machine learning scientist

Wayfair

<div><h4 class="jobSectionHeader">Salary Range: $207,900 - $219,450 per year. Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the annual base salary only and do not include equity.<br>
<br>
<b>About this role</b></h4><p>
We are looking for an experienced Machine Learning Scientist III to join our content recommendations team. In this role, you will be at the core of building and optimizing ML-based recommender systems (e.g., image and content recommendations, homepage and email optimization and personalization) to enhance the customer experience at Wayfair. Your work will directly impact how millions of customers discover and engage with products, driving significant business value.</p><p>
As part of Wayfair's SMART (Search, Marketing, and Recommendations Technology) team, you will collaborate with ML scientists, engineers, and product teams to develop and deploy cutting-edge recommendation models that operate at scale. This role is an opportunity to solve complex problems related to personalization, large-scale machine learning, latency, and scalability while leveraging state-of-the-art (SOTA) AI techniques.</p><h4 class="jobSectionHeader"><b>
What you&rsquo;ll do</b></h4><ul>
<li>Develop and optimize recommendation models that power personalized experiences across Wayfair&rsquo;s site, app, email, and push notifications.</li>
<li>Conduct applied research to improve recommender systems using traditional ML techniques, deep learning and reinforcement learning.</li>
<li>Build scalable ML pipelines for training, evaluation, and inference, ensuring models operate efficiently in production.</li>
<li>Work closely with engineering teams to deploy models in a production environment, addressing real-world constraints such as latency, interpretability, and scalability.</li>
<li>Analyze model performance and iterate based on A/B test results, offline evaluation metrics, and business impact.</li>
<li>Leverage and contribute to open-source ML frameworks while staying up to date with cutting-edge research in recommendation systems.</li>
<li>Drive innovation by identifying opportunities to improve personalization strategies and developing novel algorithms that enhance customer engagement.</li>
<li>Collaborate with cross-functional teams including product managers, software engineers, and data scientists to align ML objectives with business goals.</li>
<li>Mentor other less experienced scientists on the team</li>
</ul><h4 class="jobSectionHeader"><b>Who you are</b></h4><ul>
<li>5+ years of experience developing and deploying machine learning models, with a focus on recommendations, ranking, or personalization.</li>
<li>Strong theoretical understanding of machine learning and deep learning applied to large-scale recommendation problems.</li>
<li>Experience in training, evaluating, and optimizing recommendation models in production, leveraging techniques such as collaborative filtering, sequence modeling, representation learning and multi-armed bandits.</li>
<li>Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-Learn.</li>
<li>Familiarity with big data processing (Spark, Hadoop) and ML pipeline orchestration (Airflow, Kubeflow, MLflow).</li>
<li>Strong coding skills and familiarity with building scalable ML systems in cloud environments (AWS, GCP, Azure).</li>
<li>Ability to design experiments and analyze results using A/B testing and statistical techniques.</li>
<li>Excellent communication skills, with the ability to explain complex ML concepts to non-technical stakeholders and drive data-driven decisions.</li>
</ul><h4 class="jobSectionHeader"><b>Nice to have</b></h4><ul>
<li>Experience developing core recommendation systems for eCommerce, marketplaces, or streaming platforms.</li>
<li>Familiarity with reinforcement learning or contextual bandits for adaptive recommendation strategies.</li>
</ul><p>
This role offers the opportunity to work on high-impact ML problems at scale, shaping the future of personalization and recommendations at Wayfair. If you're passionate about building intelligent systems that enhance customer experiences, we&rsquo;d love to hear from you!</p><p><b><br>
Why You'll Love Wayfair:</b></p><ul>
<li>
Time Off:<ul>
<li>Paid Holidays</li>
<li>Paid Time Off (PTO)</li>
</ul></li><li>Health &amp; Wellness:<ul>
<li>Full Health Benefits (Medical, Dental, Vision, HSA/FSA)</li>
<li>Life Insurance</li>
<li>Disability Protection (Short Term &amp; Long Term Disability)</li>
<li>Global Wellbeing: Gym/Fitness discounts (including US Peloton, Global ClassPass, and various regional gym memberships)</li>
<li>Mental Health Support (Global Mental Health, Global Wayhealthy Recordings)</li>
<li>Caregiver Services</li>
</ul></li><li>Financial Growth &amp; Security:<ul>
<li>401K Matching (Employee Matching Program)</li>
<li>Tuition Reimbursement</li>
<li>Financial Health Education (Knowledge of Financial Education - KOFE)</li>
<li>Tax Advantaged Accounts</li>
</ul></li><li>Family Support:<ul>
<li>Family Planning Support</li>
<li>Parental Leave</li>
<li>Global Surrogacy &amp; Adoption Policy</li>
</ul></li><li>Professional Development &amp; Recognition:<ul>
<li>Rewards &amp; Recognition</li>
<li>Global Employee Anniversary Awards</li>
<li>Paid Volunteer Work</li>
</ul></li><li>Unique Perks:<ul>
<li>Employee Discount</li>
<li>U.S. Bluebikes Membership</li>
<li>Global Pod Outings</li>
</ul></li><li>Work/Life Balance:<ul><li>
Emphasizing a supportive &amp; flexible work environment that encourages a balance between personal and professional commitments</li></ul><br>
</li>
</ul><p><b>Wayfair's In-Office Policy:</b></p><p>
All Mountain View-based interns, co-ops, and corporate employees will be in office in a hybrid capacity. Employees will work in the office on designated days, Tuesday, Wednesday, and Thursday, and work remotely the other 2 days of the week.</p><div>
<p><b>
Assistance for Individuals with Disabilities</b><br>
Wayfair is fully committed to providing equal opportunities for all individuals, including individuals with disabilities. As part of this commitment, Wayfair will make reasonable accommodations to the known physical or mental limitations of qualified individuals with disabilities, unless doing so would impose an undue hardship on business operations. If you require a reasonable accommodation to participate in the job application or interview process, please let us know by completing our Accomodations for Applicants form.<br>
<br>
<b>Need Technical Assistance?</b><br>
For more information about applying for a career at wayfair, visit our FAQ page here.<br>
<br>
<b>About Wayfair Inc.</b><br>
Wayfair is one of the world&rsquo;s largest online destinations for the home. Whether you work in our global headquarters in Boston, or in our warehouses or offices throughout the world, we&rsquo;re reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If you&rsquo;re looking for rapid growth, constant learning, and dynamic challenges, then you&rsquo;ll find that amazing career opportunities are knocking.</p>
<p>
No matter who you are, Wayfair is a place you can call home. We&rsquo;re a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair &ndash; and world &ndash; for all. Every voice, every perspective matters. That&rsquo;s why we&rsquo;re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, genetic information, or any other legally protected characteristic.</p>
<p>
Your personal data is processed in accordance with our Candidate Privacy Notice (https://www.wayfair.com/careers/privacy). If you have any questions or wish to exercise your rights under applicable privacy and data protection laws, please contact us at dataprotectionofficer@wayfair.com.</p></div></div>

Machine Learning Scientist III - Recommendations

Mondo

<div>
 <br/>
 <p>
  Apply now: Data Scientist, location is Remote. The start date is TBD for this Contract position.
 </p>
 <p>
  <strong>
   Job Title:
  </strong>
  Data Scientist
  <br/>
  <strong>
   Location-Type:
  </strong>
  100% Remote (can be located in EST or CST time zones)
  <br/>
  <strong>
   Start Date:
  </strong>
  ASAP
  <br/>
  <strong>
   Duration:
  </strong>
  Contract (Possible to Hire)
  <br/>
  <strong>
   Compensation Range:
  </strong>
  $65-75/hr on W2&nbsp;
  <br/>
  <strong>
   Benefits:
  </strong>
  &nbsp;Eligible for Health, Dental, Vision, 401K
  <br/>
  <em>
   Must be authorized to work in the U.S. This position is not eligible for sponsorship
  </em>
  .
 </p>
 <p>
  <strong>
   Job Description:
   <br/>
  </strong>
  The Data Scientist will develop and deploy advanced analytics and machine learning solutions to support research, manufacturing, and business initiatives.
 </p>
 <p>
  <strong>
   Day-to-Day Responsibilities:
  </strong>
 </p>
 <ul>
  <li>
   Clean, prepare, and analyze large datasets
  </li>
  <li>
   Build and validate machine learning and statistical models
  </li>
  <li>
   Develop predictive and optimization algorithms
  </li>
  <li>
   Collaborate with cross-functional teams to deploy data solutions
  </li>
  <li>
   Communicate insights and results to non-technical stakeholders
  </li>
  <li>
   Work with data engineers to access and structure data
  </li>
  <li>
   Create visualizations, reports, and dashboards
  </li>
 </ul>
 <p>
  <strong>
   Requirements:
  </strong>
 </p>
 <strong>
  Must-Haves:
 </strong>
 <ul>
  <li>
   PhD in Chemical Engineering or Chemistry
  </li>
  <li>
   Strong programming skills in Python or R
  </li>
  <li>
   Solid foundation in statistics (regression, hypothesis testing)
  </li>
  <li>
   Experience with machine learning (classification, clustering, neural networks)
  </li>
  <li>
   Experience with supervised learning techniques (e.g., random forest, XGBoost, Lasso)
  </li>
  <li>
   Knowledge of Generative AI (LLMs, RAG, agentic AI frameworks)
  </li>
  <li>
   Experience with NLP, knowledge graphs, or advanced retrieval techniques
  </li>
  <li>
   SQL proficiency and data visualization experience
  </li>
  <li>
   Strong communication and collaboration skills
  </li>
 </ul>
 <strong>
  Nice-to-Haves:
 </strong>
 <ul>
  <li>
   Experience with Azure (Data Lake, Data Factory, Databricks)
  </li>
  <li>
   High Performance Computing (HPC) experience
  </li>
  <li>
   Experience with Power BI or Node.js
  </li>
  <li>
   Experience in manufacturing, R&amp;D, or supply chain domains
  </li>
 </ul>
 <p>
  &nbsp;
  <br/>
 </p>
</div>


Data Scientist

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems.<br>
<br>
Key job responsibilities<br>
As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services.<br>
<br>
A day in the life<br>
An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.</p><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience implementing algorithms using both toolkits and self-developed code</li><li>Have publications at top-tier peer-reviewed conferences or journals</li><li>PhD in computer science, machine learning, engineering, or related fields</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.<p><br>
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.</p><br>
USA, MA, Boston - 136,000.00 - 184,000.00 USD annually<br>
USA, WA, BELLEVUE - 136,000.00 - 184,000.00 USD annually</div><p></p>

Applied Scientist, Artificial General Intelligence, AGI Data Services

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems.<br>
<br>
Key job responsibilities<br>
As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services.<br>
<br>
A day in the life<br>
An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.</p><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience implementing algorithms using both toolkits and self-developed code</li><li>Have publications at top-tier peer-reviewed conferences or journals</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.<p><br>
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.</p><br>
USA, MA, Boston - 136,000.00 - 184,000.00 USD annually<br>
USA, WA, BELLEVUE - 136,000.00 - 184,000.00 USD annually</div><p></p>

ICR, Inc.

<div><div><b>Bayesian Statistician (Data Scientist)</b><br>
Aurora, CO</div>
<div></div><div>Applications will be accepted on an ongoing basis.</div><br>
<div><br>
<br>
ICR has opportunities available for experienced and motivated Data Scientists with a Bayesian statistics background.<br>
<br>
<b>Essential Job Responsibilities</b><br>
<br>
This Data Scientist will be expected to:</div>
<ul><li>Work independently on complex technical tasks that require in-depth data analysis methodologies and data/information collection</li>
<li>Develop unique technical solutions for applications in the intelligence field</li>
<li>Participate as a member of a multidisciplinary team to analyze and satisfy customer requirements</li>
<li>Develop, implement, validate, document, and present findings of specialized analysis software tools and models as required</li>
<li>Effectively handle concurrent technical tasks with conflicting priorities</li>
<li>Approach difficult problems with enthusiasm and creativity</li>
<li>Have the ability to change focus when necessary</li>
<li>Travel (up to 10%)</li>
</ul>
<div><br>
<b>Required Skills and Qualifications</b></div>
<ul><li>Active Top Secret Security Clearance with SSBI and SCI eligibility.</li>
<li>Experience with Bayesian statistics and time series analysis</li>
<li>Masters Degree in statistics with a minimum of Two (2) years of professional experience or PhD in statistics or related field
</li><li>Experience with computational analysis tools and developing software with at least one of the following programing language: Python (preferred), R, C++, MATLAB
</li><li>Experience with developing and applying advanced statistical/machine learning models and algorithms for one or more of the following: classification, clustering, anomaly detection, density estimation, data mining, pattern recognition, knowledge discovery</li>
<li>Experience with extracting and processing structured/unstructured data from various sources (e.g. databases, text files, web) and preparing data for analysis
</li><li>Collaborate with others in a multidisciplinary team environment to accomplish research goals
</li><li>Ability to work effectively in small-team settings to solve complex problems
</li><li>Ability and desire to obtain substantial domain knowledge in fields of application and ability to communicate effectively with subject matter experts
</li><li>Proficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information to customers</li>
</ul>
<div><br>
<b>Desired Qualifications</b></div>
<ul><li>Experience with the intelligence community
</li><li>Broad knowledge of statistical analysis, ML methods, and problem-solving skills
</li><li>Experience with: spatial statistics, multivariate statistics, Gaussian Process, Random Forest, Support Vector Machine, Natural Language Processing, Neural Networks
</li><li>Proficient with Python, Jupyter, Markdown
</li><li>Experience working with databases such as SQL and/or ELK stack
</li><li>Experience with creating data visualizations / dashboards</li>
</ul>
<div></div><div>Salary Range: $78,853 - $236,579</div>
<div></div><div>This position offers a comprehensive benefits package that includes company equity, retirement plan, company-paid health care benefits, flexible paid time off policy, and opportunity for a raise and bonus during the year.</div><br>
<div></div>
<div></div><div><div><div>ICR, Inc. considers several factors when extending job offers, including but not limited to candidates&rsquo; key skills, relevant work and/or military experience, education, training certifications and work location.
</div>
<div></div><div><div><i>ICR is proud to be an equal opportunity employer and considers qualified applicants for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, gender identity and expression, age, disability, veteran status, or any other protected factor.</i></div></div></div></div></div><div></div>

Bayesian Statistician (Data Scientist) - Aurora, CO

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.<br>
<br>
Amazon Ads Response Prediction team is your choice, if you want to join a highly motivated, collaborative, and fun-loving team with a strong entrepreneurial spirit and bias for action. We are seeking an experienced and motivated Machine Learning Applied Scientist who loves to innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems.<br>
<br>
Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities.
<br>
<br>
We are looking for a talented Machine Learning Applied Scientist for our Amazon Ads Response Prediction team to grow the business. We are providing advanced real-time machine learning services to connect shoppers with right ads on all platforms and surfaces worldwide. Through the deep understanding of both shoppers and products, we help shoppers discover new products they love, be the most efficient way for advertisers to meet their customers, and helps Amazon continuously innovate on behalf of all customers.<br>
<br>
Key job responsibilities<br>
As a Machine Learning Applied Scientist, you will:<br>
<br>
<ul><li>Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities
</li><li>Develop scalable and effective machine-learning models and optimization strategies to solve business problems
</li><li>Run regular A/B experiments, gather data, and perform statistical analysis</li><li>Work closely with software engineers to deliver end-to-end solutions into production
</li><li>Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving
</li><li>Conduct research on new machine-learning modeling to optimize all aspects of Sponsored Products and Brands business</li></ul><br>
About the team<br>
We are pioneers in applying advanced machine learning and generative AI algorithms in Sponsored Products and Brands business. We empower every customer with a customized discovery experiences from back-end optimization (such as customized response prediction models) to front-end CX innovation (such as widgets), to help shoppers feel understood and shop efficiently on and off Amazon.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></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>Experience with neural deep learning methods and machine learning</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.</li><li>Experience with large scale distributed systems such as Hadoop, Spark etc.</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>
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.<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.<p><br>
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.</p><br>
USA, CA, Palo Alto - 192,200.00 - 260,000.00 USD annually<br>
USA, WA, SEATTLE - 167,100.00 - 226,100.00 USD annually</div><p></p>

Sr Applied Scientist, Sponsored Products and Brands Ads Response Prediction

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Artificial General Intelligence (AGI) Customization Team is seeking a highly skilled and experienced Applied Scientist to support adoption and enable customization of Amazon Nova. The role focuses on developing state-of-the-art services and tools for model customization, including supervised fine-tuning, reinforcement learning, and knowledge distillation across large language models.<br>
<br>
As an Applied Scientist, you will play a important role in developing advanced customization capabilities that enable enterprises to build highly performant application-specific models without the need for training models from scratch. Your work will directly impact how companies leverage Amazon Nova models for their specific use cases.<br>
<br>
Key job responsibilities<br>
<ul><li>Contribute to the development of novel customization techniques including extended post-training, continued pre-training, and advanced knowledge distillation
</li><li>Collaborate with cross-functional teams to design and implement enterprise-ready tooling for various training techniques on Amazon SageMaker</li><li>Design and execute experiments to optimize model accuracy, latency, and cost across different customization approaches (SFT, DPO, PPO)</li><li>Develop and enhance preference learning algorithms and training curricula for customer-specific applications</li><li>Create robust evaluation frameworks for assessing model performance across different domains and use cases</li><li>Contribute to the development of the Responsible AI toolkit, including creating training and evaluation datasets for model alignment</li><li>Design and implement secure access mechanisms for early model checkpoints and weights</li><li>Communicate technical insights and results to both technical and non-technical stakeholders through presentations and documentation</li></ul></div><h2 class="jobSectionHeader"><b><br>
BASIC QUALIFICATIONS</b></h2><ul><li>3+ years of building models for business application experience</li><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</li><li>Experience in patents or publications at top-tier peer-reviewed conferences or journals</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing</li><li>1+ years of building machine learning models for business application experience</li><li>Master's degree, or PhD and 2+ years of applied research experience</li><li>Experience with any programming language such as Python, Java, C++</li><li>Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience using Unix/Linux</li><li>Experience in professional software development</li><li>PhD in computer science, machine learning, engineering, or related fields, or Master's degree</li><li>PhD in computer science, computer engineering, or related field, or experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Caffe and PyTorch</li><li>Experience that includes strong analytical skills, attention to detail, and effective communication abilities, or experience in software development and experience in managing and troublshooting network</li><li>Experience collaborating with cross-functional teams</li><li>Experience in developing and implementing algorithms and models for supervised fine-tuning and reinforcement learning</li><li>Experience with patents or publications at top-tier peer-reviewed conferences or journals</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.<p><br>
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.</p><br>
USA, MA, Cambridge - 142,800.00 - 193,200.00 USD annually<br>
USA, WA, BELLEVUE - 142,800.00 - 193,200.00 USD annually</div><p></p>

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