>Bachelor's or advanced degree in Computer Science, Mathematics, Data Science, or a related technical field, advanced degree preferred</li>
<li>6+ years of experience in software engineering or machine learning engineering, with a strong focus on AI/ML applications in insight generation, summarization, semantic search, and prediction</li>
<li>Demonstrated expertise in natural language processing (NLP) and machine learning, including hands-on experience with classifiers, transformer models, large language models (LLMs), and widely used ML and data science libraries such as scikit-learn, pandas, numpy, TensorFlow, and PyTorch</li>
<li>Experience delivering production-grade GenAI or LLM-based systems with measurable business impact</li>
<li>Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus</li>
<li>Deep proficiency in building and maintaining scalable data pipelines and distributed systems using technologies such as Apache Kafka, Airflow, and cloud data platforms like Snowflake</li>
<li>Strong programming skills in Python and SQL, with working knowledge of additional languages such as Java or Scala considered a plus</li>
<li>Practical experience with cloud-native development, containerization, and orchestration technologies such as Docker and Kubernetes</li>
<li>Demonstrated ability to solve complex technical problems, contribute to architectural decisions, and deliver high-performance, reliable solutions</li>
<li>Excellent communication and collaboration skills, with experience working cross-functionally with product managers, engineers, and data scientists in globally distributed teams</li>
<li>Experience working in fast-paced, data-driven environments. Prior exposure to fintech or financial data platforms is a strong advantage</li>
<li>Experience authoring research papers for peer-reviewed AI/ML conferences (e.g., NeurIPS, ICML, ACL) and participating in the broader AI research community is strongly preferred</li>
<li>Must be authorized to work in the United States without the need for visa sponsorship now or in the future</li>
</ul>
Benefits + Compensation at PitchBook:

Physical Health
<ul>
<li>Comprehensive health benefits</li>
<li>Additional medical wellness incentives</li>
<li>STD, LTD, AD&amp;D, and life insurance</li>
</ul>
Emotional Health
<ul>
<li>Paid sabbatical program after four years</li>
<li>Paid family and paternity leave</li>
<li>Annual educational stipend</li>
<li>Ability to apply for tuition reimbursement</li>
<li>CFA exam stipend</li>
<li>Robust training programs on industry and soft skills</li>
<li>Employee assistance program</li>
<li>Generous allotment of vacation days, sick days, and volunteer days</li>
</ul>
Social Health
<ul>
<li>Matching gifts program</li>
<li>Employee resource groups</li>
<li>Subsidized emergency childcare</li>
<li>Dependent Care FSA</li>
<li>Company-wide events</li>
<li>Employee referral bonus program</li>
<li>Quarterly team building events</li>
</ul>
Financial Health
<ul>
<li>401k match</li>
<li>Shared ownership employee stock program</li>
<li>Monthly transportation stipend</li>
</ul>
<ul><li>Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.</li></ul>

Compensation
<ul>
<li>Annual base salary: $170,000-$240,000</li>
<li>Target annual bonus percentage: 10%</li>
</ul>
Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments&mdash;those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices&mdash;that simply can't be replicated remotely. This role is expected to be in the office 5 days a week.

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-MS1

#LI-Onsite</div>

Sr. 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

Intuit

<div>Category Data
Location Mountain View, California; New York, New York; Oakland, California
Job ID 18792</div>
 <div><div>Company Overview
<div>Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.
</div></div><div>Job Overview
Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.
Intuit&rsquo;s Consumer Group, including TurboTax and Credit Karma, empowers millions of individuals to take control of their finances. TurboTax simplifies tax preparation and enables our customers to file with confidence. By harnessing the power of data and artificial intelligence (AI), we continuously innovate and evolve our consumer offerings to deliver even greater value.
As we expand our primary banking and lending products, Intuit Credit Karma is looking for an innovative, experienced, and hands-on Staff AI Scientist to join our Consumer Risk AI Science team. In this role, you&rsquo;ll develop cutting-edge credit risk AI/ML fraud models to enable existing and new money movement products. Join a collaborative and inventive team of AI scientists and machine learning engineers where your work will have a direct impact on hundreds of thousands of customers. 
Responsibilities
What you&rsquo;ll do:<ul><li>
Contribute to the fraud risk AI science initiatives for the new and evolving Money product offerings, including complete hands-on ownership of the model lifecycle, sharing ownership of success and key results at the program-level, and driving the modeling strategy across all involved teams.<ul><li>
Design, build, deploy, evaluate, defend, and monitor machine learning models to predict and detect fraud risk for our primary banking product (CK Money) and various short-term lending products (e.g., tax refund advances, FNPL, installment loans, single payment loans, and early wage access)</li><li>
Collaborate with credit policy, product and fraud risk teams to ensure models align with business goals and product offering to drive actionable lending decisions</li><li>
Build efficient and reusable data pipelines for feature generation, model development, scoring, and reporting using Python, SQL, and both commercially available and proprietary Machine Learning and AI infrastructures</li><li>
Deploy models in a production environment in collaboration with other AI scientists and machine learning enginers</li><li>
Ensure model fairness, interpretability, and compliance</li></ul></li><li>
Contribute to the evolution of our data and machine learning infrastructure within the Intuit ecosystem to improve efficiency and effectiveness of AI science solutions.</li><li>
Research and implement practical and creative machine learning and statistical approaches suitable for our fast-paced, growing environment.</li></ul>
What&rsquo;s great about the role:<ul><li>
Solve hard, meaningful problems giving customers (not fraudsters) access to their hard-earned money alongside fun, smart people.</li><li>
Experience professional growth and encourage growth throughout the team.</li><li>
Work cross functionally (with executives, engineering, policy &amp; rules, product, analytics, operations and other AI science teams) to ensure efficient and effective use of data science in ways that make an immediate, substantial, and sustainable impact</li></ul> 
Qualifications
Minimum Basic Requirements:<ul><li>
Advanced Degree (Ph.D. / MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Physics or a related quantitative discipline</li><li>
6+ years of work experience in AI Science / Machine Learning and related areas</li><li>
Authoritative knowledge of Python and SQL</li><li>
Relevant work experience in fintech fraud risk, with deep understanding of money movement products, banking, lending, and fraud detection data</li><li>
Relevant work experience in credit risk and/or financial fraud risk, with deep understanding of payment systems, money movement products, banking, and lending</li><li>
Experience with and deep understanding of developing, deploying, monitoring and maintaining a variety of machine learning techniques, including but not limited to, deep learning, tree-based models, reinforcement learning, clustering, time series, causal analysis, and natural language processing.</li><li>
Deep understanding of fraud risk modeling concepts, including fraud score calibration, label bias correction, case disposition logic, and network or graph-based link analysis for identifying organized or collusive fraud patterns.</li><li>
Ability to quickly develop a deep statistical understanding of large, complex datasets</li><li>
Expertise in designing and building efficient and reusable data pipelines and framework for machine learning models</li><li>
Strong business problem solving, communication and collaboration skills</li><li>
Ambitious, results oriented, hardworking, team player, innovator and creative thinker</li><li>
Proven experience defining and driving end-to-end modeling frameworks, methodologies, or best practices across multiple product teams or domains.</li><li>
Demonstrated ability to evaluate and integrate emerging AI/ML technologies, contributing to the company&rsquo;s external technical visibility and innovation agenda.</li></ul>
Preferred Qualifications:<ul><li>
Proficiency in deep learning ML frameworks such as TensorFlow, PyTorch, etc.</li><li>
Work experience with public cloud platforms (especially GCP or AWS) and workflow orchestration tools like Apache Airflow</li><li>
Strong background in MLOps infrastructure and tooling, particularly Vertex AI or AWS SageMaker, including pipelines, automated retraining, monitoring, and version control</li><li>
Experience with experimentation design and analysis, including A/B testing and statistical analysis.</li></ul> 
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit&reg;: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:
Bay Area California $ 205,500- 278,000
New York $ 201,500- 273,000</div></div>

Staff AI Scientist - Fintech Consumer 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

Explore 156+ Machine learning intern in New York this January. Find roles across top companies and apply now to boost your career.