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staff software engineer, backend Jobs in New York

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machine learning engineer - personalization Jobs in New York

machine learning engineer - personalization

sr machine learning engineer earner growth

Uber

<div><b>About the Role</b>
<br>
<br>
Have you ever ordered a car service on Uber, and when the ride arrives, wondered how it got to you so fast? Ever ordered food on UberEats and wondered where the driver was before receiving your order and how long it took to get to the restaurant or if your order was ready when the courier arrived? Ever wondered why your grocery delivery from Uber always has the best apple picked?
<br>
<br>
If so, Uber is for you. In our ML and Science division, we strive to make magic within Uber's marketplace. This requires judgment to make difficult trade-offs, blending algorithms with human resourcefulness, and the ability to build simplicity from complexity. When we get the balance right for everyone, Uber magic happens. We build systems to peer into the future to craft the most cost-efficient marketplace for matching supply and demand. We are passionate about using innovative economics, machine learning, and scalable distributed software that automates and optimizes every aspect of this intricate dance between participants of the marketplace.
<br>
<br>
We are involved in every stage of the product development cycle and use data to inform product decisions, build models to power our solutions, and also develop platform tools that are used across teams with a primary focus on Mobility and Delivery. We work with millions of earners across the globe to make this magic happen and want you to join us!
<br>
<br>
<b>About the Team</b>
<br>
<br>
Earners (drivers and couriers) are an integral part of Uber's multi-sided marketplace. They provide the time and the means to move people and things. Importantly, they enable the connection between the physical and digital world to make the movement happen at the push of a button for everyone, everywhere.
<br>
<br>
Within Uber, Earner Growth plays a critical role in earners' journey as the team is responsible for earner onboarding, activation, early life cycle, and resurrection. This presents the teams with the opportunity to shape and tailor the product experience during earners' many firsts (i.e., first time interacting on the Uber platform, choosing the earning opportunity, going online, receiving incentive offers, completing a trip, or reading the earnings summary). These firsts can be daunting.
<br>
<br>
Therefore, making sure that the earner journey is great at every touch point is important to build trust with Earners, communicate Uber's value proposition, and ensure each firsts to be a great experience.
<br>
<br>
<b>What You'll Do</b>
<ul><li>Build statistical, optimization, and machine learning models
</li><li>Develop innovative new earner incentives that earners for choosing our network and optimizing Uber's new earner incentives spend
</li><li>Optimize Uber's background check spend and onboarding funnel
</li><li>Design recommendation engines to recommend the most relevant earning opportunities and early lifecycle content
</li><li>Develop matching algorithms for driver to driver mentorship program
</li><li>Model and predict earner behaviors to improve earner experience throughout the onboarding funnel
</li><li>The team employs a variety of ML/AI techniques, spanning from causal ML meta learners, supervised ML, RL multi-armed bandits, genAI LLM to deep learning embeddings to build impactful data products.
</li><li>Work closely with multi-functional leads to develop technical vision, new methodological approaches, and drive team direction.
</li><li>Collaborate with cross-functional teams such as product, engineering, operations, and marketing to drive ML system development end-to-end from conceptualization to final product.
</li></ul><b>Basic Qualifications</b>
<ul><li>PhD or equivalent experience in Computer Science, Machine Learning, Operations Research, Statistics, or other related quantitative fields or related field
</li><li>4 years minimum of industry experience as a Machine Learning Engineer/Research Scientist with a strong focus on deep learning and probabilistic modeling.
</li><li>Proficiency in multiple object-oriented programming languages (e.g. Python, Go, Java, C++).
</li><li>Experience with any of the following: Spark, Hive, Kafka, Cassandra.
</li><li>Experience building and productionizing innovative end-to-end Machine Learning systems.
</li><li>Experience in exploratory data analysis, statistical modeling, hypothesis testing, and experimental design.
</li><li>Experience working with cross-functional teams(product, science, product ops etc).
</li></ul><b>Preferred Qualifications</b>
<ul><li>5+ years of industry experience in machine learning, including building and deploying ML models.
</li><li>Publications at industry recognized ML conferences.
</li><li>Experience in modern deep learning architectures and probabilistic modeling.
</li><li>Experience with optimization techniques, including reinforcement learning (RL), Bayesian methods, causal ML meta learners, genAI LLM.
</li>Expertise in the design and architecture of ML systems and workflows.<br>
<li>
</li></ul><br>
<br>
For New York, NY-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.</div>

Sr. Machine Learning Engineer, Earner Growth

Information Technology Senior Management Forum

<div><div><p>Posted Date</p>
<p>9/15/2025</p>
</div><div><p>Description</p>
<div>Senior Data Scientist, AI Foundations<p>
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.</p><p><br>
As a Data Scientist at Capital One, you&rsquo;ll be part of a team that&rsquo;s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.</p><p><b>
Team Description</b></p><p>
AI Foundations Specialist Models Data Science team builds and ships state of the art scalable architecture, AI/ML solutions for Capital One&rsquo;s award-winning mobile app. We partner with product, tech and design teams to deliver app features that delight customers with dynamic and personalized experiences, enable them to chat with Capital One&rsquo;s digital assistant Eno, or search for useful contents. You will be the driving force to experiment, innovate and create next generation experiences powered by the latest emerging generative AI technologies.</p><p><b>
In this role, you will:</b></p><ul><li>
Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money.</li><li>
Leverage a broad stack of technologies &mdash; Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and more &mdash; to reveal the insights hidden within huge volumes of numeric and textual data.</li><li>
Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for customer facing applications and features.</li><li>
Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers.</li><li>
Flex your interpersonal skills to translate the complexity of your work into tangible business goals.</li></ul><p><b>
The Ideal Candidate is:</b></p><ul><li>
Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it&rsquo;s about making the right decision for our customers.</li><li>
Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.</li><li>
Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You&rsquo;re not afraid to share a new idea.</li><li>
A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond.</li><li>
Technical. You&rsquo;re comfortable with advanced ML and DL technologies including language models and are passionate about developing further. You have hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms.</li><li>
Influential. You are passionate about AI/ML and can bring along a cross functional team in breakthrough innovations. You communicate clearly and effectively to share your findings with non-technical audiences.</li><li>
You are experienced in training language models or large computer vision models as well as have expertise in one or more key subdomains such as: training optimization, self-supervised learning, explainability, RLHF.</li><li>
You have an engineering mindset as shown by a track record of delivering models at scale both in training data and inference volumes. You have experience in delivering libraries, platforms, or solution level code to existing products.</li></ul><p><b>
Basic Qualifications:</b></p><ul><li>
Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:<ul><li>
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics</li><li>
A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration</li></ul></li></ul><p><b>
Preferred Qualifications:</b></p><ul><li>
Master&rsquo;s Degree in &ldquo;STEM&rdquo; field (Science, Technology, Engineering, or Mathematics), or PhD in &ldquo;STEM&rdquo; field (Science, Technology, Engineering, or Mathematics)</li><li>
Experience working with AWS</li><li>
At least 2 years&rsquo; experience in Python, Scala, or R</li><li>
At least 2 years&rsquo; experience with machine learning</li><li>
At least 2 years&rsquo; experience with SQL
</li></ul><p>Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.</p><p>
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.</p>
New York, NY: $145,100 - $165,600 for Sr Assoc, Data Science<br>
<p></p>
San Jose, CA: $145,100 - $165,600 for Sr Assoc, Data Science<p></p><p><br>
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.</p>
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.<p>
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.</p>
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.<p>
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.</p><p>
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com</p><p>
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.</p><p>
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</p>
Senior Data Scientist, AI Foundations<p>
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.</p><p><br>
As a Data Scientist at Capital One, you&rsquo;ll be part of a team that&rsquo;s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.</p><p><b>
Team Description</b></p><p>
AI Foundations Specialist Models Data Science team builds and ships state of the art scalable architecture, AI/ML solutions for Capital One&rsquo;s award-winning mobile app. We partner with product, tech and design teams to deliver app features that delight customers with dynamic and personalized experiences, enable them to chat with Capital One&rsquo;s digital assistant Eno, or search for useful contents. You will be the driving force to experiment, innovate and create next generation experiences powered by the latest emerging generative AI technologies.</p><p><b>
In this role, you will:</b></p><ul><li>
Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money.</li><li>
Leverage a broad stack of technologies &mdash; Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and more &mdash; to reveal the insights hidden within huge volumes of numeric and textual data.</li><li>
Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for customer facing applications and features.</li><li>
Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers.</li><li>
Flex your interpersonal skills to translate the complexity of your work into tangible business goals.</li></ul><p><b>
The Ideal Candidate is:</b></p><ul><li>
Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it&rsquo;s about making the right decision for our customers.</li><li>
Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.</li><li>
Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You&rsquo;re not afraid to share a new idea.</li><li>
A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond.</li><li>
Technical. You&rsquo;re comfortable with advanced ML and DL technologies including language models and are passionate about developing further. You have hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms.</li><li>
Influential. You are passionate about AI/ML and can bring along a cross functional team in breakthrough innovations. You communicate clearly and effectively to share your findings with non-technical audiences.</li><li>
You are experienced in training language models or large computer vision models as well as have expertise in one or more key subdomains such as: training optimization, self-supervised learning, explainability, RLHF.</li><li>
You have an engineering mindset as shown by a track record of delivering models at scale both in training data and inference volumes. You have experience in delivering libraries, platforms, or solution level code to existing products.</li></ul><p><b>
Basic Qualifications:</b></p><ul><li>
Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:<ul><li>
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics</li><li>
A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration</li></ul></li></ul><p><b>
Preferred Qualifications:</b></p><ul><li>
Master&rsquo;s Degree in &ldquo;STEM&rdquo; field (Science, Technology, Engineering, or Mathematics), or PhD in &ldquo;STEM&rdquo; field (Science, Technology, Engineering, or Mathematics)</li><li>
Experience working with AWS</li><li>
At least 2 years&rsquo; experience in Python, Scala, or R</li><li>
At least 2 years&rsquo; experience with machine learning</li><li>
At least 2 years&rsquo; experience with SQL
</li></ul><p>Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.</p><p>
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.</p>
New York, NY: $145,100 - $165,600 for Sr Assoc, Data Science<br>
<p></p>
San Jose, CA: $145,100 - $165,600 for Sr Assoc, Data Science<p></p><p><br>
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.</p>
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.<p>
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.</p>
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.<p>
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.</p><p>
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com</p><p>
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.</p><p>
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</p></div>
</div><div><p>Salary</p><p>
145,100.00 - 165,600.00 Annual</p>
</div><div></div><div><div><p>Type</p><div><p>
Full-time</p></div></div></div></div>

Senior Data Scientist, AI Foundations

Product Security Engineer, Intern

<div><b>About the Role
</b><br>
<br>
We are looking for candidates with a passion for solving new and difficult problems with data. In this role, you will be able to use your strong quantitative skills in the fields of machine learning, statistics, and/or operations research to improve the Uber user experience as well as the overall marketplace performance. You'll be joining the Mobility Marketplace organization to design, evaluate, and build promotional products for drivers.
<br>
<br>
You will solve key business problems including designing incentives structures for drivers, measuring causal impacts of promotions, and creating ML-driven optimizations for marketplace growth. You will work hand in hand with product, engineering, and operations on new product launches, experiment design and algorithm development. We are a fast-moving team and are looking for creative and curious minds to join us!
<b>- What the Candidate Will Do -
</b><br>
<ul><li>Develop and optimize ML models to enhance key marketplace signals (e.g., ETA predictions, supply availability metrics, demand forecasts).
</li><li>Collaborate with cross-functional teams (Pricing, Matching, Driver Incentives, etc.) to ensure marketplace signals are effectively utilized.
</li><li>Improve operational efficiency by building a centralized, scalable system for marketplace signals that serves multiple use cases.
</li>Leverage cutting-edge ML techniques (deep learning, probabilistic modeling, reinforcement learning, etc.) to continuously refine marketplace signals.<br>
<li>
</li></ul><b>- Basic Qualifications -
</b><br>
<ul><li>B.S. in Statistics, Mathematics, Computer Science, or Machine Learning
</li><li>2 years of experience in software engineering with an emphasis on data-driven methodologies, deep learning, and online experimentation
</li><li>Strong problem-solving skills, with expertise in ML methodologies
</li><li>Experience in applying ML, statistics, or optimization techniques to solve large-scale real-world problems (e.g. ads tech, recommender systems)
</li>Experience in ML frameworks (e.g. Tensorflow, Pytorch, or JAX) and complex data pipelines; programming languages such as Python, Spark SQL, Presto, Go, Java<br>
<li>
</li></ul><b>- Preferred Qualifications -
</b><br>
<ul><li>3+ years of experience in software engineering specializing in applied ML methods
</li><li>Experience in designing and crafting scalable, reliable, maintainable and reusable ML solutions using deep-learning techniques and statistical methods.
</li><li>Detail-oriented, ownership and truth-seeking mindset.
</li><li>Values and produces analytic evidence and insight, as well as applying them to improve technical solutions.
</li><li>Experience working in a cross-functional and/or cross-business projects, partnering with Product, Scientists, and cross-org leads to shape the team's strategies
</li>Master's degree in Computer Science, Engineering, Mathematics or related field<br>
<li>
</li></ul><br>
<br>
<br>
<br>
For New York, NY-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year. For Seattle, WA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.</div>

Machine Learning Engineer II

Flatfile

<div><div><p>Location</p><div>
New York City</div></div><div><p>
Employment Type</p><div>
Full time</div></div><div><p>
Location Type</p><div>
Remote</div></div><div><p>
Department</p><div>
Engineering</div></div><div><p>
Compensation</p><ul><div><p>
Estimated Base Salary $220K &ndash; $300K &bull; Offers Equity</p></div></ul><div><div>
In accordance with applicable law, the following represents Flatfile's reasonable estimate of the range of possible compensation for this role if hired in Colorado.</div></div></div></div>
<br><div><div><p>Overview</p><p>
</p></div><div></div><div><div><div>About Flatfile</div><p>
Flatfile is revolutionizing enterprise data handling through AI automation. We're building an AI-native data mapping, cleaning, and transformation platform that tackles the most stubborn data problems for the world's largest organizations.</p><p></p><p>
What is an &quot;AI Engineer&quot; at Flatfile</p><p>
You&rsquo;ll work at the intersection of conventional software engineering and machine learning, focusing on applying AI to solve real-world problems rather than fundamental ML research.</p><p>
As James Brady from Elicit notes: &quot;If you're a software engineer who relishes the more difficult parts of backend code&mdash;like concurrency, fault-tolerance, and distributed systems&mdash;you could be a great AI engineer.&quot;</p><p></p><p><b>
This role reports to: </b>Jon Bell, VP of Product</p><p></p><p>
What you'll do</p><ul><li><div>
You'll own critical parts of our AI-powered data platform</div></li><li><div>
Design and implement robust backend services that integrate with various AI models for data understanding and transformation</div></li><li><div>
Build fault-tolerant systems that can handle the high latency and variance inherent in working with large language models</div></li><li><div>
Create streaming architectures for real-time AI processing of customer data</div></li><li><div>
Develop evaluation frameworks to measure and improve our AI features' accuracy and reliability</div></li><li><div>
Work closely with our product team to prototype and ship new AI capabilities</div></li><li><div>
Help learn and establish best practices for AI development at Flatfile</div></li><li><div>
You&rsquo;ll also get to write some good old-fashioned code and ship more traditional software features too :)</div></li><li><div>
Oh, and we all fix bugs</div></li></ul><p></p><p><b>
Our tech stack</b></p><p>
In this role, you&rsquo;ll use LangGraph, various LLMs and open source models, React, Typescript, our in-house design system Baseline, Node (Nest.js), Prisma, Postgres, Git, Flatfile&rsquo;s homegrown data engine, and utilize AI for performance gains on a daily basis.</p><p></p><p>
What you bring to the role</p><p><b>
Essential</b></p><ul><li>Experience building production backend systems</li><li>Strong computer science fundamentals, especially in distributed systems</li><li>Experience handling asynchronous workflows and building resilient services</li><li>Genuine enthusiasm for AI technology and its practical applications</li><li>Track record of shipping customer-facing features</li></ul><p></p><p><b>
Great to have</b></p><ul><li>Experience working with LLMs in production environments</li><li>Background in data processing or ETL systems</li><li>Familiarity with AI model deployment and optimization</li><li>Experience with streaming architectures</li><li>Open source contributions to AI/ML tools</li></ul><p></p><p>
What you'll find at Flatfile</p><ul><li>A chance to shape the future of enterprise data automation</li><li>A highly collaborative, fast-paced engineering culture</li><li>Ownership of significant technical challenges and no PM overlords</li><li>The opportunity to work with cutting-edge AI technology</li><li>Competitive compensation and equity</li><li>A team of humble and audacious builders who take pride in their work</li></ul></div></div></div><p></p>

AI Engineer

Terra

<div>
 <p>
  <strong>
   Software Engineering Intern, Terra YC S24
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Location (in-person, 5min from NYU campus): New York City, NY
  </strong>
 </p>
 <p>
  <strong>
   Internship (20 hours per week, more available upon request). This is a paid position.
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <span>
   At Terra, we&rsquo;re building the simplest way for creators to design and sell their own products.
  </span>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <span>
   Our software has two aspects, the product design, and the storefront (customizeable by the creator).
  </span>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <span>
   As a Software Engineer, you&rsquo;ll be responsible for the design, development, and maintenance of a scalable Terra software ecosystem that will be used by people across the globe.
  </span>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Responsibilities:
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   <span>
    UI/UX across both the design and sale platform, along with maintenance of the Terra API to ensure security and usability
   </span>
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   <span>
    Get involved in product discussions with the team, and contribute useful features for our users.&nbsp;
   </span>
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   <span>
    Write clean, maintainable, and type-safe code.
   </span>
  </li>
 </ul>
 <p>
  <span>
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    ﻿
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    Understanding the Terra software ecosystem in order to be able to identify the cause of problems and deliver fast solutions.
   </span>
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 </ul>
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  <br/>
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  <li>
   <span>
    Work fast and correct. We are a startup, and iterate
   </span>
   <strong>
    extremely
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    fast, and you need to be able to keep up with our working pace.
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   Minimum qualifications:
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    Strong proficiency in TypeScript, with experience architecting and maintaining production-grade, large-scale systems.
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    Experience with component-driven UI development (Figma, design systems) to build scalable and maintainable interfaces, mobile first design skills.
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    Hands-on expertise in Next.js for building performant, SEO-optimized, and scalable web applications.
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    Experience with common npm libraries and tooling, including TanStack Query, Drizzle ORM, Supabase CLI, and modern state/data management patterns.
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    Proficiency with Git-based workflows (GitHub), Node.js runtime, and Docker for containerized environments.
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   Preferred qualifications:
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    Deep understanding of relational database design (PostgreSQL), including schema optimization, normalization/denormalization strategies, query performance tuning, and advanced security features (RLS, server-side transactions, encryption at rest/in-transit).
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  </li>
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    Experience with scalability patterns (caching, load balancing, distributed systems) and event-driven architectures (Redis, Upstash).
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    Knowledge of machine learning frameworks (TensorFlow, PyTorch) and data processing pipelines is a plus.
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    Familiarity with cloud-native development (AWS, GCP, or Azure), including serverless functions, managed databases, and storage services.
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</div>


Software Engineer Intern

Amazon Web Services

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Generative AI Innovation Center at AWS empowers customers to harness state of the art AI technologies for transformative business opportunities. Our multidisciplinary team of strategists, scientists, engineers, and architects collaborates with customers across industries to fine-tune and deploy customized generative AI applications at scale. Additionally, we work closely with foundational model providers to optimize AI models for Amazon Silicon, enhancing performance and efficiency.
<br>
<br>
As a software development engineer (SDE) on our team, you will drive the development of custom Large Language Models (LLMs) across languages, domains, and modalities. You will be responsible for fine-tuning state-of-the-art LLMs for diverse use cases while optimizing models for high-performance deployment on AWS&rsquo;s custom AI accelerators. This role offers an opportunity to innovate at the forefront of AI, tackling end-to-end LLM training pipelines at massive scale and delivering next-generation AI solutions for top AWS clients.
<br>
<br>
Key job responsibilities<br>
<ul><li>Large-Scale Training Pipelines: Design and implement distributed training pipelines for LLMs using tools such as Fully Sharded Data Parallel (FSDP) and DeepSpeed, ensuring scalability and efficiency
</li><li>LLM Customization &amp; Fine-Tuning: Adapt LLMs for new languages, domains, and vision applications through continued pre-training, fine-tuning, and Reinforcement Learning with Human Feedback (RLHF)
</li><li>Model Optimization on AWS Silicon: Optimize AI models for deployment on AWS Inferentia and Trainium, leveraging the AWS Neuron SDK and developing custom kernels for enhanced performance
</li><li>Customer Collaboration: Interact with enterprise customers and foundational model providers to understand their business and technical challenges, co-developing tailored generative AI solutions
</li></ul><br>
About the team<br>
ABOUT AWS:<br>
<br>
Diverse Experiences
<br>
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn&rsquo;t followed a traditional path, or includes alternative experiences, don&rsquo;t let it stop you from applying.
<br>
<br>
Why AWS
<br>
Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.<br>
<br>
Work/Life Balance
<br>
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve in the cloud.<br>
<br>
Inclusive Team Culture
<br>
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.<br>
<br>
Mentorship and Career Growth<br>
We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.<br>
<br>
AWS Global Services<br>
AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center. You&rsquo;ll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>3+ years non-internship professional software development experience</li><li>2+ years non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>Experience programming with at least one software programming language</li><li>Hands-on experience with deep learning and/or machine learning methods (e.g. for training, fine tuning, and inference)</li><li>Hands-on experience with generative AI technology</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>2+ years full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>Bachelor's degree in computer science or equivalent</li><li>1+ years experience hands-on experience with developing, deploying, or optimizing machine learning models using a recognized ML library or framework</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/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>

Machine Learning Engineer, Generative AI Innovation Center

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