applied ai engineer ii

data engineer ii

aerospace quality engineer Jobs in Redmond

aerospace quality engineer

agentic ai developer

ai software engineer ii

senior ai machine learning engineer minecraft

Microsoft

<div>
 <strong>
  Overview
  <br/>
  <br/>
 </strong>
 At Mojang Studios, the creators of Minecraft, we are on a mission to build a better world through the power of play.
 <br/>
 <br/>
 Why play? Well, play is at the heart of everything we do. It&rsquo;s the blocky backbone of our games, the core of our development philosophy, and even the origin of our name. From the relentless experimentation of our endlessly inspiring community to the classrooms where Minecraft has become an essential teaching tool, play is the bedrock of our existence.
 <br/>
 <br/>
 We enable millions to create and play together, connect people across the globe, and foster a community that is among the most active and passionate in the world. Our community is global and incredibly diverse. When we are developing anything within our franchise, we keep this in mind. We want everyone to not only feel included in Minecraft, but also to see themselves in what we make. Our goal is for the Mojang Studios team to be as diverse as our community.
 <br/>
 <br/>
 The Senior AI/Machine Learning Engineer at Mojang Studios will support the strategy, development, and execution of AI products that will unlock increased productivity and advanced capabilities inside and outside of the game. This role will apply expertise in AI &amp; ML algorithms, frameworks, and architectures as well as data and cloud infrastructure knowledge to guide and build solutions for a variety of teams and data modalities across the studio. This is a critical role to executing our AI strategies across workflows, internal tools, and player experiences
 <br/>
 <br/>
 Microsoft&rsquo;s mission is to empower every person and every organization on the planet to achieve more. As employees, we come together with a growth mindset, innovate to empower others and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond
 <br/>
 <br/>
 In the end, it&rsquo;s the people of Mojang Studios that make this place truly special. When you join, you&rsquo;ll find yourself in the company of incredibly bright, warm, and creative individuals &ndash; all united and working toward a single goal. Come help us reach it!
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, build, and productionize AI (Artificial Intelligence)/GenAI (Generative Artificial Intelligence) services and platform components for internal and player‑facing experiences across Minecraft and other titles.
  </li>
  <li>
   Create reusable AI building blocks and reference integrations to accelerate teams and drive studio‑wide AI enablement.
  </li>
  <li>
   Own cloud infrastructure &amp; MLOps (Machine Learning Operations): data pipelines, training/evaluation, deployment, monitoring, and operational support.
  </li>
  <li>
   Improve reliability, performance, and cost with guardrails, fallback paths, SLOs (Service Level Objectives), and actionable runbooks.
  </li>
  <li>
   Engineer for security, privacy, and compliance through secure data access patterns and threat modeling.
  </li>
  <li>
   Embed responsible AI principles (fairness, transparency, player safety) into system design and operations.
  </li>
  <li>
   Collaborate cross‑discipline to solve product problems and deliver measurable business/player impact; participate in design/code reviews and pair programming.
  </li>
  <li>
   Document and communicate: share learnings to upskill the studio and present findings/opportunities to leadership.
  </li>
  <li>
   Embody our Culture &amp; Values
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <strong>
  Required Qualifications:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  </li>
  <ul>
   <li>
    OR equivalent experience.
    <br/>
   </li>
  </ul>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience in AI/ML (Machine Learning) principles, frameworks, and tools (e.g., PyTorch, Generative AI, RAG (Retrieval-Augmented Generation), with experience in big data technologies like Spark (PySpark) and Databricks.
  </li>
  <li>
   Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  </li>
  <ul>
   <li>
    OR equivalent experience.
   </li>
  </ul>
  <li>
   Games industry knowledge
  </li>
  <li>
   Skilled in Python (C#/TypeScript a plus), modern dev practices (Agile, GitHub, Azure DevOps), and designing, deploying, and monitoring cloud infrastructure for AI systems.
  </li>
  <li>
   Familiar with multiple data modalities and ML domains: computer vision, audio, predictive modeling, NLP (Natural Language Processing), time series forecasting, graph networks, deep learning, and reinforcement learning.
  </li>
  <li>
   Verbal and written communication skills.
  </li>
  <li>
   Ability to translate complex technical concepts into clear, actionable insights for non-technical stakeholders.
   <br/>
  </li>
 </ul>
 Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.
 <br/>
 <br/>
 Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
 <br/>
 <br/>
 https://careers.microsoft.com/us/en/us-corporate-pay
 <br/>
 <br/>
 This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
 <br/>
 <br/>
 Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about
 <strong>
  requesting accommodations.
 </strong>
</div>


Senior AI/Machine Learning Engineer, Minecraft

<div><b>Overview</b><p><br>
Are you an engineer who loves pairing strong product instincts with AI, machine learning, and bringing meaningful UX interactions to life with craft and precision? This role works in a people-centric, culture-first environment alongside designers, product partners, engineers, strategists, and writers to design and build modern experiences that make intelligent systems feel clear, trustworthy, and human.</p><p>
We&rsquo;re a forward-looking team passionate about building innovative technology and shipping delightful experiences&mdash;especially where AI changes what products can do. We invest in rapid prototyping, model tuning and evaluation, data experiments, and AI-related explorations to help explore the future of intelligent Microsoft products. Our team brings diverse backgrounds in multiple disciplines, from engineering, design, or research to behavioral sciences or medicine; we come in all shapes and sizes. We love pushing boundaries and helping evolve Microsoft&rsquo;s products. Our current focus is on Copilot in the M365 Enterprise world.</p><p>
We're looking for a Senior UX Data Engineer who is self-driven, focused on machine learning, and cares about bringing thoughtful product design to life. You can turn ideas into interactive experiences, learn new tools quickly, and are comfortable exploring the unknown. You value strong engineering practices and know how to collaborate across design and product.</p><p>
You contribute openly, prototype or experiment to learn, share feedback generously, and help raise the quality of the team&rsquo;s work. You are curious, adaptable, and motivated to build experiences that make a real impact.</p><p>
If you&rsquo;re looking for a change and wanting to make an impact &ndash; we invite you to join us in our mission and vision to build the future of UX for Microsoft.</p><p></p><b><br>
Responsibilities</b><br>
<p></p><ul><li>
Design and run applied science and/or machine learning experiments to explore new ideas and validate hypotheses</li><li>
Conduct research on state-of-the-art technologies, methodologies, and emerging trends</li><li>
Translate concepts into working prototypes through code</li><li>
Provide thoughtful, constructive feedback and propose creative, practical solutions</li><li>
Communicate insights, decisions, and results clearly and concisely to cross-functional partners</li><li>
Contribute to publications, technical reports, and knowledge-sharing initiatives</li></ul><br>
<b>
Qualifications</b><br>
<h2 class="jobSectionHeader"><b>
Required Qualifications:</b></h2><ul><li>
Master's Degree in Computer Science, Software Engineering, Graphic Design, Product Design, Visual Design, Human Computer Interaction, or related field AND 3+ years experience working in product or service design and/or shipping production code
<ul><li>OR Bachelor's Degree in Computer Science, Software Engineering, Graphic Design, Product Design, Visual Design, Human Computer Interaction, or related field AND 4+ years experience working in product or service design and/or shipping production code
</li><li>OR equivalent experience.</li></ul></li></ul><p><b>
Other Requirements:</b></p><ul><li>
GitHub, CodePen, or other links showcasing coding skills OR portfolio is required with application submission.</li></ul><h2 class="jobSectionHeader"><b>
Preferred Qualifications:</b></h2><ul><li>
Python coding skills and experience with ML frameworks such as PyTorch or TensorFlow</li><li>
Experience working with LLMs, including prompt design, tool and function calling, retrieval strategies (RAG), and multi-step agent orchestration</li><li>
Experience building machine learning pipelines for model quality, optimizations, evaluations, integrations, or UX outcomes (e.g., rubric-based human evals, offline test sets, experiment design, and/or A/B testing), and using results to iterate on both UX and implementation</li><li>
Ability to build and iterate on ML pipelines, integrating insights back into product and experience design</li><li>
Proficiency in data analysis and experimentation to inform product decisions</li><li>
Foundations in linear algebra, calculus, and probability and statistics</li><li>
Familiarity with MLOps and experiment tracking tools like MLflow, Kubeflow, Weights and Biases or equivalent</li><li>
Understanding of production ML requirements, with a track record of mitigating risk and downstream impact</li><li>
Experience with cloud AI and ML services</li><li>
Interest in human-computer interaction, behavioral psychology, and trust in intelligent systems</li><li>
Mastery of at least one back-end coding language</li><li>
Experience building ML-powered product experiences</li></ul><br>
<p></p>
<br>
<br>
<p>UX Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.
</p><p></p><p>Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:<br>
https://careers.microsoft.com/us/en/us-corporate-pay</p><p><br>
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.</p><p></p><p><br>
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process<b>.</b></p></div>

Senior UX Data Engineer

<div><b>Overview</b><div></div><div><div><p><br>
As a <b>Senior Research Engineer</b> at Microsoft, you will advance Microsoft&rsquo;s mission to empower every person and every organization to achieve more. You will help build and integrate cutting-edge AI into Microsoft products and services within <b>Experience + Devices</b> (E+D) org, ensuring solutions are inclusive, ethical, and impactful. This role blends applied research, machine learning engineering, and product innovation. You will lead efforts to ship reliable, production-grade AI systems across the stack, from model development and fine-tuning to performance optimization and deployment.</p></div><div><p>
We are in an era of unprecedented AI innovation. As Microsoft leads the way in foundation models, multimodal systems, and AI agents, our goal is to build an open architecture platform where users can interact with tailored AI agents that drive tangible, real-world outcomes. As a Senior Research Engineer, you will:</p></div><div><ul><li><p>
Bridge the gap between state-of-the-art research and customer-facing features</p></li></ul></div><div><ul><li><p>
Drive systems-level innovation across models, infrastructure, and deployment</p></li></ul></div><div><ul><li><p>
Champion responsible AI by embedding fairness, safety, privacy, and performance from the ground up</p></li></ul></div></div><b><br>
Responsibilities</b><div><div><p><b><br>
Bringing State-of-the-Art Research to Products</b></p></div><div><ul><li><p>
Design and implement AI systems using foundation models, prompt engineering, retrieval-augmented generation, multi-agent architectures, and classic ML</p></li></ul></div><div><ul><li><p>
Fine-tune large language models on domain-specific data and evaluate via offline and online methods such as A/B testing, telemetry, and shadow deployments</p></li></ul></div><div><ul><li><p>
Build and harden prototypes into production-ready services using robust software engineering and MLOps practices</p></li></ul></div><div><ul><li><p>
Drive original research and thought leadership (whitepapers, internal notes, patents); convert insights into shipped capabilities</p></li></ul></div><div><ul><li><p>
Research Translation: Continuously review emerging work; identify high-potential methods and adapt them to Microsoft problem spaces</p></li></ul></div><div><p><b>
End-to-End System Development</b></p></div><div><ul><li><p>
ML Design &amp; Architecture: Own end-to-end pipeline from data prep, training, evaluation, deployment, and feedback loops</p></li></ul></div><div><ul><li><p>
Identify and resolve model quality gaps, latency issues, and scale bottlenecks using PyTorch, or TensorFlow</p></li></ul></div><div><ul><li><p>
Operate CI/CD and MLOps workflows including model versioning, retraining, evaluation, and monitoring</p></li></ul></div><div><ul><li><p>
Integrate AI components into Microsoft products in close partnership with engineering and product teams</p></li></ul></div></div><div><div><p><b>
Data-Driven Innovation</b></p></div><div><ul><li><p>
Evaluation &amp; Instrumentation: Build robust offline/online evals, experimentation frameworks, and telemetry for model/system performance.</p></li></ul></div><div><ul><li><p>
Learning Loop Creation: Operationalize continuous learning from user feedback and system signals; close the loop from experimentation to deployment.</p></li></ul></div><div><ul><li><p>
Experimentation &amp; E2E Validation: Design controlled experiments, analyze results, and drive product/model decisions with data.</p></li></ul></div><div><ul><li><p>
Develop proofs of concept that validate ideas quickly at realistic scales</p></li></ul></div><div><ul><li><p>
Curate high-signal datasets, including synthetic and red-team corpora, and establish labeling protocols and data quality checks tied to evaluation KPIs</p></li></ul></div><div><p><b>
Cross-Functional Collaboration</b></p></div><div><ul><li><p>
Partner with software engineers, scientists, designers, and product managers to deliver high-impact AI features</p></li></ul></div><div><ul><li><p>
Translate research breakthroughs into scalable applications aligned with product priorities</p></li></ul></div><div><ul><li><p>
Communicate findings and decisions through internal forums, demos, and documentation</p></li></ul></div><div><p><b>
Responsible AI &amp; Ethics</b></p></div><div><ul><li><p>
Identify and mitigate risks related to fairness, privacy, safety, security, hallucination, and data leakage</p></li></ul></div><div><ul><li><p>
Uphold Microsoft&rsquo;s Responsible AI principles throughout the lifecycle</p></li></ul></div><div><ul><li><p>
Contribute to internal policies, auditing practices, and tools for responsible AI</p></li></ul></div><div><p><b>
Operating Altitudes</b></p></div><div><ul><li><p>
Paper level (ideas and math): Read, critique, and adapt the latest research; identify gaps; design methods with clear trade-offs and guarantees; communicate complex ideas clearly.<br>
Example: &ldquo;This objective is brittle under our data regime. Here is a tighter analysis and a revised loss we can test this sprint.&rdquo;</p></li></ul></div><div><ul><li><p>
Code level (implementation): Turn ideas into robust, tested, maintainable modules; integrate with CI/CD; profile and optimize for latency and throughput.<br>
Example: &ldquo;Refactored the prototype into a reusable PyTorch component, added unit tests and benchmarks, and cut P95 inference latency by 30%.&rdquo;</p></li></ul></div><div><p><b>
Specialty Technical Areas</b></p></div><div><ul><li><p>
Large-scale training and fine-tuning of LLMs, vision-language, or multimodal models</p></li></ul></div><div><ul><li><p>
Multi-agent systems, dialogue agents, and copilots</p></li></ul></div></div><div><div><ul><li><p>
Optimization of inference speed, accuracy, reliability, and cost in production</p></li></ul></div><div><ul><li><p>
Retrieval systems and hybrid architectures using RAG and vector databases</p></li></ul></div><div><ul><li><p>
ML for real-world data constraints such as missing data, noisy labels, and class imbalance</p></li></ul></div></div><b><br>
Qualifications</b><div><p><b><br>
Required Qualifications</b></p></div><div><ul><li><p>
Bachelor&rsquo;s degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field and 4 or more years in applied ML or AI research and product engineering,</p><ul><li>
OR Master&rsquo;s degree and 3 or more years in applied ML or AI research and product engineering,</li><li>
OR PhD in a relevant field and 2 or more years with generative AI, LLMs, or related ML algorithms</li></ul></li></ul></div><div><p><b>
Other Requirements</b></p></div><div><p>
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:</p><ul><li><b>
Microsoft Cloud Background Check:</b> This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.</li></ul></div><div><p><b>
Preferred Qualifications</b></p></div><div><ul><li><p>
PhD in AI/ML or related field with top-venue publications and/or patents</p></li></ul></div><div><ul><li><p>
Experience with Microsoft&rsquo;s LLMOps stack: Azure AI Foundry, Azure Machine Learning, Semantic Kernel, Azure OpenAI Service, and Azure AI Search for vector/RAG</p></li></ul></div><div><ul><li><p>
Familiarity with responsible AI evaluation frameworks and bias mitigation methods</p></li></ul></div><div><ul><li><p>
Experience across the product lifecycle from ideation to shipping</p></li><li><p>
Proficiency in Python and at least one deep learning framework such as PyTorch, JAX, or TensorFlow</p></li><li><p>
Experience deploying Fine Tuned LLMs or multimodal models in live production environments</p></li><li><p>
Experience shipping and maintaining production AI systems</p></li></ul><div>
#CXAJOBS</div><div>
#BICJOBS</div></div><br>
<br>
<br>
<p>Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.
</p><p></p><p>Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:<br>
https://careers.microsoft.com/us/en/us-corporate-pay</p><p><br>
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.</p><p></p><p><br>
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process<b>.</b></p></div>

Senior Research Engineer

Software Engineer, Machine Learning

NVIDIA

<div><div>We are now looking for a Senior Deep Learning Engineer! At NVIDIA, we are at the forefront of advancing the capabilities of artificial intelligence. We are seeking an ambitious and forward-thinking senior deep learning engineer to contribute to the development of next-generation inference optimizations targeting frontier workloads including multi-agent AI systems, generative multimodal models, and inference-time compute scaling. In this role, you will characterize these emerging workloads and develop novel methods to optimize for them across inferencing engines, systems, and hardware architectures. Your work will span multiple tiers of the inference stack from the algorithmic to system level.</div><div></div><div>
As NVIDIA makes significant strides in AI datacenters, our team holds a central role in maximizing the efficiency of our exponentially growing inference deployment needs and establishing a data-driven approach to algorithmic improvements, hardware design and system software development. We collaborate extensively with diverse teams at NVIDIA, spanning deep learning research and framework development teams, to silicon architecture. Thriving in such a high-impact, interdisciplinary environment necessitates not only technical proficiency but also a growth mindset and a pragmatic attitude &mdash; qualities that fuel our collective success in shaping the future of datacenter technology.</div><div></div><div>
What You'll Be Doing:</div><ul><li><div>
Continuously keeping up to date on the latest advancements in generative AI research.</div></li><li><div>
Analyzing and prototyping emerging workloads in multi-agent AI systems, generative multimodal models, and inference-time compute scaling.</div></li><li><div>
Pioneering and developing optimizations for these workloads across the inference stack to push the boundaries of inferencing quality and speed on NVIDIA systems.</div></li><li><div>
Collaborating closely with production teams to incorporate the latest advancements into cutting-edge software frameworks.</div></li></ul><div><br>
What We Need to See:</div><ul><li><div>
Master's degree (or equivalent experience) in Computer Science, Artificial Intelligence, Applied Mathematics, or related fields.</div></li><li><div>
A strong foundation in deep learning, with a particular emphasis on generative models and inferencing.</div></li><li><div>
A track record of at least 5 years of relevant software development experience in modern deep learning frameworks such as PyTorch.</div></li><li><div>
Growth mindset and pragmatic attitude.</div></li></ul><div></div><div>
Ways to Stand Out From the Crowd:</div><ul><li><div>
Published research or noteworthy contributions to the field of deep learning, particularly in areas such as inference-time compute, multimodal generation, AI systems, etc.</div></li><li><div>
Experience with prototyping or deployment of agentic AI systems and/or multimodal generation models.</div></li><li><div>
Experience with collaborating across algorithms, software and performance teams to deliver high quality solutions.</div></li><li><div>
Familiarity with computer architecture and how it relates to AI algorithms development.</div></li></ul><div><br>
NVIDIA is widely considered to be one of the technology world&rsquo;s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you!</div><div></div>
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.<div></div><div><div><div><div><div><div><div><div>
You will also be eligible for equity and <div>benefits</div>.</div></div></div></div></div></div></div></div><div></div>
Applications for this job will be accepted at least until March 6, 2026.<div></div><div>
This posting is for an existing vacancy.</div><div>
NVIDIA uses AI tools in its recruiting processes.</div><div></div>
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.</div><div></div>

Senior Deep Learning Engineer

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Amazon LEO is an initiative to increase global broadband access through a constellation of 3,236 satellites in low Earth orbit (LEO). Its mission is to bring fast, affordable broadband to unserved and underserved communities around the world. Amazon LEO will help close the digital divide by delivering fast, affordable broadband to a wide range of customers, including consumers, businesses, government agencies, and other organizations operating in places without reliable connectivity.<br>
<br>
We are seeking an exceptional Senior Software Engineer to lead our team in building the operational backbone of a revolutionary laser communication network connecting satellites in space and ground stations on Earth. This is a high-impact leadership role where you'll drive multiple concurrent projects that directly enable network operations at unprecedented scale.<br>
<br>
The Opportunity<br>
You'll architect and deliver mission-critical tools and services that power network operations for our dynamic space-based laser link infrastructure. Working in an environment where ambiguity meets innovation, you'll transform complex, evolving requirements into elegant, scalable solutions while mentoring and leading a team of engineers to execute your vision.<br>
<br>
What You'll Build<br>
Design and develop sophisticated multi-layered services that collect real-time telemetry from our satellite constellation, analyze network topology, and intelligently correlate data to identify and resolve faults. Your systems will automatically trigger remediation runbooks, escalate issues to appropriate teams, and leverage machine learning and generative AI to detect anomalies, perform root cause analysis, and predict customer impact before it occurs.<br>
<br>
What We're Looking For<br>
You bring proven experience architecting and delivering complex, distributed systems in production environments. As a full-stack engineer, you possess both the technical depth to build clean, maintainable back-end services and the product sensibility to create intuitive, actionable visualizations that operators can trust and understand at a glance. Your meticulous attention to detail manifests in every layer of the stack&mdash;from elegant API design and robust data pipelines to thoughtful UI/UX that transforms complex telemetry into clear operational insights.<br>
<br>
You excel at breaking down ambitious technical roadmaps into actionable milestones and have a track record of successfully onboarding and elevating junior engineers. Deep expertise in distributed cloud services and infrastructure-as-code principles is essential, as is the ability to thrive in high-ownership, high-accountability environments where your decisions directly impact mission success.<br>
<br>
Why This Role Matters<br>
Your work will be the operational nervous system of our space network&mdash;enabling seamless connectivity, ensuring reliability, and pushing the boundaries of what's possible in space-based communications.<br>
If you're passionate about solving hard problems at the intersection of space technology, distributed systems, and operational excellence, we want to hear from you.<br>
<br>
Export Control Requirement:
<br>
Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.<br>
<br>
Key job responsibilities<br>
<ul><li>Lead end-to-end automation initiatives as a team leader, developing sophisticated tools and services that address complex network operations, debugging, and troubleshooting challenges while guiding team efforts and priorities.</li></ul><br>
<ul><li>Collaborate with cross-functional teams to analyze network architecture, stakeholder requirements, and customer needs; architect and implement software solutions that deliver measurable business value.</li></ul><br>
<ul><li>Design and implement AI/ML solutions utilizing AWS services to enhance space network operations and problem resolution.</li></ul><br>
<ul><li>Drive data-driven decision making by developing and maintaining comprehensive network KPI (Key Performance Indicators) systems, including databases, dashboards, and visualization platforms for performance monitoring and reporting.</li></ul><br>
<ul><li>Provide technical leadership and mentorship as a team leader to software/network engineers through effective task delegation, project management, and onboarding programs to optimize team productivity and development cycles.</li></ul><br>
A day in the life<br>
As Senior Software Engineer, you begin your day by reviewing satellite network data, identifying anomalies, and formulating mitigation plans. You then analyze the performance metrics of the team's software tools/services, using these insights to guide your decision-making. Drawing on your deep expertise in distributed systems, cloud infrastructure, and DevOps, you lead cross-functional discussions to collaboratively design scalable architectures that automate data collection, analysis, and issue resolution. Throughout the day, you mentor junior engineers, align stakeholders, update project plans, showcasing your technical prowess, problem-solving skills, exceptional leadership to ensure the reliable operation of complex space satellite network.<br>
<br>
About the team<br>
The Optical Inter-Satellite Link (OISL) organization is responsible for the design, development, and manufacturing of critical hardware and software that makes laser links between satellites possible. We are rapidly expanding and developing a new Network Automation team. We are looking for a senior software engineer to join and lead our new team to develop novel software services that can automate fault finding based on satellite data, automate workflows and operational procedures, and use ML/AI to find and correlate anomalies in the space network, identify root causes, and predict customer impacts.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>8+ years of non-internship professional software development experience</li><li>6+ years of programming with at least one software programming language experience</li><li>6+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>Experience as a mentor, tech lead or leading an engineering team</li><li>6+ years of designing and developing large-scale, multi-tiered, multi-threaded, distributed software applications, tools, systems, and services using: Java, JavaScript, TS, Python, React, Angular, etc.</li><li>Experience with AWS services such as EC2, S3, SQS, SNS, Lambda, Kafka, DynamoDB and event-driven systems etc.</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>8+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>Bachelor's degree in computer science or equivalent</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, WA, REDMOND - 168,100.00 - 227,400.00 USD annually</div><p></p>

Senior Software Development Engineer, Amazon Leo OISL

<div><b>Overview</b><p><br>
We&rsquo;re building a Frontier Marketing organization where the Media Data Science &amp; Analytics team leads the way in transforming how Microsoft measures, analyzes, and optimizes media and digital experiences. Our team blends advanced analytics, experimentation, and AI-powered insights to drive smarter decision making and measurable business outcomes across paid media and owned digital properties. We operate with agility, prioritize outcomes over activity, and embrace rapid learning loops to unlock deeper audience understanding, maximize impact, and accelerate innovation in media and discovery strategy.</p><p></p><p><br>
To support this transformation, we are seeking a Senior Data Scientist to lead advanced experimentation and causal inference efforts that enable rigorous campaign measurement and drive data-informed marketing decisions at scale. In this role, you'll directly support Microsoft's mission by enabling data-driven marketing decisions that drive customer engagement and revenue growth. Shape What You Will Do As a Senior Data Scientist on the Media Data Science and Analytics team, you will design and implement advanced experimentation frameworks including Bayesian hypothesis testing, causal inference modeling, and heterogeneous treatment effect analysis, while building and deploying Machine Learning (ML) models and data pipelines to support portfolio impact measurement and campaign analytics at scale. This will include developing solutions that are reusable, readily discoverable by decision makers, and self-service oriented, driving meaningful interpretation of data, and supporting campaign optimization.</p><p></p><p><br>
This candidate thrives in fast-paced environments, demonstrates comfort with ambiguity, and collaborates effectively across teams and functional boundaries. Curiosity, a bias for action, and the ability to balance business context with technical experience are essential. In this role, you will support the rhythm of business by providing actionable recommendations to stakeholders based on rigorous analysis and clear insights. You will leverage statistical and machine learning techniques to develop scalable, efficient, and impactful data products while also diving deep into the details to uncover the story behind the data. You will bring sharp analytical thinking, communication skills, and the confidence to engage with executives and stakeholders across the business.</p><p></p><p><br>
Microsoft&rsquo;s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.</p><p>
In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.</p><p></p><b><br>
Responsibilities</b><br>
<ul><li>
Experimentation and Causal Inference Design and implement advanced experimentation frameworks including Bayesian hypothesis testing and causal inference modeling.</li><li>
Develop heterogeneous treatment effect analyses to understand differential campaign impacts across customer segments.</li><li>
Establish clear linkage between A/B test results and desired business outcomes.</li><li>
Assess the degree to which campaigns meet business objectives and address gaps.</li><li>
Ensure alignment on definitions and standards across stakeholders.</li><li>
Define, design, and promote appropriate feedback and evaluation methods. Present results and findings to senior stakeholders.</li><li>
Build and deploy ML models to support portfolio impact measurement and campaign analytics at scale.</li><li>
Develop and maintain data pipelines that enable scalable, automated analysis.</li><li>
Evaluate the viability of automated methods for data collection, reporting, and analysis.</li><li>
Ensure solutions are reusable, easily discoverable, and self-service oriented.</li><li>
Identify and promote methods that enhance efficiency in analytics and reporting.</li><li>
Drive meaningful data interpretation to inform business decisions and shape organizational understanding through compelling storytelling.</li><li>
Recommend and socialize optimal methods for operationalizing, sharing, and scaling insights.</li><li>
Share knowledge and practical rationale for transitioning ad-hoc analyses to regular reporting features.</li><li>
Share domain knowledge to create clarity and ensure readiness to leverage data and insights effectively.</li><li>
Orchestration and Collaboration Leverage working relationships within and across teams to ensure alignment and quality execution.</li><li>
Drive the adoption of recommended data sources and analysis practices.</li><li>
Consult across teams and influence data strategy, experimentation culture, and measurement frameworks on decisions related to data sourcing, analyses, and interpretation of results.</li><li>
Coach and mentor less experienced analysts, as needed, and enable cross-functional partners to become data-savvy.</li><li>
Share insights and analytical experience through various means, including dashboards, reports, and visualizations.</li><li>
Synthesize and simplify details across analyses to highlight relevant findings. Identify opportunities to improve the efficiency of insights reporting techniques.</li><li>
Guide others and establish partnerships with stakeholders to ensure results are accessible and relevant.</li><li>
Embody our Culture and Values</li></ul><br>
<b>
Qualifications</b><p><b><br>
Required/minimum qualifications</b></p><ul><li>
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) experience in data science, applied statistics, machine learning, or quantitative research</li><li><ul><li>
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years experience in data science, applied statistics, machine learning, or quantitative research</li><li>
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years experience in data science, applied statistics, machine learning, or quantitative research</li><li>
OR equivalent experience.</li></ul></li></ul><p></p><p><b><br>
Additional or preferred qualifications</b></p><ul><li>
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years experience in data science, applied statistics, machine learning, or quantitative research</li><li><ul><li>
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years experience in data science, applied statistics, machine learning, or quantitative research</li><li>
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years experience in data science, applied statistics, machine learning, or quantitative research</li><li>
OR equivalent experience.</li></ul></li></ul><ul><li>
4+ years of experience with Python or R for statistical analysis and machine learning.</li><li>
4+ years of experience with SQL and data pipeline development.</li><li>
3+ years of experience designing and analyzing A/B experiments or causal inference studies.</li><li>
2+ years of experience with Bayesian methods, causal inference techniques (e.g., difference-in-differences, instrumental variables, propensity score matching), or heterogeneous treatment effect estimation.</li><li>
2+ years of experience building and deploying ML models.</li><li>
4+ years of experience presenting complex technical findings to both technical and non-technical senior level stakeholders.</li><li>
Experience with marketing mix modeling (MMM) or attribution modeling.</li><li>
Experience with cloud-based ML platforms (e.g., Azure ML, Databricks).</li><li>
4+ years' experience analyzing marketing campaign performance.</li><li>
Experience with Microsoft Fabric, Power BI, or similar visualization platforms.</li></ul><br>
<br>
<br>
<p>Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.
</p><p></p><p>Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:<br>
https://careers.microsoft.com/us/en/us-corporate-pay</p><p><br>
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.</p><p></p><p><br>
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process<b>.</b></p></div>

Senior Data Scientist

Explore 75+ Senior ai machine learning engineer minecraft in Redmond this March. Find roles across top companies and apply now to boost your career.