machine learning scientist

black.ai

<p>At Sonder, we believe that every person deserves to feel safe, supported, and empowered to be at their best - wherever they are. That's why we're redefining workplace health, safety, and wellbeing through a seamless blend of technology and human expertise. Sonder's mobile platform provides 24/7, real-time support from a dedicated team of safety, medical, and mental health professionals - ensuring that our members receive immediate care when they need it most. In critical situations, we go beyond digital support, offering on-the-ground assistance to manage time-sensitive incidents.</p> <p>By harnessing real-time insights, we enable organisations to take proactive steps toward a healthier, safer future, which leads directly to tangible bottom-line business outcomes.</p> <p><b>An Exciting Time to Join Sonder!</b></p> <p>Since our founding in 2017, Sonder has experienced rapid growth, expanding operations across Australia, New Zealand, and the UK. Backed by Australia's leading venture capital firms, Seek and Blackbird, we are well-capitalised and on a mission to scale globally, partnering with corporations, educational institutions, and government agencies to transform workplace wellbeing at scale.</p> <p>Our impact and scale:</p> <ul> <li>1,000,000+ members across multiple countries</li> <li>200+ team members, plus an extensive network of on-the-ground responders</li> </ul> <p>If you're passionate about using technology and human expertise to drive meaningful change, join us in shaping the future of workplace wellbeing!</p> <b>Role Summary</b> <p>Are you a recent PhD graduate or Postdoctoral researcher passionate about applying cutting edge AI to solve real world problems? Join Sonder as an Applied Machine Learning Scientist/Engineer - focusing on LLM Research & Fine Tuning Engineering, and help us build a new generation of AI systems that directly impact human well being and safety.</p> <p>This is a unique opportunity for a PhD level candidate to apply their deep academic knowledge to a mission driven environment. This role is distinct from typical AI tooling or RAG based roles.</p> <p>We are not seeking candidates whose primary experience is in building vector search systems or integrating off the shelf APIs. Instead, we require deep, hands on expertise with the internal workings of large language models. Your work will be instrumental in developing our personalisation engine and fine tuning state of the art open source LLMs like LLaMa, Mistral, and DeepSeek. Your research will translate directly into creating specialised LLMs that provide empathetic, life saving support to our members.</p> <p>We're looking for someone who thrives on technical challenges and wants to see their expertise translate into a positive, tangible impact.</p> <b>Key Responsibilities</b> <ul> <li>Research, fine tune, and optimise open source LLMs using techniques such as PEFT, LoRA, and QLoRA to build our proprietary AI models.</li> <li>Contribute to the design and implementation of our personalisation and recommendation engines to deliver tailored, proactive support.</li> <li>Develop and maintain robust machine learning pipelines for model training, evaluation, and deployment.</li> <li>Collaborate closely with cross functional teams, including product managers, software engineers, and mental health professionals, to translate research into effective product features.</li> <li>Stay current with the latest advancements in AI and LLM research, and apply new techniques to improve our systems.</li> <li>Publish and/or present research findings at conferences or in academic journals where appropriate, contributing to the broader AI community.</li> </ul> <b>Key Qualifications</b> <ul> <li>A recently completed <b>PhD</b> or <b>Postdoctoral experience</b> in Machine Learning, AI, Computer Science, or a closely related quantitative field.</li> <li>Deep theoretical and practical understanding of Transformer architectures, attention mechanisms, and training dynamics.</li> <li>Hands on experience fine tuning open source LLMs (e.g., LLaMa, Mistral, DeepSeek).</li> <li>Strong computer science fundamentals and coding proficiency in Python.</li> <li>Solid experience with deep learning frameworks such as PyTorch or TensorFlow.</li> <li>A profound passion for applying AI to high impact, meaningful domains such as mental health and well being.</li> </ul> <p><b>Candidates with primary experience limited to building Retrieval Augmented Generation (RAG) systems or MLOps tooling are not a suitable fit for this specific role.</b></p> <b>Nice to Have</b> <ul> <li>Experience with <b>distributed training</b> techniques for large models.</li> <li>Familiarity with cloud based machine learning stacks (e.g., <b>AWS, GCP</b>).</li> <li>A track record of <b>peer reviewed publications</b> in top tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, AAAI, ACL).</li> </ul> <b>Eligibility</b> <ul> <li>The right to work full time in Australia</li> <li>Located within commuting distance to our Sydney office at the time of commencement.</li> </ul> <b>Impact & Growth</b> <p>Your work at Sonder will go beyond just optimising models; it will directly contribute to saving lives and improving mental well being on a global scale. This role offers the opportunity to shape our core AI technology from the ground up while growing as a leader in a supportive, mission driven environment. You will have the freedom to explore new research ideas and the resources to see them through to deployment, making a tangible difference in the world.</p> <b>Why Join Sonder?</b> <p>At Sonder, we thrive in a fast paced, high performance environment with a strong commitment to our people. Our team is a collaborative, vibrant group of passionate professionals, dedicated to making a real impact on people's lives every day.</p> <ul> <li>Hybrid and flexible working environment. Enjoy the perfect balance of in office collaboration and work from home flexibility, empowering you to optimise your productivity and work life balance.</li> <li>Gain free access to the Sonder app for you and your family, offering 24/7 on demand support for health, wellbeing, and safety.</li> <li>$1000 annual contribution as part of your development plan + 2 days of study leave</li> <li>Paid parental leave with an attractive return to work policy, 12 weeks for Primary Carers and 4 weeks for Secondary Carers, plus our Primary Carers return to work at 80% for the first 3 months at full pay.</li> <li>Participate in our Employee Share Option Plan (ESOP) for you to be a part of Sonder's success.</li> <li>Salary Packaging and novated leasing</li> <li>Access $250 annually to fund to invest in your wellbeing, empowering you to choose the support that best fits your needs.</li> <li>Free coffee on Tuesdays and catered lunch on Thursdays.</li> <li>Team social fund to connect with your team, plus monthly company wide social events.</li> <li>Dog friendly office.</li> <li>Volunteer leave. 2 days per year to participate in meaningful causes and contribute back to the community.</li> </ul> <p>Check out our life page for more info - </p> <b>Sonder is for Everyone</b> <p>We're committed to building a diverse and inclusive workplace. We encourage applications from people of all backgrounds, experiences, abilities and identities. If you need any support with your application or the recruitment process, please reach out - we'd love to hear from you.</p> <p>Due to the nature of our industry, all Sonder employees are required to complete a National Police Check and Working With Children Check.</p>

Applied Machine Learning Scientist/Engineer - LLMs (Recent PhD Grad)

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Interested to build the next generation Financial systems that can handle billions of dollars in transactions? Interested to build highly scalable next generation systems that could utilize Amazon Cloud?<br>
Massive data volume + complex business rules in a highly distributed and service oriented architecture, a world class information collection and delivery challenge. Our challenge is to deliver the software systems which accurately capture, process, and report on the huge volume of financial transactions that are generated each day as millions of customers make purchases, as thousands of Vendors and Partners are paid, as inventory moves in and out of warehouses, as commissions are calculated, and as taxes are collected in hundreds of jurisdictions worldwide.<br>
<br>
Key job responsibilities<br>
<ul><li>Understand the business and discover actionable insights from large volumes of data through application of machine learning, statistics or causal inference.
</li><li>Analyse and extract relevant information from large amounts of Amazon&rsquo;s historical transactions data to help automate and optimize key processes</li><li>Research, develop and implement novel machine learning and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection.</li><li>Use machine learning and analytical techniques to create scalable solutions for business problems.</li><li>Identify new areas where machine learning can be applied for solving business problems.</li><li>Partner with developers and business teams to put your models in production.</li><li>Mentor other scientists and engineers in the use of ML techniques.</li></ul><br>
A day in the life<br>
<ul><li>Understand the business and discover actionable insights from large volumes of data through application of machine learning, statistics or causal inference.
</li><li>Analyse and extract relevant information from large amounts of Amazon&rsquo;s historical transactions data to help automate and optimize key processes</li><li>Research, develop and implement novel machine learning and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection.</li><li>Use machine learning and analytical techniques to create scalable solutions for business problems.</li><li>Identify new areas where machine learning can be applied for solving business problems.</li><li>Partner with developers and business teams to put your models in production.</li><li>Mentor other scientists and engineers in the use of ML techniques.</li></ul><br>
About the team<br>
The FinAuto TFAW(theft, fraud, abuse, waste) team is part of FGBS Org and focuses on building applications utilizing machine learning models to identify and prevent theft, fraud, abusive and wasteful(TFAW) financial transactions across Amazon. Our mission is to prevent every single TFAW transaction. As a Machine Learning Scientist in the team, you will be driving the TFAW Sciences roadmap, conduct research to develop state-of-the-art solutions through a combination of data mining, statistical and machine learning techniques, and coordinate with Engineering team to put these models into production. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</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></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms</li><li>Experience in professional software development</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, FinAuto

MAERSK

<p></p><div><p><b>Associate AI/ML Scientist &ndash; Global Data Analytics, Technology (Maersk)<br>
</b></p><br>
This position will be based in India &ndash; Bangalore/Pune
<br>
<br>
<b>A.P. Moller - Maersk
</b><br>
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A.P. Moller &ndash; Maersk is the global leader in container shipping services. The business operates in 130 countries and employs 80,000 staff. An integrated container logistics company, Maersk aims to connect and simplify its customers&rsquo; supply chains.
<br>
<br>
Today, we have more than 180 nationalities represented in our workforce across 131 Countries and this mean, we have elevated level of responsibility to continue to build inclusive workforce that is truly representative of our customers and their customers and our vendor partners too.
<br>
<br>
<b>The Brief
</b><br>
<br>
In this role as an AI/ML Scientist on the Global Data and Analytics (GDA) team, you will support the development of strategic, visibility-driven recommendation systems that serve both internal stakeholders and external customers. This initiative aims to deliver actionable insights that enhance supply chain execution, support strategic decision-making, and enable innovative service offerings.
<br>
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You should be able to design, develop, and implement machine learning models, conduct deep data analysis, and support decision-making with data-driven insights. Responsibilities include building and validating predictive models, supporting experiment design, and integrating advanced techniques like transformers, GANs, and reinforcement learning into scalable production systems.
<br>
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The role requires solving complex problems using NLP, deep learning, optimization, and computer vision. You should be comfortable working independently, writing reliable code with automated tests, and contributing to debugging and refinement.
<br>
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You&rsquo;ll also document your methods and results clearly and collaborate with cross-functional teams to deliver high-impact AI/ML solutions that align with business objectives and user needs.
<br>
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<b>What I'll be doing &ndash; your accountabilities?
</b><br>
<ul><li>Design, develop, and implement machine learning models, conduct in-depth data analysis, and support decision-making with data-driven insights
</li><li>Develop predictive models and validate their effectiveness
</li><li>Support the design of experiments to validate and compare multiple machine learning approaches
</li><li>Research and implement cutting-edge techniques (e.g., transformers, GANs, reinforcement learning) and integrate models into production systems, ensuring scalability and reliability
</li><li>Apply creative problem-solving techniques to design innovative models, develop algorithms, or optimize workflows for data-driven tasks
</li><li>Independently apply data-driven solutions to ambiguous problems, leveraging tools like Natural Language Processing, deep learning frameworks, machine learning, optimization methods and computer vision frameworks
</li><li>Understand technical tools and frameworks used by the team, including programming languages, libraries, and platforms and actively support debugging or refining code in projects
</li><li>Write and integrate automated tests alongside their models or code to ensure reproducibility, scalability, and alignment with established quality standards
</li><li>Contribute to the design and documentation of AI/ML solutions, clearly detailing methodologies, assumptions, and findings for future reference and cross-team collaboration
</li><li>Collaborate across teams to develop and implement high-quality, scalable AI/ML solutions that align with business goals, address user needs, and improve performance
</li></ul><br>
<b>Foundational Skills
</b><br>
<ul><li>Mastered <b>Data Analysis and Data Science </b>concepts and can demonstrate this skill in complex scenarios
</li><li><b>AI &amp; Machine Learning, Programming and Statistical Analysis </b>Skills beyond the fundamentals and can demonstrate the skills in most situations without guidance.
</li></ul><br>
<b>Specialized Skills
</b><br>
<ul><li>To be able to understand beyond the fundamentals and can demonstrate in most situations without guidance:
<ul><li>Data Validation and Testing
</li><li>Model Deployment
</li><li>Machine Learning Pipelines
</li><li>Deep Learning
</li><li>Natural Language Processing (NPL)
</li><li>Optimization &amp; Scientific Computing
</li><li>Decision Modelling and Risk Analysis.
</li></ul></li><li>To understand fundamentals and can demonstrate this skill in common scenarios with guidance:
<ul><li>Technical Documentation.
</li></ul></li></ul><br>
<b>Qualifications &amp; Requirements
</b><br>
<ul><li>Bachelor's degree in B.E/BTech, preferably in computer science
</li><li>Experience with collaborative development workflow: IDE (Integrated Development Environment), Version control(github), CI/CD (e.g. automated tests in github actions)
</li><li>Communicate effectively with technical and non-technical audiences with experience in stakeholder management
</li><li>Structured, highly analytical mind-set and excellent problem-solving skills;
</li><li>Self-starter, highly motivated &amp; Willing to share knowledge and work as a team.
</li><li>An individual who respects the opinion of others; yet can drive a decision though the team;
</li></ul><br>
<b>Preferred Experiences<br>
</b><br>
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<ul><li>5+ years of years of relevant experience in the field of Data Engineering
</li><li>3+ years of hands-on experience with Apache Spark, Python and SQL
</li><li>Experience working with large datasets and big data technologies to train and evaluate machine learning models.
</li><li>Experience with containerization: Kubernetes &amp; Docker
</li><li>Expertise in building cloud native applications and data pipelines (Azure, Databricks, AWS, GCP) C
</li><li>Experience with common dashboarding and API technologies (PowerBI, Superset, Flask, FastAPI, etc
</li></ul><br>
<i>As a performance-oriented company, we strive to always recruit the best person for the job &ndash; regardless of gender, age, nationality, sexual orientation or religious beliefs. We are proud of our diversity and see it as a genuine source of strength for building high-performing teams.<br>
</i><br>
<p></p><p>Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.<br>
</p><p></p><p>We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing accommodationrequests@maersk.com .</p></div><p></p>

AI/ML Scientist

State Street

<div><div>About the Role</div><div>
We are seeking a highly motivated and technically skilled Data Scientist to join our AI/ML science team as part of the Agentic AI platform buildout. The Science pillar advances LLM research, fine‑tuning, evaluation frameworks, anomaly detection, and frontier model development&mdash;partnering closely with Platform Engineering, SRE, and Pods/Business Engagement to ship production-grade agents and platform features.</div><div></div><div>
This role will focus on applied research and product-oriented data science requirements &ndash; designing and validating domain-specific LLM solutions, building evaluation taxonomies and metrics and operationalizing fine-tuning/tooling for business use cases.</div><div></div><div>
Key Responsibilities</div><ul><li><div>
Own BU specific problem statements and objectives to deliver value leveraging agentic AI workflows and domain LLMs</div></li><li><div>
LLM research and fine-tuning including evaluating foundational models, fine-tuning and prompt optimization with robust data curation and governance alignment</div></li><li><div>
Evaluation frameworks &amp; taxonomies and Frontier model evaluation and buildout</div></li><li><div>
Develop and maintain knowledge graphs and embeddings for semantic search and reasoning</div></li><li><div>
Inference engine for scalable, low latency serving for tuned models, agentic workflows and cost optimization</div></li><li><div>
Collaborate with engineering teams to deploy scalable AI solutions in production environments.</div></li><li><div>
Conduct experiments and evaluations to benchmark model performance and ensure robustness</div></li><li><div>
Opportunity to Research, document and socialize</div></li></ul><div></div><ul><li><div>
Required Qualifications</div></li></ul><ul><li><div>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, Machine Learning, or related field.</div></li><li><div>
1+ years of experience in applied machine learning or NLP.</div></li><li><div>
Hands-on experience with LLM&rsquo;s, GenAI or NLP at production scale</div></li><li><div>
Strong understanding of graph databases (e.g., Neo4j, RDF, DGL) and knowledge graph construction.</div></li><li><div>
Proficiency in Python and ML libraries (PyTorch, TensorFlow, Scikit-learn).</div></li><li><div>
Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.</div></li><li><div>
Prior work on agentic AI is a big plus</div></li></ul><div></div><div>
About State Street<br>
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What we do. State Street is one of the largest custodian banks, asset managers and asset intelligence companies in the world. From technology to product innovation, we&rsquo;re making our mark on the financial services industry. For more than two centuries, we&rsquo;ve been helping our clients safeguard and steward the investments of millions of people. We provide investment servicing, data &amp; analytics, investment research &amp; trading and investment management to institutional clients.<br>
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Work, Live and Grow. We make all efforts to create a great work environment. Our benefits packages are competitive and comprehensive. Details vary by location, but you may expect generous medical care, insurance and savings plans, among other perks. You&rsquo;ll have access to flexible Work Programs to help you match your needs. And our wealth of development programs and educational support will help you reach your full potential.<br>
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Inclusion, Diversity and Social Responsibility. We truly believe our employees&rsquo; diverse backgrounds, experiences and perspectives are a powerful contributor to creating an inclusive environment where everyone can thrive and reach their maximum potential while adding value to both our organization and our clients. We warmly welcome candidates of diverse origin, background, ability, age, sexual orientation, gender identity and personality. Another fundamental value at State Street is active engagement with our communities around the world, both as a partner and a leader. You will have tools to help balance your professional and personal life, paid volunteer days, matching gift programs and access to employee networks that help you stay connected to what matters to you.<br>
<br>
State Street is an equal opportunity and affirmative action employer.</div><div></div><div>
About State Street</div><div></div><div>
Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.</div><div></div><div>
We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you&rsquo;ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.</div><div></div><div>
As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.</div><div></div><div>
Discover more information on jobs at <div>StateStreet.com/careers</div></div><div></div><div>
Read our <div>CEO Statement</div></div></div>

Data Scientist – Agentic AI / Graph/ LLM Science , Senior Associate

YO IT CONSULTING

<div><div><div><p><b>hiring a Data Scientist</b> to help build advanced analytics and data-driven infrastructure for its AI lab partner focused on developing intelligent agent-based systems. This role is ideal for analytical thinkers who excel at turning large-scale data into actionable insights and enjoy working at the intersection of machine learning, experimentation, and real-world applications. You&rsquo;ll be designing data pipelines, statistical models, and performance metrics that drive the next generation of autonomous systems.</p>
<h2 class="jobSectionHeader"><b>You&rsquo;re a great fit if you:</b></h2>
<ul><li><p>Have a strong background in <b>data science, machine learning, or applied statistics</b>.</p>
</li><li><p>Are proficient in <b>Python, SQL</b>, and familiar with libraries such as <b>Pandas, NumPy, Scikit-learn, and PyTorch/TensorFlow</b>.</p>
</li><li><p>Understand <b>probabilistic modeling, statistical inference, and experimentation frameworks (A/B testing, causal inference)</b>.</p>
</li><li><p>Can <b>collect, clean, and transform complex datasets</b> into structured formats ready for modeling and analysis.</p>
</li><li><p>Have experience designing and evaluating <b>predictive models</b>, using metrics like precision, recall, F1-score, and ROC-AUC.</p>
</li><li><p>Are comfortable working with <b>large-scale data systems</b> (Snowflake, BigQuery, or similar).</p>
</li><li><p>Are curious about <b>AI agents</b>, and how data can shape the reasoning, adaptability, and behavior of intelligent systems.</p>
</li><li><p>Enjoy <b>collaborating with cross-functional teams</b> &mdash; from engineers to research scientists &mdash; to define meaningful KPIs and experiment setups.</p>
</li></ul><h2 class="jobSectionHeader"><b>Primary Goal of This Role</b></h2>
<p>To design and implement robust data models, pipelines, and metrics that support experimentation, benchmarking, and continuous learning for agentic AI systems. The role focuses on building data-driven insights into how agents reason, perform, and improve over time across algorithmic and real-world tasks.</p>
<h2 class="jobSectionHeader"><b>What You&rsquo;ll Do</b></h2>
<ul><li><p>Develop <b>data collection and preprocessing pipelines</b> for structured and unstructured data from multiple agent simulations.</p>
</li><li><p>Build and iterate on <b>machine learning models</b> for performance prediction, behavior clustering, and outcome optimization.</p>
</li><li><p>Design and maintain <b>dashboards and visualization tools</b> for monitoring agent performance, benchmarks, and trends.</p>
</li><li><p>Conduct <b>statistical analyses</b> to evaluate the efficacy of AI systems under various environments and constraints.</p>
</li><li><p>Collaborate with engineers to design <b>evaluation frameworks</b> that measure reasoning quality, adaptability, and efficiency.</p>
</li><li><p>Prototype <b>data-driven tools and feedback loops</b> to automatically improve model accuracy and agent behavior over time.</p>
</li><li><p>Work closely with AI research teams to <b>translate experimental results</b> into scalable, production-grade insights.</p>
</li></ul><h2 class="jobSectionHeader"><b>Why This Role Is Exciting</b></h2>
<ul><li><p>Work at the forefront of <b>AI agent intelligence</b> and help define how data shapes their evolution.</p>
</li><li><p>Blend <b>machine learning, experimentation, and data engineering</b> in one role.</p>
</li><li><p>Collaborate with top-tier AI engineers on <b>new agent benchmarks and feedback mechanisms</b>.</p>
</li><li><p>Contribute to a mission that merges <b>algorithmic reasoning, real-world performance, and human-like decision-making</b>.</p>
</li></ul><h2 class="jobSectionHeader"><b>Pay &amp; Work Structure</b></h2>
<ul><li><p><b>Part-time (20 hrs - 40 hrs/week)</b></p>
</li><li><p>Weekly bonus of $500 - $1000 USD per 5 task created.</p>
</li></ul></div></div><div><div><h2 class="jobSectionHeader"><b>Contract and Payment Terms</b></h2>
<ul><li>You will be engaged as an independent contractor.</li>
<li>This is a fully remote role that can be completed on your own schedule.</li>
<li>Projects can be extended, shortened, or concluded early depending on needs and performance.</li>
<li>Your work at will not involve access to confidential or proprietary information from any employer, client, or institution.</li>
<li>Payments are weekly on Stripe or Wise based on services rendered.</li></ul></div></div></div>

Data Scientist Machine Learning - Remote

<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, Business Data Technologies

<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>
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Applied Scientist II, Business Data Technologies

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