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ai research scientist - mllm training Jobs in Seattle

ai research scientist - mllm training

applied scientist

applied scientist ii, sponsored products and brands - advertiser guidance Jobs in Seattle

artificial intelligence researcher Jobs in Seattle

artificial intelligence researcher

ai research scientist mllm training

Cerebro

<div>
 <p>
  Are you ready to pioneer the future of AI? We&rsquo;re seeking a
  <strong>
   Research Scientist
  </strong>
  with expertise in training
  <strong>
   Multimodal Large Language Models (MLLMs)
  </strong>
  to join an ambitious, cutting-edge team working at the intersection of
  <strong>
   AI, deep learning, and human expression.
  </strong>
  This role offers a unique opportunity to define the next wave of AI innovation by building the
  <strong>
   first real-time human foundation model
  </strong>
  that integrates text, speech, facial expressions, and body language. If you&rsquo;re passionate about pushing research boundaries while delivering real-world applications, we&rsquo;d love to hear from you.
  <strong>
   About the Role
  </strong>
 </p>
 <p>
  As a Research Scientist, you&rsquo;ll drive the development of advanced systems capable of
  <strong>
   understanding and generating lifelike, human-like responses
  </strong>
  in real-time. This unified model will:
 </p>
 <ul>
  <li>
   <strong>
    Understand fine-grained human signals
   </strong>
   &mdash; from a subtle change in tone to a quirked eyebrow &mdash; and infer meaning in context.
  </li>
  <li>
   <strong>
    Generate lifelike, responsive avatars
   </strong>
   whose gestures, expressions, and tone evolve frame-by-frame to deliver genuine, social, and emotionally intelligent interactions.
  </li>
 </ul>
 <p>
  This is an opportunity to tackle blank-page problems and shape foundational technology in an area where real-time, multimodal interaction is still an
  <strong>
   unsolved frontier.This Role is Perfect for You If You...
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Have a PhD
   </strong>
   (or equivalent experience) in training multimodal large language models, autoregressive architectures, or related fields, with a proven track record of publishing groundbreaking research.
  </li>
  <li>
   <strong>
    Excel at deep learning
   </strong>
   and know how to run the entire ML pipeline &mdash; from data preparation and rapid prototyping to large-scale model training, benchmarking, and evaluation.
  </li>
  <li>
   <strong>
    Thrive in ambiguity
   </strong>
   and enjoy charting your own path to solve complex, unstructured challenges.
  </li>
  <li>
   Are passionate about
   <strong>
    bridging research breakthroughs with real-world applications.
   </strong>
  </li>
  <li>
   Write
   <strong>
    clean, efficient code
   </strong>
   that scales and stands the test of time.
  </li>
  <li>
   Collaborate effectively with a diverse team of brilliant minds from different domains.
  </li>
 </ul>
 <p>
  <strong>
   Why Join Us?
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Shape the future of AI:
   </strong>
   This is a rare opportunity to work on foundational technology that unites text, speech, and vision into a cohesive, real-time system &mdash; tackling problems others haven&rsquo;t solved yet.
  </li>
  <li>
   <strong>
    Be part of a world-class team:
   </strong>
   Work alongside PhDs from top institutions like MIT, UW, and Oxford, with decades of combined experience at leading companies like Apple and Meta.
  </li>
  <li>
   <strong>
    Frontier research meets real-world impact:
   </strong>
   Our team has a proven track record of advancing AI avatars and audio-visual generation, publishing at top conferences, and shipping real-time ML products used by millions.
  </li>
  <li>
   <strong>
    Collaborate in-person:
   </strong>
   Join us at our Seattle HQ, where our team works together 5 days a week to drive innovation forward.
  </li>
 </ul>
 <p>
  <strong>
   Key Details
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Location:
   </strong>
   Seattle, Washington (In-person collaboration, 5 days/week)
  </li>
  <li>
   <strong>
    Funding:
   </strong>
   $10M seed round backed by Accel, South Park Commons, Lightspeed, and top angels from the AI industry.
  </li>
 </ul>
 <p>
  <strong>
   What We&rsquo;re Building
  </strong>
 </p>
 <p>
  We&rsquo;re creating the
  <strong>
   first human foundation model
  </strong>
  that operates across text, speech, facial expression, and body language in real time. The goal? To make AI
  <strong>
   socially and emotionally intelligent,
  </strong>
  able to interpret subtle human signals and respond in a way that feels truly human.The industry has made strides in areas like voice AI and avatar visuals, but existing solutions remain fragmented. This role offers the chance to be a
  <strong>
   trailblazer
  </strong>
  in a field where the boundaries are still being defined.
  <strong>
   How to Apply
  </strong>
 </p>
 <p>
  If this sounds like the challenge you&rsquo;ve been looking for, let&rsquo;s connect! Apply now to join a team that&rsquo;s reshaping the future of AI &mdash; one lifelike interaction at a time.
  <strong>
   Note:
  </strong>
  This posting is intentionally anonymized to respect client confidentiality. We look forward to hearing from innovative thinkers ready to make an impact.
 </p>
 <p>
  Auto
 </p>
 <p>
 </p>
</div>


AI Research Scientist - MLLM Training

Tata Consultancy Services (TCS)

<div></div><div><div><div><div><div><ul><li>5+ years of building models for business application experience</li>
<li>PhD, or Master's degree and 6+ years of CS, CE, ML or related field experience</li>
<li>Experience programming in Java, C++, Python or related language</li>
<li>Practical experience with LLM pre-training or post-training, and experience working with organic, synthetic, agentic, or reasoning data for LLMs</li>
<li>Published research in top conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL) and/or demonstrated significant industry influence in the field of AI</li>
<li>Experience using Unix/Linux</li>
<li>Experience in professional software development</li>
<li>Experience working on SOTA LLMs.</li>
<li>Multiple first-author LLM-related publications in top-tier conferences (e.g., NeurIPS, ICLR, ACL, EMNLP, NAACL)</li>
</ul></div><div>Preferred qualifications:
</div><div><div><ul><li>5+ years of experience building and deploying machine learning models or developing algorithms for business applications.</li>
<li>A strong track record of publications at top-tier, peer-reviewed conferences or journals (e.g., NeurIPS, ICML, ACL, KDD, CVPR).</li>
<li>Proven ability to transition research to production-grade, scalable systems.</li>
<li>Experience with Generative AI tools, Large Language Models (LLMs), Transformers, Reinforcement Learning, or advanced Computer Vision/NLP techniques.</li>
<li>Expertise in Python, Java, or C++, as well as experience with distributed machine learning frameworks (e.g., Spark, Hadoop</li>
</ul></div></div><div><div><b>TCS Employee Benefits Summary:</b>
</div><div><ul><li>Discretionary Annual Incentive.</li>
<li>Comprehensive Medical Coverage: Medical &amp; Health, Dental &amp; Vision, Disability Planning &amp; Insurance, Pet Insurance Plans.</li>
<li>Family Support: Maternal &amp; Parental Leaves.</li>
<li>Insurance Options: Auto &amp; Home Insurance, Identity Theft Protection.</li>
<li>Convenience &amp; Professional Growth: Commuter Benefits &amp; Certification &amp; Training Reimbursement.</li>
<li>Time Off: Vacation, Time Off, Sick Leave &amp; Holidays.</li>
<li>Legal &amp; Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.</li>
</ul></div><div>#LI-RJ2
</div><div>Salary Range-$120,000-$150,000 a year
</div></div></div></div></div><div><div><div><b>Location</b></div>
<div>Seattle, WA</div>
</div><div><div><b>Job Function</b></div>
<div>TECHNOLOGY</div>
</div><div><div><b>Role</b></div>
<div>Scientist</div>
</div><div><div><b>Job Id</b></div>
<div>401448</div>
</div><div><div><b>Desired Skills</b></div>
<div>Python</div>
</div><div><div><b>Salary Range</b></div>
<div>$120,000-$150,000 a year</div></div></div></div><div></div>

Applied scientist

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
We are looking for a passionate Applied Scientist to help pioneer the next generation of agentic AI applications for Amazon advertisers. In this role, you will design agentic architectures, develop tools and datasets, and contribute to building systems that can reason, plan, and act autonomously across complex advertiser workflows. You will work at the forefront of applied AI, developing methods for fine-tuning, reinforcement learning, and preference optimization, while helping create evaluation frameworks that ensure safety, reliability, and trust at scale.
<br>
<br>
You will work backwards from the needs of advertisers&mdash;delivering customer-facing products that directly help them create, optimize, and grow their campaigns. Beyond building models, you will advance the agent ecosystem by experimenting with and applying core primitives such as tool orchestration, multi-step reasoning, and adaptive preference-driven behavior. This role requires working independently on ambiguous technical problems, collaborating closely with scientists, engineers, and product managers to bring innovative solutions into production.<br>
<br>
Key job responsibilities<br>
<ul><li>Design and build agents to guide advertisers in conversational and non-conversational experience.</li><li>Design and implement advanced model and agent optimization techniques, including supervised fine-tuning, instruction tuning and preference optimization (e.g., DPO/IPO).</li><li>Curate datasets and tools for MCP.
</li><li>Build evaluation pipelines for agent workflows, including automated benchmarks, multi-step reasoning tests, and safety guardrails.</li><li>Develop agentic architectures (e.g., CoT, ToT, ReAct) that integrate planning, tool use, and long-horizon reasoning.</li><li>Prototype and iterate on multi-agent orchestration frameworks and workflows.</li><li>Collaborate with peers across engineering and product to bring scientific innovations into production.</li><li>Stay current with the latest research in LLMs, RL, and agent-based AI, and translate findings into practical applications.</li></ul><br>
About the team<br>
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights.<br>
<br>
We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.<br>
<br>
The Campaign Strategies team within Sponsored Products and Brands is focused on guiding and supporting 1.6MM advertisers to meet their advertising needs of creating and managing ad campaigns. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in guidance systems can have outsized impact on advertiser success and Amazon&rsquo;s retail ecosystem.<br>
<br>
Our vision is to build a highly personalized, context-aware agentic advertiser guidance system that leverages LLMs together with tools such as auction simulations, ML models, and optimization algorithms. This agentic framework, will operate across both chat and non-chat experiences in the ad console, scaling to natural language queries as well as proactively delivering guidance based on deep understanding of the advertiser. To execute this vision, we collaborate closely with stakeholders across Ad Console, Sales, and Marketing to identify opportunities&mdash;from high-level product guidance down to granular keyword recommendations&mdash;and deliver them through a tailored, personalized experience. Our work is grounded in state-of-the-art agent architectures, tool integration, reasoning frameworks, and model customization approaches (including tuning, MCP, and preference optimization), ensuring our systems are both scalable and adaptive.</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>3+ years of building models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience in designing experiments and statistical analysis of results</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience in professional software development</li><li>Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.<p><br>
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.</p><br>
USA, NY, New York - 172,400.00 - 223,400.00 USD annually<br>
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually</div><p></p>

Applied Scientist II, Sponsored Products and Brands - Advertiser Guidance

<div>
 <p>
  Are you passionate about advancing the frontier of AI? Do you thrive at the intersection of cutting-edge research and real-world impact? A fast-growing AI startup is looking for exceptional AI researchers and engineers with expertise in
  <strong>
   multimodal models
  </strong>
  to join their world-class team in
  <strong>
   Seattle, WA
  </strong>
  .
 </p>
 <p>
  <strong>
   About Us
  </strong>
 </p>
 <p>
  We are a well-funded startup backed by top-tier investors, with a mission to bring real-time AI avatars to life. Our team includes experts with advanced degrees from leading institutions and extensive experience at top tech companies. With significant funding and a clear vision, we are scaling rapidly and looking for top talent to help operationalize cutting-edge research into transformative products.
 </p>
 <p>
  <strong>
   What You&rsquo;ll Do
  </strong>
 </p>
 <p>
  As an
  <strong>
   AI Research Engineer
  </strong>
  , you&rsquo;ll play a pivotal role in bridging the gap between research and production. Your responsibilities will include:
 </p>
 <ul>
  <li>
   <strong>
    Operationalizing Research
   </strong>
   : Collaborate with researchers to transition models from experimental checkpoints to production-ready systems. Establish scalable patterns for large-scale training, rapid experimentation, and deployment of new architectures.
  </li>
  <li>
   <strong>
    Optimizing Model Performance
   </strong>
   : Profile and enhance model inference for latency and throughput using techniques like quantization, pruning, distillation, and architectural refinements to ensure cost-effective scalability.
  </li>
  <li>
   <strong>
    Model Acceleration
   </strong>
   : Apply optimization techniques (e.g., TensorRT, ONNX, vLLM) to accelerate multimodal models, including video diffusion, large language models (LLMs), and speech models.
  </li>
  <li>
   <strong>
    Designing Data Pipelines
   </strong>
   : Build efficient pipelines for video data ingestion, preprocessing, and training at
   <strong>
    petabyte scale
   </strong>
   using tools like Dagster and Ray.
  </li>
  <li>
   <strong>
    Evaluating and Iterating
   </strong>
   : Develop evaluation frameworks to measure model quality, establish benchmarks, and guide continuous improvement of model capabilities.
  </li>
 </ul>
 <p>
  <strong>
   What We&rsquo;re Looking For
  </strong>
 </p>
 <p>
  We&rsquo;re seeking candidates with a strong foundation in AI research and production engineering. The ideal candidate will have:
 </p>
 <ul>
  <li>
   <strong>
    Production ML Experience
   </strong>
   : Proven track record of deploying ML models to production, with a deep understanding of common failure modes (e.g., resource contention, OOMs, batch optimization) and how to address them.
  </li>
  <li>
   <strong>
    Deep Learning Expertise
   </strong>
   : Strong knowledge of PyTorch and modern ML architectures, with experience training and optimizing large models (e.g., transformers, diffusion models).
  </li>
  <li>
   <strong>
    Systems Proficiency
   </strong>
   : Comfort working with GPUs, debugging CUDA issues, and profiling model workloads to identify compute or memory bottlenecks.
  </li>
  <li>
   <strong>
    Data Engineering Skills
   </strong>
   : Experience building scalable data pipelines for high-bandwidth media processing and training workflows.
  </li>
 </ul>
 <p>
  <strong>
   Preferred Qualifications
  </strong>
 </p>
 <ul>
  <li>
   Experience with
   <strong>
    video or audio models
   </strong>
   in research or production settings.
  </li>
  <li>
   Familiarity with
   <strong>
    low-level optimization
   </strong>
   (e.g., CUDA kernels, Triton, custom operators).
  </li>
  <li>
   Knowledge of
   <strong>
    real-time ML systems
   </strong>
   and latency-critical inference.
  </li>
  <li>
   Prior work with
   <strong>
    model compression techniques
   </strong>
   (quantization, distillation, pruning).
  </li>
 </ul>
 <p>
  <strong>
   Why Join Us?
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Impactful Work
   </strong>
   : Your contributions will directly shape the future of real-time AI avatars, advancing cutting-edge research into products that touch millions of lives.
  </li>
  <li>
   <strong>
    World-Class Team
   </strong>
   : Collaborate with some of the brightest minds in AI, including researchers and engineers from top institutions and companies.
  </li>
  <li>
   <strong>
    Growth Opportunities
   </strong>
   : Be part of a fast-growing startup with significant funding and a clear vision for the future.
  </li>
  <li>
   <strong>
    In-Person Collaboration
   </strong>
   : Work alongside your teammates in our vibrant
   <strong>
    Seattle HQ
   </strong>
   , fostering creativity and innovation through daily collaboration.
  </li>
 </ul>
 <p>
  <strong>
   How to Apply
  </strong>
 </p>
 <p>
  If you&rsquo;re excited about the opportunity to work on
  <strong>
   multimodal AI models
  </strong>
  and help bring groundbreaking research to life, we&rsquo;d love to hear from you! Apply now to join a team shaping the future of AI.
 </p>
</div>


Artificial Intelligence Researcher

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-the-art generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights.
<br>
<br>
We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.<br>
<br>
<br>
<br>
Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we&rsquo;re helping businesses grow on Amazon.com and beyond!<br>
<br>
Key job responsibilities<br>
This role will redesign how ads create personalized, relevant shopping experiences with customer value at the forefront. Key responsibilities include:<br>
<br>
<ul><li>Design and develop solutions using GenAI, deep learning, multi-objective optimization and/or reinforcement learning to transform ad retrieval, auctions, whole-page relevance, and shopping experiences.</li><li>Partner with scientists, engineers, and product managers to build scalable, production-ready science solutions.</li><li>Apply industry advances in GenAI, Large Language Models (LLMs), and related fields to create innovative prototypes and concepts.</li><li>Improve the team's scientific and technical capabilities by implementing algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling.</li><li>Mentor junior scientists and engineers to build a high-performing, collaborative team.</li></ul><br>
A day in the life<br>
As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced&mdash;elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon&rsquo;s rich data and the world&rsquo;s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science.<br>
<br>
About the team<br>
The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon&mdash;such as product detail pages, the homepage, and store-in-store pages&mdash;to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack&mdash;from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences&mdash;all designed to deliver meaningful value.</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 Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience in machine learning, data mining, information retrieval, statistics or natural language processing</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Demonstrated expertise in Generative AI technologies, including foundation models, LLMs, and model customization for specific business applications</li><li>Hands-on experience building ads ranking, retrieval, recommendation, or personalization systems that operate at web scale</li><li>Technical proficiency in advanced AI approaches such as multi-modal modeling, few-shot learning, retrieval-augmented generation (RAG), or reinforcement learning from human feedback (RLHF)</li><li>Track record of designing and implementing online experimentation frameworks, including A/B testing methodologies and performance metrics for advertising or e-commerce</li><li>Proven ability to translate complex technical concepts into clear explanations for diverse audiences, from engineers to executives</li><li>Deep knowledge of computational advertising fundamentals, including auction mechanisms, advertising economics, and advertiser success metrics</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.<p><br>
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.</p><br>
USA, CA, Palo Alto - 192,200.00 - 260,000.00 USD annually<br>
USA, NY, New York - 183,800.00 - 248,700.00 USD annually<br>
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div><p></p>

Senior Applied Scientist, Off-Search, Sponsored Products and Brands

Data Scientist, Product Analytics

Apple

<p>Join Apple Maps, where our mission is to build the best map in the world. As a Senior Data Scientist in the Maps Evaluation organization, you will be instrumental in harnessing the power of user data to strategically inform and influence critical decisions across the Maps organization. We work in a highly collaborative, fast-paced environment where you&rsquo;ll have significant autonomy to define and lead impactful projects, drive substantial change, and contribute your unique perspective to a team committed to creating something truly wonderful.<br>
<br>
<b>Description</b><br>
<br>
We are seeking a highly talented and seasoned Data Scientist to join our cross-functional team, dedicated to proactively identifying opportunities and optimizing user engagement, retention, and growth within Apple Maps. You will partner closely with Product and Program teams, acting as a strategic thought leader to leverage data and inform product direction. This role offers unparalleled scope to architect, define, and build the next generation of metrics and analytical frameworks. We're looking for a creative problem-solver who can innovate within our robust privacy commitments, evolving our current metrics foundation into a comprehensive, cutting-edge insights platform. Your day-to-day responsibilities will span the full data lifecycle, from proactive exploratory data analysis and metrics design to leading deep dives and crafting and presenting executive-level strategic reports.&quot;,&quot;responsibilities&quot;:&quot;Lead the design, creation, and validation of novel metrics for user engagement, retention, and growth.<br>
<br>
Drive the development and implementation of sophisticated data products (e.g., user segmentation models, churn propensity scores, growth forecasting tools).<br>
<br>
Proactively lead deep-dive analyses to uncover insights into user behavior and inform critical business decisions.<br>
<br>
Engage with and influence partners and executive leadership to shape product strategy and roadmap with compelling, data-driven recommendations.<br>
<br>
Architect solutions to highly ambiguous product goals and complex business problems, transforming them into well-defined and solvable data science challenges.<br>
<br>
Drive the development, adoption, and best practices for advanced tools and automated data pipelines (primarily using Python and SQL-based ETL frameworks) to ensure efficiency and scalability.<br>
<br>
Mentor and guide junior data scientists, fostering their technical and analytical growth.<br>
<br>
Champion new ideas and analytical approaches, pushing the team towards innovative solutions and methodologies.<br>
<br>
<b>Preferred Qualifications</b><br>
<br>
Deep expertise in user engagement analytics, retention strategies, and/or growth modeling.<br>
<br>
Extensive experience with large data sets using technologies like Hadoop and Spark.<br>
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Demonstrated experience in architecting and implementing automated analytics tasks and data pipelines at scale.<br>
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Proven track record of leading complex projects within highly cross-functional teams, driving consensus and delivering results.<br>
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Experience mentoring junior team members and contributing to a data science community.<br>
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Experience contributing to product strategy and roadmap definition.<br>
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<b>Minimum Qualifications</b><br>
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MS/PhD in Computer Science, Statistics, Data Science, Physics, Operations Research, or similar quantitative domain.<br>
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5+ years of industry experience with data analysis at web scale or relevant work experience, demonstrating increasing levels of responsibility and impact.<br>
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Expert proficiency in Python for data manipulation, analysis, and modeling.<br>
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Expert proficiency in at least one database language (e.g., SQL, Snowflake) for complex data extraction and transformation.<br>
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Proven ability to translate highly ambiguous business questions and strategic needs into robust technical requirements and analytical solutions.<br>
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Deep understanding and practical application of advanced statistical techniques and modeling, including predictive modeling and causal inference.<br>
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Exceptional communication and presentation skills, with a track record of influencing product and executive leadership.<br>
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Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .<br>
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<b>Pay &amp; Benefits</b><br>
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At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $163,300 and $290,100, and your base pay will depend on your skills, qualifications, experience, and location.<br>
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Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.<br>
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Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.</p>

Senior Data Scientist - Maps Eval

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