applied scientist

Audible

<div>
 
 Description
 
 
 
 At Audible, we believe stories have the power to transform lives. It&rsquo;s why we work with some of the world&rsquo;s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us.
 
 
 
 About This Role
 
 
 
 As an Applied Scientist, you will solve large complex real-world problems at scale, draw inspiration from the latest science and technology to empower undefined/untapped business use cases, delve into customer requirements, collaborate with tech and product teams on design, and create production-ready models that span various domains, including Machine Learning (ML), Artificial Intelligence (AI) and Generative AI, Natural Language Processing (NLP), Reinforcement Learning (RL), real-time and distributed systems.
 
 
 
 About You
 
 
 
 Your work will focus on inventing or adapting scientific approaches, models, and algorithms driven by customer needs at the project level. You will develop components and/or end-to-end solutions that are deployed into production or directly support production systems, delivering consistently high-quality work that meets both scientific and engineering best practices. You will develop reusable science components and services that resolve architecture deficiencies and customers&rsquo; pain points, while making technical trade-offs for long-term/short- term. You will work semi-autonomously to deliver solutions, contribute to research papers at peer-reviewed venues when appropriate, and document your work thoroughly to enable others to understand and reproduce it. Your decision-making will consistently incorporate robust, data-driven business and technical judgment. You will collaborate with other scientists to raise the bar of both scientific and engineering complexity for the team and to foster valuable scientific partnership opportunities to help/guide science decisions. We work in a highly collaborative, fast-paced environment where scientists, engineers, and product managers work to test and build scalable foundational capabilities, as well as customer facing experiences. You will have the opportunity to innovate and think big within your projects scope, implement optimization services and algorithms, and influence the experiences of millions of customers. We are looking for a results-oriented Applied Scientist with deep knowledge in ML, NLP, Deep Learning, GenAI, and/or large-scale distributed computation.
 
 
 As an Applied Scientist, you will...
 
 
 <ul>
 <li>
 Understand use cases across the business and adopt/extend/design/invent solutions/models that are scalable, efficient, and automated for difficult problems that are not well defined
 </li>
 <li>
 Work closely with fellow scientists and software engineers (at Audible and Amazon) to build and productionize models, deliver novel and highly impactful features
 </li>
 <li>
 Review models of peers for the purpose of reducing and managing risk to the business, while improving customer experience
 </li>
 <li>
 Design, develop, and deploy modeling techniques and solutions for Content Understanding, Recommendations, GenAI-based product features, by employing a wide range of methodologies, working from simple to complex
 </li>
 <li>
 Contribute to initiatives that employ the most recent advances in ML/AI in a fast-paced, experimental environment
 </li>
 <li>
 Push the boundary of innovation
 
 
 </li>
 </ul>
 
 About Audible
 
 
 
 Audible is the leading producer and provider of audio storytelling. We spark listeners&rsquo; imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.
 
 
 
 Basic Qualifications
 
 
 
 <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>
 MSc + 5ys of relevant experience, or PhD +1 year in one of the following disciplines: Machine Learning, Computer Science, Computer Engineering, Data Science, Applied Math, or a related quantitative field
 </li>
 <li>
 3+ years of experience in Deep Learning, Natural Language
 </li>
 <li>
 Processing/Understanding, GenAI and/or Reinforcement Learning
 </li>
 <li>
 Proficiency in Python, SQL, and other scripting languages
 </li>
 <li>
 Experience employing and innovating with LLMs/GenAI to solve complex problems
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience using Unix/Linux
 </li>
 <li>
 Experience in professional software development
 </li>
 <li>
 Experience with building Recommendation Systems
 </li>
 <li>
 Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions) or similar cloud-platforms
 
 
 </li>
 </ul>
 Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
 
 
 m/w/d
 
 
 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.
 
 
 
 
 Company
 
 - Audible GmbH - B38
 
 
 Job ID: A10450357
</div>

Applied Scientist

TomTom

<div>
 You'll join the ALF (Localization Features) team within TomTom's ADAS &amp; ADS Product Unit, which develops the HD maps and ADAS technology that powers real-time location intelligence for major automotive and tech companies. ALF is responsible for the localization features layer of the HD map and the ML systems that extract them from real-world sensor data at world scale.
 
 
 You'll work shoulder-to-shoulder with applied scientists and software engineers, partner with adjacent teams, and own the quality trajectory of features that ship to customers under product targets.
 
 
 
 What You Will Do
 
 
 
 <ul>
 <li>
 Work with a team of senior engineers and applied scientists to develop high-quality algorithms and ML software that powers TomTom's HD maps for ADAS.
 </li>
 <li>
 Contribute to the design, implementation, and integration of algorithms, ML systems, and data pipelines within your area of focus, from problem framing through experimentation to production rollout.
 </li>
 <li>
 Contribute to measurable improvements in output quality (recall, precision, latency, cost) against hard customer-facing targets.
 </li>
 <li>
 Own well-scoped components within the team's processing pipelines, from upstream input data through algorithmic and ML processing to validated outputs published to downstream consumers.
 </li>
 <li>
 Tackle complex technical problems at scale noisy upstream signals, geospatial geometry, ground truth quality, and large-scale evaluation pipelines.
 </li>
 <li>
 Build iteratively using agile methodologies and rigorous experimentation; document outcomes so the team can build on them.
 </li>
 <li>
 Support junior engineers and interns, and contribute to hiring as an interviewer.
 
 
 </li>
 </ul>
 
 What You Will Need
 
 
 
 <ul>
 <li>
 3+ years of professional Applied Science, Machine Learning, algorithm development, or related experience.
 </li>
 <li>
 Bachelor's degree (minimum) in Computer Science, Machine Learning, Computer Vision, Geospatial Science, Statistics, or a related quantitative field. Master's or PhD a plus.
 </li>
 <li>
 Solid fundamentals in algorithm design and analysis data structures, complexity reasoning, and applied algorithms for geospatial and signal-processing problems.
 </li>
 <li>
 Solid fundamentals in machine learning model training and evaluation, statistics, and experimental design.
 </li>
 <li>
 Proficiency in Python; experience with at least one ML framework (PyTorch, TensorFlow, or equivalent) and at least one large-scale data processing framework (Spark, Databricks, or equivalent).
 </li>
 <li>
 Experience taking algorithms, ML models, or data pipelines into production, not just running experiments offline.
 </li>
 <li>
 Breadth across applied science comfortable working across algorithms, modeling, evaluation, ground truth quality, and methodology. You should be able to pick up a new sub-domain quickly rather than only operating in a single area of expertise.
 </li>
 <li>
 Working familiarity with several of the following (in depth experience is not needed) algorithm design for geospatial and geometric problems (polygon geometry, map-matching, spatial indexing), classical ML and clustering on noisy sensor data, computer vision (detection, segmentation), data and ML pipelines at scale (training pipelines, MLOps, dataset generation).
 </li>
 <li>
 Comfortable with written and verbal communication in English.
 </li>
 <li>
 Curiosity and desire to learn, and to expand your skill set across the ML stack.
 </li>
 <li>
 Ability to solve a complex problem on your own by leveraging experience, peers, and other resources.
 
 
 </li>
 </ul>
 
 What We Offer
 
 
 
 A competitive compensation package, of course.
 
 
 Time and resources to grow and develop, including a personal development budget and paid leave for learning days, as well as paid access to e-learning resources such as O&rsquo;Reilly and LinkedIn Learning.
 
 
 Time to support life outside of work, with enhanced parental leave plus paid leave to care for loved ones and volunteer in local communities.
 
 
 Work flexibility, where TomTom&rsquo;ers, in agreement with their manager and team, use both the office and home to focus, collaborate, learn and socialize. It&rsquo;s all about getting the best out of both worlds &ndash; we ask TomTom&rsquo;ers to come to the office two days a week, and the remaining three are free to be worked in either location.
 
 
 Improve your home office with a setup budget and get extra support with a monthly allowance.
 
 
 Enjoy options to work from your home country and abroad for a set number of days each year, to visit family and friends, or to simply explore the world we&rsquo;re mapping.
 
 
 Take the holidays you want with a competitive holiday plan, plus an extra day off to celebrate your birthday.
 
 
 Join annual events like our Hackathon and DevDays to bring your ideas to life with talented teammates from around the world.
 
 
 Become a part of our inclusive global culture and have the chance to collaborate with a diverse community &ndash; we have over 80 nationalities at TomTom!
 
 
 Find out more about our global benefits and enjoy additional local benefits tailored to your location.
 
 
 
 Meet your team
 
 
 
 We are the ADAS &amp; ADS Product Unit, leading the production of TomTom&rsquo;s HD maps and ADAS technology.
 
 
 In a diverse team of applied scientists, engineers, data scientists, and more, equipped with a broad array of expertise, you&rsquo;ll collaborate on groundbreaking location-based technologies and applications.
 
 
 More specifically, you&rsquo;ll be at the forefront of the creation of advanced HD maps. You&rsquo;ll also help update these in real-time, ensuring our maps are pushing the world forward instantly. These maps will then go on to empower the largest car manufacturers, transportation giants, and major tech companies around the world.
 
 
 
 At TomTom...
 
 
 
 You&rsquo;ll help people find their way in the world. In 2004, TomTom revolutionized how the world moves with the introduction of the first portable navigation device. Now, we intend to do it again by engineering the first-ever real-time map, the smartest and most useful map on the planet.
 
 
 Work with a team of 3,300+ unique, curious and passionate problem-solvers. Together, we&rsquo;ll open up a world of possibilities for car manufacturers, enterprises and developers to help people understand and get closer to the world around them.
 
 
 
 After you apply
 
 
 
 Our recruitment team will work hard to give you a meaningful experience throughout your journey with us, no matter the outcome. Your application will be screened closely and you can rest assured that all follow-up actions will be thorough, from assessments and interviews all the way through onboarding. To find out more about our application process, check out our hiring FAQs .
 
 
 
 TomTom is an equal opportunity employer
 
 
 
 TomTom is where you can find your place in the world. Every day we welcome, nurture and celebrate differences. Why? Because your uniqueness is what makes you,
 
 you
 
 . No matter your culture or background, you&rsquo;ll find your impact at TomTom. Research also shows that sometimes women and underrepresented communities can be hesitant to apply for positions unless they believe they meet 100% of the criteria. If you can relate to this, please know that we&rsquo;d love to hear from you.
 
 
 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
</div>

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
Alexa is looking for an Applied Scientist with a strong background in Natural Language Processing (NLP) and Large Language Models (LLMs) to help build state-of-the-art conversational systems. 
 
In this role, you will collaborate with a large team of scientists training the Large Language Models that power the Alexa stack, as well as software engineers serving them in production systems. You will own solutions end-to-end: from ideation and research through to production deployment, enabling conversational assistants to support external tools, leverage diverse sources of information, and deliver novel reasoning capabilities to millions of Alexa customers. 
 
Key job responsibilities 
As an Applied Scientist, you will develop innovative solutions to complex problems to extend the functionalities of conversational assistants. 
 
You will use your technical expertise to research and implement novel algorithms and modelling solutions in collaboration with other scientists and engineers. 
 
You will analyze customer behaviors and define metrics to enable the identification of actionable insights and measure improvements in customer experience. 
 
You will communicate results and insights to both technical and non-technical audiences through written reports, presentations and external publications. 
 
You would be able to bi-modal on science and engineering: someone who combines strong scientific foundations with the execution skills to ship high-quality solutions. 
 
A day in the life 
As an Applied Scientist on the Alexa Science team, you'll drive innovation in evaluating new product experiences while discovering novel approaches to enhance model capabilities and enrich customer interactions. You'll collaborate with cross-functional teams of engineers and scientists to identify root causes of model and system integration issues, continuously improving the end-to-end customer experience. 
 
You'll partner closely with scientists developing and fine-tuning large language models, engineers building low-latency inference infrastructure, and product teams defining customer experience metrics. 
 
About the team 
We are a team of applied scientists and engineers building the intelligence layer that powers Alexa+. Our work sits at the intersection of large language models, decision-making under uncertainty, and production ML systems. What we build directly shapes the customer experience: determining which models serve their requests, optimizing response latency, and creating natural, seamless interactions. 
 
We're a collaborative team that values rigorous experimentation, clear communication, and delivering solutions that perform at scale in real-world environments.<h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>PhD, or a Master's degree and experience in CS, CE, ML or related field</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience in building machine learning models for business application</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience in patents or publications at top-tier peer-reviewed conferences or journals</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> 
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates. 
 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
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 - LLM, Alexa

Amazon

<div>
 
 Description
 
 
 
 Amazon's Middle Mile Science group is looking for an Applied Scientist to build machine learning and optimization models for large-scale transportation planning systems. This includes the development of dynamic pricing and network planning models to improve operations and services for our external freight customers.
 
 
 The Middle Mile Science group develops optimization and machine learning systems that power Amazon's freight transportation network, from network design and pricing to real-time load planning and capacity utilization. The scale of Amazon's fulfillment operations requires robust transportation networks that minimize cost while meeting all customer deadlines. Real-time execution depends on state-of-the-art optimization and artificial intelligence to coordinate thousands of operators and drivers. This includes shipper-facing and carrier-facing marketplace algorithms as well as network planning and optimization tools. Amazon often finds that existing techniques do not match our unique business needs, driving the innovation of new approaches and algorithms.
 
 
 As an Applied Scientist focusing on external freight within middle mile transportation, you will work closely with business leaders, engineers, and fellow scientists to design and build scalable products operating across multiple transportation modes. You will create experiments and prototypes of new machine learning and optimization applications, present research findings to senior leadership, and implement your models within production systems. You will write production-quality code designed for
 
 
 scalability and maintainability, and make decisions that affect how we build and integrate algorithms across our product portfolio.
 
 
 
 About The Team
 
 
 
 Our Middle Mile Marketplace Science team builds the algorithms for Amazon&rsquo;s rapidly growing freight marketplace. Amazon contracts with 3P shippers and a network of independent carriers, using a mix of contract structures with varying service and risk profiles. Our work focuses on mechanisms and learning algorithms to optimize pricing and matching in this complex marketplace, and continually improve the experience for carriers and shippers. This is an area with many challenging problems and a huge business impact for Amazon!
 
 
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 Experience programming in Java, C++, Python or related language
 </li>
 <li>
 Experience with discrete and continuous optimization methodologies and algorithms
 </li>
 <li>
 PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or equivalent quantitative field, or Master's degree and 5+ years of industry or academic research experience
 </li>
 <li>
 3+ years of building machine learning or optimization algorithms for business applications
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience in professional software development
 </li>
 <li>
 Experience in standard machine-learning and statistical modeling tools and techniques (e.g. random forests, gradient-boosted regression, LASSO, logistic regression)
 </li>
 <li>
 Strong track record of publications at top-tier journals or conferences
 </li>
 <li>
 Experience with integer programming, dynamic programming, and/or stochastic optimization
 
 
 </li>
 </ul>
 Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
 
 
 Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
 
 
 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.
 
 
 
 
 Company
 
 - Amazon UK Services Ltd.
 
 
 Job ID: A10379006
</div>

Applied Scientist, Amazon Transportation

Zalando

<div><div>Ort</div><div>
Germany - Berlin</div><div>
Vertrag</div><div>
Full time</div><div>
Job-Kategorie</div><div>
Applied Science &amp; Research</div></div>
 <div><div>Junior Applied Scientist (all genders) - B2B Data Science and Algorithms
The ZEOS department is responsible for all partner-facing Zalando Logistics Solutions. We provide a holistic approach to delivering the fulfillment solutions that meet our partner&rsquo;s needs by unifying these services under a single umbrella. We aim to provide our partners with a profitable fulfillment experience, and we see that to do this, Machine Learning, Operations Research, and data-driven solutions will play a pivotal role.
We are seeking a highly motivated Junior Applied Scientist who is fueled by the desire to kickstart their career by building innovative and impactful ML/Optimization systems for our B2B logistics partners. You will join an established team of Senior Applied Scientists and Machine Learning Engineers, working in a cross-functional setup with Product Managers, Data Engineers, and Software Engineers.
The team&rsquo;s focus is helping our B2B partners improve inventory health and order fulfillment efficiency. With guidance and mentorship from senior team members, you will contribute to building various ML/DL forecasting models (demand, returns, lead-times), stochastic inventory optimization solutions, recommendation services, and emerging Agentic AI systems. You will play a key role in a cross-functional team where your eagerness to learn and grow will directly translate into value for our partners!
WHY YOU SHOULD BE INTERESTED&hellip;<ul><li>
Learn and Impact from Day One: You won't be stuck doing busywork. You will be an active scientific partner, working alongside experienced scientists and product teams to define problems and build solutions. Your fresh perspective will help identify new opportunities to create value for our partners.</li><li>
Tackle Complex Scientific Problems with Expert Guidance: This is your chance to bridge the gap between academia and industry. You'll tackle cutting-edge challenges in stochastic inventory optimization, multi-echelon demand forecasting, and recommender systems while receiving the mentorship needed to succeed.</li><li>
Explore Emerging Tech like Agentic AI: As we explore opening up MCP servers to our partners, you will assist in defining how we measure their performance. You will contribute to implementing evaluation frameworks (e.g., LLM-as-a-judge, safety guardrails) to ensure autonomous systems act reliably.</li><li>
Grow into End-to-End Ownership: You will have the opportunity to follow ideas from initial research and prototyping to production. You will learn how to define success metrics, collaborate with engineers to deploy scalable services, and monitor real-world impact on partner KPIs.</li><li>
Drive Impact at a Multi-Merchant Scale: Your contributions will help build platform-level services that scale across hundreds of diverse partners, shaping the future of a more sustainable and efficient e-commerce logistics network.</li></ul> 
WE&rsquo;D LOVE TO MEET YOU IF&hellip;<ul><li>
Educational background in a quantitative field; Masters degree or higher preferred.</li><li>
Up to 2 years of hands-on experience (including internships, working student roles, or significant academic/thesis projects) applying scientific methods to solve complex problems.</li><li>
A solid theoretical foundation and practical exposure in at least one of the following areas:</li><li>
Machine Learning or Deep Learning for time-series forecasting (e.g., LGBM, ARIMA, Prophet, Transformers).</li><li>
Operations Research and Optimization (e.g., stochastic inventory models, linear/integer programming, Monte Carlo simulations).</li><li>
Machine Learning Engineering basics (e.g., understanding of git, batch processing, basic software testing).</li><li>
Agentic AI &amp; MCP evaluation frameworks</li><li>
Proficiency in SQL and Python, with some exposure to working with datasets.</li><li>
Strong communication skills with the ability to explain scientific concepts clearly and a desire to learn how to communicate effectively with business stakeholders.</li><li>
A collaborative, growth-oriented mindset. You have a passion for learning by doing and are not afraid to ask questions.</li><li>
You thrive in our team's core value: &ldquo;High Challenge, High Support&rdquo;! We cherish an open, direct feedback culture and are here to help you develop into a world-class scientist.</li></ul>
INCLUSIVE BY DESIGN
At Zalando, our vision is to be the leading pan-European ecosystem for fashion and lifestyle e-commerce - one that is inclusive by design. We only assess candidates based on qualifications, merit, and business needs. We welcome applications from people of all gender identities, sexual orientations, personal expressions, racial identities, ethnicities, religious beliefs, and disability statuses. We only want to know why you're great for this role, so please avoid including your picture, age, and marital status in your CV as well.
We want to provide you with a great candidate experience. Please feel free to inform us of any accommodations you may need, so we can best support and assist you throughout the hiring process.
do.BETTER - our diversity &amp; inclusion strategy: https://jobs.zalando.com/en/our-culture/diversity-and-inclusion
OUR OFFER<ul><li>
Zalando provides a range of benefits, here's an overview of what you can expect. Ask your Talent Acquisition Partner to learn more about what we offer.</li><li>
Employee shares program</li><li>
40% off fashion and beauty products sold and shipped by Zalando, 30% off Lounge by Zalando, discounts from external partners</li><li>
2 paid volunteering days per year</li><li>
27 days of vacation a year to start for full-time employees</li><li>
Family services, including counseling and support</li><li>
Health and wellbeing options (including Wellhub, formerly Gympass)</li><li>
Mental health support and coaching available</li><li>
Drive your development through our training platform and biannual peer-to-peer review</li></ul></div><div>
Recruiter
Casimir Udegbunam
casimir.udegbunam@zalando.de</div><div>
 Nach der Pr&uuml;fung werden unsere Recruiter*innen &uuml;ber eine offizielle Zalando E-Mail-Adresse (@zalando.de) Kontakt aufnehmen.
In einigen F&auml;llen arbeiten wir auch mit einer Auswahl von Headhunter*innen und Agenturen zusammen, um bestimmte Positionen zu besetzen. Bitte beachte, dass weder Zalando noch unsere Rekrutierungspartner*innen irgendeine Art von Bezahlung verlangen, um sich f&uuml;r eine Stelle zu bewerben oder an einem Vorstellungsgespr&auml;ch teilzunehmen.</div></div>
 <div></div><div><div><div><h2 class="jobSectionHeader">&Uuml;ber Zalando</h2>
Zalando wurde 2008 in Berlin gegr&uuml;ndet und ist die f&uuml;hrende europ&auml;ische Technologieplattform f&uuml;r Mode und Lifestyle. Wir verbinden 62 Millionen aktive Kund*innen mit mehr als 7.000 Marken in 29 M&auml;rkten. Unser Gesch&auml;ft basiert auf einer einzigartigen, KI-gest&uuml;tzten Daten- und Infrastrukturplattform. F&uuml;r unsere Kund*innen bietet unser Multi-App-Ansatz &ndash; bestehend aus Zalando, ABOUT YOU und Lounge by Zalando &ndash; ein inspirierendes, hochgradig personalisiertes Einkaufserlebnis. F&uuml;r unsere Partner bauen wir das Betriebssystem f&uuml;r den E-Commerce. &Uuml;ber ZEOS, Tradebyte und SCAYLE &ouml;ffnen wir unsere Logistik-, Software- und Servicekapazit&auml;ten f&uuml;r Marken und Einzelh&auml;ndler*innen zur nahtlosen, grenz&uuml;berschreitenden Skalierung ihres Gesch&auml;fts.</div></div></div>

Junior Applied Scientist (all genders)

Oracle

<div>The IC5 Applied Scientist for Robotics, Perception, and Embodied AI will serve as a senior technical leader responsible for defining, prototyping, and delivering AI capabilities for commercially viable robotic systems. This role partners across science, software engineering, product, and hardware teams to identify high-impact opportunities, translate ambiguous product needs into research and engineering roadmaps, and guide end-to-end solution development from data collection and experimentation through production deployment. The scientist will lead applied research in multi-sensor fusion, real-time signals, perception, multimodal reasoning,
 
reinforcement learning, and action-conditioned planning, with a strong bias for hands-on execution and full-stack delivery.</div>
 <div><h1 class="jobSectionHeader">Key Responsibilities
</h1><h2 class="jobSectionHeader">Solution Identification and Strategy
</h2><ul><li>Partner with science, engineering, product, and hardware leaders to identify strategic product needs where robotics, perception, and embodied AI can create measurable customer and business impact.
</li><li>Evaluate academic literature, industry benchmarks, robotics platforms, and commercially viable robot APIs to assess feasibility, technical difficulty, and delivery risks.
</li><li>Break down ambiguous robotics and AI problems into clear research plans, model architectures, data requirements, evaluation criteria, and production milestones.
</li><li>Set science quality standards for applied robotics workstreams, including perception accuracy, latency, robustness, safety, reliability, and operational feedback metrics.
</li><li>Prioritize solutions using the scientific process, including modeling approaches, evaluation techniques, data collection strategies, and risk/reward tradeoffs.
</li></ul><h2 class="jobSectionHeader">Applied Research and Model Development
</h2><ul><li>Lead the design and execution of research programs and POCs for sensors, multi-sensor fusion, real-time signal processing, and perception systems.
</li><li>Develop and guide approaches for object detection, tracking, activity recognition, scene understanding, and related perception capabilities in real-world environments.
</li><li>Advance multimodal AI systems that combine signals such as camera, depth, lidar, audio, telemetry, proprioception, and task context.
</li><li>Apply reinforcement learning, action-conditioned planning, decision-making, and reasoning methods to enable robot behaviors that are robust, measurable, and product-relevant.
</li><li>Define dataset strategy, data quality criteria, labeling approaches, simulation or synthetic data opportunities, and evaluation protocols for robotics and embodied AI use cases.
</li><li>Guide model training, fine-tuning, optimization, inference design, and compute/latency tradeoffs for real-time or near-real-time deployment scenarios.
</li></ul><h2 class="jobSectionHeader">Solution Delivery and Production Integration
</h2><ul><li>Lead full-stack execution across experimentation, data pipelines, model development, evaluation, deployment integration, and production monitoring.
</li><li>Partner closely with software engineering, machine learning engineering, hardware teams, and product stakeholders to integrate AI capabilities into robotic systems and services.
</li><li>Evaluate and review high-complexity code, establish best practices for repositories, version control, code review, documentation, testing, and delivery readiness.
</li><li>Define operational metrics and user feedback loops to assess delivered solutions in production and inform future technical strategy.
</li><li>Serve as an escalation point for complex robotics, AI, perception, and systems integration issues, driving root-cause analysis and durable solutions.
</li></ul><h2 class="jobSectionHeader">Research Leadership and Influence
</h2><ul><li>Demonstrate thought leadership in at least one business-critical area such as robot perception, multimodal systems, sensor fusion, reinforcement learning, or embodied AI.
</li><li>Translate research insights into clear technical recommendations, patents, white papers, design documents, demos, or conference-quality publications where appropriate.
</li><li>Mentor and guide scientists and engineers, raising the bar for applied research rigor, experimentation quality, and production readiness.
</li><li>Establish productive collaborations with internal teams, external research groups, academic partners, or commercial robotics ecosystem partners where relevant.
</li></ul><h1 class="jobSectionHeader">Core Competencies
</h1><ul><li>Bias for action with a strong hands-on orientation; able to move from ambiguous idea to prototype, evaluation, and production path quickly.
</li><li>Ability to execute full-stack AI workflows spanning data, experimentation, modeling, evaluation, APIs, deployment, and feedback loops.
</li><li>Strong cross-functional collaboration with hardware teams, software engineering, ML engineering, product, operations, and leadership stakeholders.
</li><li>Excellent judgment in balancing scientific rigor, product urgency, systems constraints, safety, reliability, and customer impact.
</li><li>Clear executive-level communication; able to explain complex robotics and AI tradeoffs to technical and non-technical audiences.
</li></ul><h1 class="jobSectionHeader">Required Technical Expertise
</h1><ul><li>Deep experience in machine learning, artificial intelligence, computer vision, perception, robotics, sensor fusion, real-time signal processing, or a closely related field.
</li><li>Experience with perception capabilities such as object detection, tracking, activity recognition, scene understanding, localization, or state estimation.
</li><li>Experience designing multimodal AI systems that combine heterogeneous data sources and reason over context, actions, and temporal signals.
</li><li>Practical knowledge of reinforcement learning, planning, sequential decision-making, robotics control interfaces, or action-conditioned model behavior.
</li><li>Strong programming capability in applicable languages such as Python and/or C++, and experience with modern ML frameworks and production-oriented software practices.
</li><li>Familiarity with APIs, SDKs, or integration patterns from commercially viable robotics platforms.
</li></ul><h1 class="jobSectionHeader">Minimum Qualifications
</h1><ul><li>15 years of experience in data science, machine learning, artificial intelligence, robotics, computer vision, signal processing, statistical modeling, data mining, or a related field; OR
</li><li>Bachelor's degree in Mathematics, Statistics, Computer Science, Data Science, Physics, Robotics, Electrical Engineering, Mechanical Engineering, or related field and 11 years of relevant experience; OR
</li><li>Master's degree in one of the above or related fields and 9 years of relevant experience; OR
</li><li>Doctorate in one of the above or related fields and 7 years of relevant experience.
</li><li>7+ years of hands-on experience with Python, C++, PyTorch, and ROS for software development, machine learning, and robotics applications.
</li><li>Demonstrated technical leadership guiding teams and stakeholders toward strategic goals.
</li></ul><h1 class="jobSectionHeader">Preferred Qualifications
</h1><ul><li>16 years of experience in data science, machine learning, artificial intelligence, robotics, computer vision, perception, signal processing, or related field; OR equivalent degree-based experience aligned to Oracle IC5 guidelines.
</li><li>2 years of leadership experience with or without direct reports, including technical direction, mentoring, project planning, or cross-functional execution.
</li><li>2 years of experience working with operating budgets and/or project financials, where applicable.
</li><li>5+ years of experience creating technical publications, patents, white papers, peer-reviewed conference or journal articles, or equivalent technical documentation.
</li><li>Demonstrated experience delivering robotics, embodied AI, perception, or multimodal systems from research concept into production or customer-facing environments.
</li><li>Hands-on experience with commercial robot platforms, robot SDKs/APIs, simulation environments, telemetry pipelines, and real-time deployment constraints.
</li></ul><h1 class="jobSectionHeader">Success Profile
</h1><ul><li>Builds credibility as a senior applied science leader who can bridge research depth with pragmatic product delivery.
</li><li>Operates comfortably across sensors, models, APIs, hardware/software boundaries, and executive decision-making forums.
</li><li>Raises the bar for AI adoption in robotics by creating reusable patterns, evaluation standards, and scalable delivery practices.</li></ul></div>

Lead Principal Applied Scientist - Robotics

<div>
 
 Description
 
 
 
 Are you interested in how to build AI reasoning systems that give provably correct answers? Are you excited by science at the interface of classical AI reasoning and Large Language Models (LLMs)? Would you like to apply your technology to serve operations customers better?
 
 
 Amazon Robotics is looking for a talented Applied Scientist. You will innovate on combining language models (LMs) with classical AI reasoning. You will work with a team of scientists and engineers to achieve this. You will publish your results in papers at leading venues in AI. You will be part of a larger team and have the opportunity to work on problems such as: using LMs to generate plans, using AI reasoning to verify plan correctness, learning efficient reasoning strategies, self-improving models. You will work on basic science and on business problems in robotics, automation and fulfillment across our operations.
 
 
 Key job responsibilities
 
 
 
 In This Role You Will
 
 
 
 <ul>
 <li>
 Work closely with other scientists and engineers, and be part of Amazon&rsquo;s diverse global science community.
 </li>
 <li>
 Publish your research in top-tier academic venues and hone your presentation skills.
 </li>
 <li>
 Be inspired by challenges and opportunities to invent new techniques in your area(s) of expertise.
 
 
 </li>
 </ul>
 A day in the life
 
 
 You'll meet regularly with your technical lead and your team on your ideas, get guidance and feedback, work together on architectures and algorithms, author papers, build AI systems, all with the aim of delivering results for your operations customers. You'll work closely with other scientists to review your plans and results. You'll meet with engineers to implement your ideas at scale.
 
 
 
 About The Team
 
 
 
 The Veritas team is a science team working at the boundary between language models and classical AI reasoning. We work across on customer problems in fulfillment, automation and robotics. We focus on high quality research science informed by practical problems.
 
 
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 Experience in building models for business application
 </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>
 Experience implementing algorithms using toolkits and self-developed code
 </li>
 <li>
 Publication record in top tier venues in generative AI reasoning or classical planning
 </li>
 <li>
 PhD in a relevant field (reinforcement learning, neurosymbolic AI, LLMs for formal reasoning)
 </li>
 <li>
 Experience in reinforcement learning or neuro-symbolic AI
 </li>
 <li>
 Practical experience with PyTorch, the HuggingFace ecosystem, SageMaker, and RL tools
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience using Unix/Linux
 </li>
 <li>
 Experience in professional software development
 </li>
 <li>
 Experience using AWS tools and services - including AWS batch, Boto, S3, EC2 etc
 </li>
 <li>
 Strong skills in experimental design/statistical analysis
 </li>
 <li>
 Strong software engineering skills
 
 
 </li>
 </ul>
 Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
 
 
 m/w/d
 
 
 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.
 
 
 
 
 Company
 
 - Amazon Development Center Germany GmbH
 
 
 Job ID: A10376861
</div>

Applied Scientist, Amazon Robotics

Search 1691+ Applied scientist jobs near you this July. New roles added regularly across leading industries. Apply today.

1691 applied scientist jobs Near Me

Applied Scientist

Applied Scientist

Applied Scientist - LLM, Alexa

Applied Scientist, Amazon Transportation

Junior Applied Scientist (all genders)

Lead Principal Applied Scientist - Robotics

Applied Scientist, Amazon Robotics