nlp scientist

ING Hubs Türkiye

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   About ING Hubs
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  Following ING&rsquo;s strategic ambition to deliver a superior experience to its customers worldwide, the hubs network contributes to fostering efficiency and digitalization across ING. Providing concentrated expertise along with scalable and sustainable solutions, the hubs focus on straight-through processing, delivering automated services like software development, data management and retail operations.
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  𝑃𝑟𝑒𝑠𝑒𝑛𝑡 𝑖𝑛 𝑃𝑜𝑙𝑎𝑛𝑑, 𝑅𝑜𝑚𝑎𝑛𝑖𝑎, 𝑆𝑙𝑜𝑣𝑎𝑘𝑖𝑎, 𝑡&planckh;𝑒 𝑃&planckh;𝑖𝑙𝑖𝑝𝑝𝑖𝑛𝑒𝑠 𝑎𝑛𝑑 𝑇𝑢𝑟𝑘𝑖𝑦𝑒, 𝐼𝑁𝐺 𝐻𝑢𝑏𝑠 𝑒𝑚𝑝𝑙𝑜𝑦 𝑚𝑜𝑟𝑒 𝑡&planckh;𝑎𝑛 11,000 𝑝𝑟𝑜𝑓𝑒𝑠𝑠𝑖𝑜𝑛𝑎𝑙𝑠 𝑖𝑛 𝑑𝑜𝑚𝑎𝑖𝑛𝑠 𝑠𝑢𝑐&planckh; 𝑎𝑠 𝑠𝑜𝑓𝑡𝑤𝑎𝑟𝑒 𝑑𝑒𝑣𝑒𝑙𝑜𝑝𝑚𝑒𝑛𝑡, 𝑑𝑎𝑡𝑎 𝑚𝑎𝑛𝑎𝑔𝑒𝑚𝑒𝑛𝑡, 𝑜𝑝𝑒𝑟𝑎𝑡𝑖𝑜𝑛𝑠 𝑜𝑟 𝑛𝑜𝑛-𝑓𝑖𝑛𝑎𝑛𝑐𝑖𝑎𝑙 𝑟𝑖𝑠𝑘
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  ING Hubs Turkiye core capabilities, 𝐑𝐞𝐭𝐚𝐢𝐥 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐚𝐧𝐝 𝐓𝐞𝐜𝐡, have us looking for data experts, developers and other professionals to get onboard in our Istanbul office located in Technopark, Vadistanbul
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  <strong>
   About ING
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  Think Forward! Our purpose is to empower people to stay a step ahead in life and in business. We are an industry recognized strong brand with positive recognition from customers in many countries, a strong financial position, Omni-channel distribution strategy and international network. If you want to work at a place where we believe that you can make a difference by using the latest Analytics techniques to generate data-driven approaches and conversational products and solve real business challenges, please read on.
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   ING Analytics
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  ING Analytics is a new unit responsible for realizing this vision for ING, differentiating ING as a leader in data-driven organization, within the banking sector and beyond. The team consists of a number of Global Analytics Centre of Excellences around the bank&rsquo;s key capabilities (such as Pricing, Risk Management, Financial Crime, Customer Intelligence and People Analytics.) as well as strong coordination areas around data management, technology, customer journey, UX, as well as external partnerships.
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   COO Analytics- Customer Due Diligence
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  You will be part of the COO Analytics Tribe, which delivers generative AI , AI and advanced analytics capabilities to all ING countries.
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  Specifically, you will help creating innovative-scalable-data driven solutions in the space of Customer Due Diligence. You proactively work with teams to implement these solutions across the organization. You will work collaboratively with an extended group of stakeholders, including global and local KYC (Know Your Customer).
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  Your mission will be to ensure the improvement of our products with a team and supporting all ING countries in reaching their targets by providing smart advanced analytics solutions, to strengthen ING leadership in digitalization &amp; support our 40 million customers.
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  We work in a fun and creative environment, and we&rsquo;re dedicated to bringing out the best in both our relations and our projects, ranging from enhancing our virtual assistants in production via innovative NLP techniques sush as Generative AI and Large Language Models, to building speech analytics use cases across all the countries ING operates in.
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   The opportunity
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  As a NLP/LLM Data Scientist, you will be joining the global ING Analytics organization and will partner with Machine Learning (ML) Engineers and Customer Journey Experts to design and implement leading-edge conversational AI products, such as agent assists and Retrieval Augmented Generation systems using LLMs. As an NLP/LLM data scientist, you understand business needs, perform data preprocessing and analysis, and build machine learning models and/or design and implement NLP models using managed LLM services for speech and text data to improve our platform and ING&rsquo;s KYC agents&rsquo; efficiencies globally.
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  <strong>
   A day in the life of an NLP Data Scientist
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  After your morning coffee, you stand up with data engineers to understand the best scalable way to get models to run in production, leading the way in how to approach a modeling problem and to turn data into business value. You talk to the business to convince them that your solution has value and you incorporate their feedback into your modeling pipeline. After a lunch break with colleagues, you think of a new technology you&rsquo;d like to try out. You start investigating and write it up for the next experimentation day or demo. At the end of the afternoon, you finalize some comments other colleagues from the ING Analytics Community had on your latest blog post or start building your presentation for the next conference you will be presenting at. As a Data Scientist working for ING Global Analytics, you&rsquo;ll never get bored with many experienced and skilled colleagues around you, the freedom to innovate, and to not only use open source and cloud managed service tooling, but also contribute and teach about them.
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   You Will Be Responsible For
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   Design and implementation of solutions using Generative AI and LLM technologies
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   Developing production level NLP models
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   Working with ML Engineers to productionize your developed NLP models
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   Using the cutting-edge NLP and (Gen)AI frameworks and technologies such as Large Language Models and Generative AI
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   Following best practices in developing ML code and ML software tests
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   Making design and technical decisions for (Gen)AI projects at ING Analytics. Supporting local teams in several countries and their projects. Participating in design, analysis, and interpretation of business hypotheses and exploring datasets. Recommending ideas to the business based on data.
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   Assisting your model users to understand the data science principles and when needed explaining the model behavior and possible corrective actions.
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   Contributing to strengthening the data analytics capability within the team.
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  <strong>
   About you
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   Always thinking a step ahead and never satisfied with the status quo
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   Enthusiasm for helping others to be successful and a talent for taking it on and making it happen
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   You have a learning attitude. Not only to master new technologies and programming languages, but also on the interpersonal level. You are proven to be able to ask and give feedback
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   You embrace challenges in a fast-changing and complex environment
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   You are a naturally collaborative person who listens and invests in others to achieve common goals
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   You have a Pro-active and can-do attitude (self-steering)
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   You take pride in your code and take responsibility for keeping it running in production
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   You combine both thinking of the future and a hands-on, right now attitude
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   You enjoy working in a team, with highly skilled people, having a creative atmosphere where trying out new things is encouraged.
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   How to succeed
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   Degree in Computer Science, and preferably in Natural Language Processing, Information Retrieval, or Machine Learning.
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   A minimum of 2 years experience in building Natural Language Processing or Information Retrieval pipelines and models
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   Experience with operationalisation of LLMs or Generative AI applications
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   You have an in-depth understanding of algorithms like Transformers, Recurrent Neural Networks, and Convolutional Neural Network
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   Strong programming skills in Python, experience in delivering production grade code, and reasonable SQL understanding
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   Can build an &ldquo;end-to-end ML software product&rdquo; which has NLP/IR component
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   Experience with Deep Learning frameworks like Tensorflow and PyTorch
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   You have excellent oral and written communication skills at the technical and business level
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   Fluent in written and spoken English.
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   Familiarity with Agile Scrum way of working
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   Nice To Have
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   Experience with Google Cloud Platform
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   Experience with applying NLP on banking and/or KYC domains
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   Knowledge of DevOps practices including Git and CI/CD
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   Experience with CI/CD for Machine Learning pipeline (CD4ML).
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  <strong>
   What We Offer at ING Hubs Turkiye
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  At ING Hubs Turkiye, we believe that your work should be fulfilling in every way. We pay attention to even the smallest details to ensure that your experience is rewarding. Here&rsquo;s what you can expect when you join our organization:
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   Be Yourself, Be an ING'er
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    Dynamic Environment:
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   Work in an informal, vibrant atmosphere with innovative colleagues supporting your endeavors.
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    Innovation Culture:
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   Share your innovative ideas while exploring PACE methodology with us.
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    Global Exposure:
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   Participate in global projects and expand your career opportunities.
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    Communication &amp; Celebrations:
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   Enjoy various communication activities and celebrations that promote a friendly work environment.
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    Health Care:
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   Your health matters; we offer a comprehensive health insurance package for you and your loved ones, including spouse and children.
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    Private Pension Plan:
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   Secure your future dreams with our private pension plan.
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   If you want to do your thing and explore the life while working don&rsquo;t miss this opportunity!
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</div>


Senior NLP Data Scientist

Cotiviti

<div>Overview:
<div>
Cotiviti is seeking a Data Scientist to lead the development of advanced classification and predictive systems for healthcare risk adjustment and ICD-10 code classification. This role will focus on building intelligent NLP systems that analyze clinical charts and encounters to accurately identify and classify ICD-10 codes through sophisticated pattern recognition, machine learning, and natural language processing techniques.</div>
Responsibilities:
<ul><li>Lead development of NLP-based classification systems for ICD-10 code identification from clinical charts and encounters
</li><li>Design and implement deep learning models using PyTorch and transformer architectures for medical text analysis
</li><li>Build and optimize machine learning models for accurate risk adjustment coding and HCC classification
</li><li>Develop decision support systems for automated ICD-10 code suggestion and validation
</li><li>Create and maintain feature engineering pipelines for clinical text processing and model training
</li></ul><div>&bull; Implement model evaluation metrics and performance optimization strategies for healthcare coding accuracy &bull; Produce comprehensive technical documentation and training materials for NLP models
</div><ul><li>Conduct system health checks and performance monitoring for deployed coding models
</li><li>Collaborate with engineering teams to integrate ML/NLP solutions into production systems
</li><li>Provide technical guidance on statistical modeling, transformer architectures, and algorithm selection
</li><li>Support data pipeline design and implementation for clinical text analytical workflows
</li><li>Participate in code reviews and maintain high standards for code quality
</li><li>Experience with distributed computing frameworks and big data technologies for processing large volumes of clinical data
</li><li>Mentor junior scientists and analysts in machine learning, NLP, and artificial intelligence best practices
</li><li>Track record of using assistive AI technology to improve quality and efficiency of modeling and analytics
</li><li>Complete all responsibilities as outlined in the annual performance review and/or goal setting. <b>Required</b>
</li><li>Complete all special projects and other duties as assigned. <b>Required</b>
</li><li>Must be able to perform duties with or without reasonable accommodation. <b>Required</b></li></ul>
Qualifications:
<ul><li>Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or related field; Master's in Data Science or related field preferred</li><li>3+ years of experience in machine learning and AI with focus on NLP, classification, and predictive systems</li><li>Strong expertise in PyTorch and transformer architectures (BERT, RoBERTa, etc.) for text classification</li><li>Advanced Python programming skills with experience in NLP frameworks and libraries</li><li>Experience with healthcare claims data, clinical text processing, and ICD-10 coding systems preferred</li><li>Knowledge of risk adjustment methodologies and HCC (Hierarchical Condition Categories) coding</li><li>Experience with feature engineering techniques for clinical text and model evaluation methodologies</li><li>Experience with model deployment and monitoring in production environments</li><li>Understanding of data quality frameworks and error detection methodologies for healthcare coding</li><li>Strong analytical and problem-solving skills with focus on clinical data challenges</li><li>Excellent communication skills with ability to explain technical NLP concepts clearly</li><li>Experience with version control systems and collaborative development practices</li><li>Expertise with SQL and data manipulation tools for healthcare datasets.</li></ul></div>

Data Scientist

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability &amp; fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations.<br>
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As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results.<br>
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Key job responsibilities<br>
As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.</p><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree</li><li>1 year of relevant applied research experience with PhD or 3+ years of applied research experience with a Masters&rsquo; degree in Electrical Engineering, Computer Science, Computer Engineering, Mathematics, or related field with specialization in Machine Learning, NLP, Computer Vision, Deep Learning, or GenAI related fields.</li><li>Should be an expert in either Computer Vision or NLP and have a good understanding of the both.</li><li>Excellent communication skills</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Post Graduate degree (MS or PhD) in Electrical Engineering, Computer Science, Mathematics or Physics with specialization in ML, NLP or Computer Vision.</li><li>Strong verbal/written communication skills, including an ability to effectively collaborate with both research and technical teams.</li><li>Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.</li><li>Solid understanding of machine learning, deep learning algorithms and computational complexity.</li><li>Strong CS fundamentals in data structures, problem solving, algorithm design and complexity analysis.</li></ul><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.</div>

Applied Scientist II, RBS Tech

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability &amp; fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations.<br>
<br>
As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results.<br>
<br>
Key job responsibilities<br>
As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will independently file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.</p><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>Master's degree</li><li>2+ years of relevant applied science research experience with a Masters&rsquo; degree in Electrical Engineering, Computer Science, Computer Engineering, Mathematics, or related field with specialization in machine learning, NLP, Computer Vision, deep or related fields.</li><li>Excellent communication skills</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Have publications at top-tier peer-reviewed conferences or journals</li><li>Strong verbal/written communication skills, including an ability to effectively collaborate with both research and technical teams.</li><li>Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.</li><li>Solid understanding of machine learning, deep learning algorithms and computational complexity.</li><li>Strong CS fundamentals in data structures, problem solving, algorithm design and complexity analysis.</li></ul><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.</div>

Applied Scientist, RBS Tech

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Are you excited about joining a team of scientists building lasting solutions for Amazon customers from the ground up? Our team is using machine learning, and statistical methods to take Amazon&rsquo;s unique customer obsession culture to another level by designing solutions that change customers behavior when it comes to product search, discovery, and purchase. In order to achieve this, we need scientists who will help us build advanced algorithms that deliver first-rate user experience during customers&rsquo; shopping journeys on Amazon. These algorithms will utilize advances in Natural Language Understanding, and Computer Vision to source and understand content that customers trust, and furnish customers with the content in a way that meets their needs at any stage of their shopping journey.
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Key job responsibilities<br>
As a Sr. Applied Scientist, you are able to use a range of science methodologies in NLP/CV to solve challenging business problems when the solution is unclear. For example, you may lead the development of reinforcement learning models such as MAB to rank content to be shown to customers based on their queries. You have a combination of business acumen, broad knowledge of statistics, deep understanding of ML algorithms, and an analytical mindset. You thrive in a collaborative environment, and are passionate about learning.
<br>
<br>
Our team utilizes a variety of AWS tools such as SageMaker, S3, and EC2 with a variety of skillsets in ML models, particularly using NLP and CV. You will bring knowledge in many of these domains along with your own specialties and skillset.<br>
<br>
Major responsibilities:<br>
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<ul><li>Use statistical and machine learning techniques to create scalable and lasting systems.</li><li>Analyze and understand large amounts of Amazon&rsquo;s historical business data for Recommender/Matching algorithms</li><li>Design, develop and evaluate highly innovative models for NLP/CV.</li><li>Work closely with teams of scientists and software engineers to drive real-time model implementations and new feature creations.</li><li>Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and implementation.</li><li>Research and implement novel machine learning and statistical approaches, including NLP and Computer Vision</li></ul><br>
A day in the life<br>
In this role, you&rsquo;ll be utilizing your NLP or CV skills, and creative and critical problem-solving skills to drive new projects from ideation to implementation. Your science expertise will be leveraged to research and deliver often novel solutions to existing problems, explore emerging problems spaces, and create or organize knowledge around them.<br>
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</div><h2 class="jobSectionHeader"><b>BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>3+ years of building machine learning models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with neural deep learning methods and machine learning</li><li>4+ years of applied research experience</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>
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 $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Senior Applied Scientist, Creators

Cerence AI

<div><div>A Moving Experience.</div><div>
Do you have a passion for pushing the boundaries of innovation? Are you excited about AI&rsquo;s potential to improve the human experience? Then come join the ride!</div><div></div><div>
Who is Cerence ai?</div><div></div><div>
Cerence ai is the global leader in AI for transportation, specialized in building AI and voice-powered companions for cars, two-wheelers, and more that enable people to focus on what matters most. With over 500 million cars shipped with Cerence ai technology, we partner with leading automakers (such as Volkswagen, Mercedes, Audi, Toyota and many more), mobility providers, and technology companies to power intuitive, integrated experiences that create safer, more connected, and more enjoyable journeys for drivers and passengers alike.</div><div></div><div>
Our Driving Force</div><div></div><div>
Our team is dedicated to pushing the boundaries of AI innovation, working around the globe with headquarters in Burlington, Massachusetts, USA and 16 other offices across Europe, Asia, and North America. We bring together diverse backgrounds and varied skill sets with the shared goal of advancing the next generation of transportation user experiences. Our culture is customer-centric, collaborative, fast-paced, and fun, with continuous opportunities for learning and development to support your career growth.</div><div>
Interested in having a significant impact in a dynamic industry with a high-performing global team?</div><div>
We are seeking a highly skilled and innovative Senior Research Scientist specializing in Speech Recognition to drive advanced research and development in NLP, Machine Learning, Deep Learning, generative AI, and large language models (LLMs). This role will focus on building state-of-the-art ASR systems, applying retrieval-augmented generation (RAG) and finetuning techniques, leveraging agentic AI frameworks, and utilizing cloud platforms for scalable deployments. Person should be well-versed in the latest advancements in speech recognition technology, including Generative AI, large language models (LLMs), Agentic AI framework and exposure to Cloud platforms. This role offers a unique opportunity to impact the next generation of speech AI technologies, working with cutting-edge LLMs and agentic AI frameworks under a collaborative and innovative environment.</div><div></div><div>
Your Impact:</div><ul><li>
Conduct applied research to develop, train, and optimize speech recognition models incorporating NLP, deep learning, and generative AI techniques.</li><li>
Design and experiment with LLMs and RAG models for improved conversational AI systems.</li><li>
Drive finetuning and domain adaptation strategies for enhancing model performance on multilingual and low-resource speech data.</li><li>
Work with agentic AI frameworks to enable advanced workflow orchestration and stateful agent interactions.</li><li>
Collaborate with cross-functional teams, including other AI researchers and scientists, to seamlessly integrate features and functionalities.</li><li>
Collaborate with engineering teams to implement and deploy scalable cloud-based AI pipelines and services.</li><li>
Analyse and preprocess large-scale speech datasets, ensuring high-quality data management for model training.</li><li>
Publish research findings in internal and / or external conferences, actively participate in hackathons and contribute to the scientific community.</li><li>
Mentor junior researchers and contribute to knowledge sharing and technical leadership within the team.</li></ul><div></div><div>
What you bring:</div><ul><li>
PhD or Master&rsquo;s degree in Computer Science, Electrical Engineering, Computational Linguistics, or related fields.</li><li>
Strong expertise in speech recognition, NLP, machine learning, deep learning, and generative AI.</li><li>
Proven experience with LLMs, retrieval-augmented generation (RAG), and model finetuning.</li><li>
Familiarity with agentic AI frameworks and their application in conversational or speech systems.</li><li>
Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud for AI deployment.</li><li>
Proficiency in Python, deep learning frameworks (PyTorch or TensorFlow), and software engineering best practices.</li><li>
Experience with large-scale speech data processing and annotation.</li><li>
You possess excellent problem-solving skills, attention to detail, analytical thinking, and a collaborative mindset to work effectively within our fast-paced and innovative environment.</li><li>
Excellent communication skills and ability to collaborate across multidisciplinary teams.</li></ul><div>
Preferred Qualifications:</div><ul><li>
Publications in major AI, speech, or NLP conferences.</li><li>
Knowledge of distributed computing and containerization (Docker, Kubernetes).</li><li>
Experience with end-to-end ASR systems or multi-modal AI models.</li></ul><div></div><div>
What We Offer:</div><ul><li>
Annual bonus opportunity</li><li>
Insurance coverage</li><li>
Paid time off</li><li>
Paid holidays</li><li>
Equity-based awards for some positions and levels</li><li>
Remote and/or hybrid work available depending on position.</li></ul><div></div><div>
All compensation and benefits are subject to the terms and conditions of the underlying plans or programs, as applicable and as may be amended, terminated or superseded from time to time.</div><div></div><div>
Cerence Inc. (Nasdaq: CRNC and <div>www.cerence.com</div>) is the global industry leader in creating unique, moving experiences for the automotive world. Spun out from Nuance in October 2019, Cerence is a new, independent company that has quickly gained traction as a leader in the automotive voice assistant space, working with all of the world&rsquo;s leading automakers &ndash; from Ford and Fiat Chrysler to Daimler, Audi and BMW to Geely and SAIC &ndash; to transform how a car feels, responds and learns. Its track record is built on more than 20 years of industry experience and leadership and more than 500 million cars on the road today across more than 70 languages.</div><div></div><div><br>
As Cerence looks to the future and continues an ambitious growth agenda, we need someone to join the team and help build the future of voice and AI in cars. This is an exciting opportunity to join Cerence&rsquo;s passionate, dedicated, global team and be a part of meaningful innovation in a rapidly growing industry.</div><div></div><div>
EQUAL OPPORTUNITY EMPLOYER</div><div></div><div>
Cerence is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal, state and local laws that prohibit employment discrimination on the basis of age, race, color, gender, gender identity, gender expression, sex, sex stereotyping, pregnancy, national origin, ancestry, religion, physical or mental disability, medical condition, marital status, citizenship status, sexual orientation, protected military or veteran status, genetic information and other protected classifications. Cerence Equal Employment Opportunity Policy Statement.</div><div></div><div>
All prospective and current Employees need to remain vigilant when it comes to executing security policies in the workplace. This includes:</div><div><ul><li><br>
Following workplace security protocols and training programs to familiarize with the ways to maintain a safe workplace.</li><li>Following security procedures to report any suspicious activity.</li><li>Having respect for corporate security procedures to allow those procedures to be effective.</li><li>Adhering to company's compliance and regulations.</li><li>Encouraging to follow a zero tolerance for workplace violence.</li></ul></div><ul><li>Basic knowledge of information security and data privacy requirements (e.g., how to protect data &amp; how to be handling this data).</li><li>Demonstrative knowledge of information security through internal training programs.</li></ul></div>

Senior Research Scientist

Microsoft

<div><div>Do you want to shape the future of the autonomous enterprise and lead the development of intelligent, agent-first experiences that transform how businesses operate? The Business and Industry Solutions (BIS) team is looking for a Senior Applied Scientist to drive innovation at the intersection of AI, experimentation, and enterprise systems. In this role, you will design and evaluate autonomous agents that deliver measurable improvements in accuracy, latency, and cost-efficiency. You&rsquo;ll lead rapid experimentation cycles, develop robust evaluation frameworks, and apply advanced techniques like reinforcement learning to enable multi-step reasoning and decision-making. You&rsquo;ll collaborate across engineering, product, and partner teams to ensure agents are performant, secure, reliable, and extensible&mdash;empowering customers and partners to build on our platform. This is your opportunity to influence the next generation of AI-native business applications and deliver real-world impact at scale.</div><div></div><div><br>
The ideal candidate has prior expertise in natural language processing (NLP), with a strong foundation in large language model (LLM) development, evaluation, and fine-tuning. They should have hands-on experience in applying advanced fine-tuning techniques&mdash;including instruction tuning, reinforcement learning from human feedback (RLHF), and tool-augmented generation&mdash;to build agents capable of multi-step reasoning and decision-making. Familiarity with prompt/context engineering, context-aware orchestration, and integrating LLMs with external tools and APIs is essential. The candidate should be comfortable working in a fast-paced, experimentation-driven environment, leveraging both offline and online evaluation methods to iterate rapidly and optimize agent behavior. A deep understanding of the challenges and opportunities in building AI-native enterprise applications will be key to success in this role.</div><div></div><h2 class="jobSectionHeader"><b><br>
Responsibilities</b></h2><div></div><ul><li><b><br>
Drive strategic impact</b> by identifying and leading high-leverage data science and analytics initiatives across multiple product domains.</li><li><b>
Lead the development and deployment of advanced model fine-tuning pipelines</b>, leveraging Reinforcement Learning from Human Feedback (RLHF) to align AI system behavior with human intent and improve performance in complex, real-world enterprise scenarios.</li><li><b>
Steer strategic direction and investment decisions</b> by owning complex, end-to-end projects that blend technical depth with organizational influence.</li><li><b>
Build alignment and trust across leadership and cross-functional teams</b> through clear, persuasive communication and collaborative engagement.</li><li><b>
Design and implement robust measurement systems</b>, experimentation frameworks, and causal inference methodologies tailored to dynamic AI systems and enterprise-scale environments.</li><li><b>
Mentor and elevate the data science community</b> by championing best practices, nurturing talent, and cultivating a collaborative, high-performance culture.</li><li><b>
Harness AI to accelerate workflows</b> and amplify team productivity through intelligent automation and innovation.</li></ul><h2 class="jobSectionHeader"><b>
Qualifications</b></h2><ul><li>
Bachelor's degree in Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)</li><li>
Or, Master's Degree in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)<b> (</b><b>OR)</b></li><li>
 Doctorate in Statistics, Mathematics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)</li></ul><ul><li>
5+ years experience developing and deploying AI/ML products or systems at multiple points in the product cycle from ideation to shipping.</li></ul><div><b><br>
Preferred Qualifications:</b></div><ul><li>
Master's Degree in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 12+ years related experience (e.g., statistics, predictive analytics, research)<b> (</b><b>OR)</b></li><li>
 Doctorate in Statistics, Mathematics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)</li><li>
5+ years experience developing and deploying GenAI products or systems at multiple points in the product cycle from ideation to shipping.</li><li>
Experience with modern NLP techniques and language model architectures (e.g. Transformer, etc).</li><li>
Deep understanding of statistics and statistical theory</li><li>
Experience working with real-world noisy data</li><li>
Demonstratable experience with software engineering principles, parallel and distributed computing, statistics, machine learning, cloud technologies like Azure, AWS, Google Cloud, IaaS, PaaS and SaaS</li></ul><div></div><div><b><br>
Other Requirements</b></div><div></div><div><br>
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:</div><div><b>
Microsoft Cloud Background Check:</b> This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.</div><div></div><p><br>
#BICJobs</p><br>
<div></div>
Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.</div>

Principal Applied Science Engineer

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