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Seated

<div><p>This role is on-site, 5 days a week, working from our Flatiron office in NYC.</p><p></p><p><b>
About Seated</b></p><p>
Seated is the first dynamic pricing platform for restaurants. We help fill their empty seats while providing consumers incredible rewards to top brands and unique experiences. We are quickly expanding our offerings to cities across the country and are looking for talented and ambitious people to embark on the journey with us!</p><p></p><p><b>
Role Overview</b></p><p><br>
We're fast-paced, innovative, and metric-driven, with a team passionate about delighting our customers. We're looking for a mid-level Software Development Engineer with a strong foundation in backend systems and distributed architectures. You'll help build and scale the systems that power Seated's growing platform.</p><p></p><p>
You'll translate business needs into live features and partner directly with business owners who recognize the value of technology. You'll have a strong voice in product design and ownership across coding, QA, and production support.</p><p></p><p><b>
Responsibilities</b></p><ul><li>
Design, build, and maintain scalable backend systems that power our core platform services</li><li>
Partner with business stakeholders to translate requirements into well‑implemented, deterministic workflows and services</li><li>
Build reliable, fault‑tolerant distributed systems with strong coding, testing, observability, performance, and reliability practices
</li><li>Contribute to technical design for high‑performance, service‑oriented architectures</li><li>
Scale backend services and microservices for high throughput and low latencey</li></ul><br>
<b>
Requirements</b><br>
<ul><li>
Bachelor&rsquo;s in Computer Science or Engineering; 3+ years of experience shipping production payment/fintech systems</li><li>
Strong understanding of backend architecture and distributed systems design</li><li>
Ability to quickly learn new payment technologies and apply them to real‑world solutions and product design</li><li>
Proficiency in Java and the Spring Boot framework; or equivalent expertise in a similar object‑oriented language.</li><li>
Experience building high‑availability systems, including low‑latency APIs and distributed RESTful/gRPC services; practiced in backward compatibility, deterministic behavior, and idempotency</li></ul><p></p><p><b>
Preferred Experience</b></p><ul><li>
Solid knowledge of distributed databases and scalable, fault‑tolerant caching</li><li>
Experience with AI agents and prompt engineering; able to build web features using agentic workflows and modern frontend frameworks</li><li>
Cloud experience (AWS or GCP), containerization (Docker); familiarity with AWS services such as ECS, RDS, and Kinesis, plus observability tools like Datadog</li><li>
Preferred: Experience with workflow orchestration engines (Temporal, Cadence, or AWS Step Functions)</li></ul><br>
<b>
Benefits</b><br>
<ul><li>
$160K - $180K + stock options</li><li>
401k with company match</li><li>
Medical, dental, and vision coverage</li><li>
FSA, dependent care, and commuter benefits</li><li>
Paid parental leave and unlimited PTO</li><li>
TeleDoc, One Medical, Talkspace, and WellHub access</li><li>
Citi Bike membership</li><li>
$100 monthly Seated dining credit</li></ul></div>

Software Development Engineer II

Bloomberg

<div><div><div><div><div><div>Senior Software Engineer - Data &amp; Analytics Federation
</div></div></div></div></div><div><div><div><div><div>Location
</div><div>New York
</div></div><div><div>Business Area
</div><div>Engineering and CTO
</div></div><div><div>Ref #
</div><div>10050103
</div></div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>Description &amp; Requirements
</b></h2></div></div><div><div><div><div><div><div>Bloomberg&rsquo;s Data &amp; Analytics Federation group enables content providers to expose a wide variety of data and analytics to any consumer application, ensuring the highest quality and reducing time to market. At the core of that mission is Calcrt, the single point of entry for the Bloomberg Terminal and Enterprise systems to retrieve any kind of data - serving over 400 billion requests a day.</div><div></div><div><br>
We own CalcrtX, a ground-up redesign that will redefine how data providers integrate with Calcrt. This moonshot project brings a modern, service-oriented architecture to one of Bloomberg&rsquo;s most critical systems, making it easier for data providers to deliver content at massive scale and higher reliability.</div><div></div><div><b><br>
Our team:</b></div>
<div>
We&rsquo;re the backbone of Bloomberg&rsquo;s data infrastructure, connecting applications to every type of content they need. Our work powers everything from market analytics to client dashboards. We design, build, and operate systems that must perform flawlessly at global scale.</div><div></div><div><br>
Our stack includes Modern C++, Python, BAS, Apache Arrow, and microservices-based async frameworks running on Linux.</div><div></div><div><b><br>
We'll trust you to:</b></div>
<ul><li>Shape the architecture and design of CalcrtX from the ground up.</li></ul>
<ul><li>Solve distributed systems problems at multi-billion-request-per-day scale.</li></ul>
<ul><li>Collaborate with dozens of teams across Engineering to redefine how data flows across Bloomberg.</li></ul>
<ul><li>Learn continuously through tech talks, study groups, and internal/external presentations.</li></ul>
<ul><li>Design and implement highly scalable, resilient microservices for CalcrtX.</li></ul>
<ul><li>Partner with data provider and client teams to streamline integration and performance.</li></ul>
<ul><li>Build tooling and frameworks that improve developer experience for hundreds of internal teams.</li></ul>
<ul><li>Ensure operational excellence, reliability, and observability across the new architecture.</li></ul>
<ul><li>Continuously optimize latency, throughput, and resource efficiency.</li></ul><div></div><div><b><br>
You'll need to have:</b></div>
<ul><li>4+ years of experience developing in Modern C++ or Python.</li></ul>
<ul><li>Strong system design and distributed systems fundamentals.</li></ul>
<ul><li>Familiarity with asynchronous frameworks and service-oriented architectures.</li></ul>
<ul><li>A collaborative mindset with excellent communication skills.</li></ul>
<ul><li>A degree in Computer Science, Engineering, Mathematics, or a related field &mdash; or equivalent work experience.</li></ul><div></div><div><b><br>
We'd love to see:</b></div>
<ul><li>Experience with Apache Arrow, BAS, or high-throughput data processing systems.</li></ul>
<ul><li>Knowledge of Linux system programming or performance engineering.</li></ul>
<ul><li>Contributions to large-scale infrastructure or open-source projects.</li></ul>
<ul><li>Passion for improving developer productivity and platform experience.</li></ul></div>
</div></div><div><div><div>Salary Range = 160000 - 240000 USD Annually + Benefits + Bonus</div><div><br>
<div><br>
</div><div>The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.<div><br>
<br>
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.<br>
</div></div></div></div></div><div><div>Discover what makes Bloomberg unique - watch our for an inside look at our culture, values, and the people behind our success.</div></div></div></div></div></div>

Senior Software Engineer - Data & Analytics Federation

Rippling

<div><h2 class="jobSectionHeader"><b>About Rippling</b></h2><p>
Rippling gives businesses one place to run HR, IT, and Finance. It brings together all of the workforce systems that are normally scattered across a company, like payroll, expenses, benefits, and computers. For the first time ever, you can manage and automate every part of the employee lifecycle in a single system.</p><p></p><p><br>
Take onboarding, for example. With Rippling, you can hire a new employee anywhere in the world and set up their payroll, corporate card, computer, benefits, and even third-party apps like Slack and Microsoft 365&mdash;all within 90 seconds.</p><p></p><p><br>
Based in San Francisco, CA, Rippling has raised $1.4B+ from the world&rsquo;s top investors&mdash;including Kleiner Perkins, Founders Fund, Sequoia, Greenoaks, and Bedrock&mdash;and was named one of America's best startup employers by Forbes.</p><p></p><p><br>
We prioritize candidate safety. Please be aware that all official communication will only be sent from @Rippling.com addresses.</p><h2 class="jobSectionHeader"><b><br>
About the role</b></h2><p>
The Data Bridge team at Rippling is assembling founding members to build data systems that will power ML models and new product lines. Our team is a foundational platform component positioned at the core of Rippling's compound startup strategy. We're set to build advanced data systems, enabling Rippling to exceed its current 500+ integrations and solidify its reputation as the go-to for launching groundbreaking HR, IT, and Benefits products.</p><p>
As the market increasingly rewards organizations that own scaled distribution networks, control extensive data sets, and rapidly bring products to market, Rippling and the Data Bridge team are poised to lead. If you are serious about your craft, eager to establish infrastructure with a long-term impact, and have a focused approach to delivering substantial value quickly, we&rsquo;d love to have you on the Data Bridge team at Rippling.</p><h2 class="jobSectionHeader"><b>
What you will do</b></h2><ul><li>
Lead mission-critical projects and deliver data ingestions capabilities end-to-end with high quality</li><li>
Have clear ownership of one or many products, APIs or platform spaces</li><li>
Work within Rippling's central infrastructure team, responsible for delivering highly scalable distributed data ingestion systems, build a data lake architecture for various downstream systems to consume</li><li>
Get exposure to partners and customers in different business domains, who will help provide feedback for your product space</li><li>
Ensure operational excellence and scale the platform capabilities to serve many different UCs across Rippling Products.</li><li>
Build and grow your engineering skills in different challenging areas and solve hard technical problems</li><li>
Influence architecture, technology selections, and trends of the whole company</li></ul><h2 class="jobSectionHeader"><b>
What you will need</b></h2><ul><li>
8+ years of professional work experience as a backend engineer</li><li>
Significant leadership experience driving complex cross-functional projects across teams, product managers, designers, etc</li><li>
Expertise in building complex distributed services with high availability and strict SLAs</li><li>
Experience building large-scale user-facing applications, APIs, and developer tools</li><li>
Strong CS fundamentals, and knowledge of architecture and common design patterns</li><li>
You&rsquo;re passionate about being in a product-focused environment where everyone cares deeply about customer impact</li><li>
You have experience of running data processing pipelines in production using distributed data processing frameworks like Apache Spark or Flink.</li><li>
Bonus points if you&rsquo;ve built integrations with 3rd party SaaS providers and workflow orchestration systems</li><li>
Bonus points if you&rsquo;ve previously worked with AWS and have working knowledge of observability tooling</li></ul><h2 class="jobSectionHeader"><b>
Additional Information</b></h2><p>
Rippling is an equal opportunity employer. We are committed to building a diverse and inclusive workforce and do not discriminate based on race, religion, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, veteran or military status, or any other legally protected characteristics, Rippling is committed to providing reasonable accommodations for candidates with disabilities who need assistance during the hiring process. To request a reasonable accommodation, please email accommodations@rippling.com</p><p></p><p><br>
Rippling highly values having employees working in-office to foster a collaborative work environment and company culture. For office-based employees (employees who live within a defined radius of a Rippling office), Rippling considers working in the office, at least three days a week under current policy, to be an essential function of the employee's role.</p><p></p><p><br>
This role will receive a competitive salary + benefits + equity. The salary for US-based employees will be aligned with one of the ranges below based on location; see which tier applies to your location here.</p><p></p><p><br>
A variety of factors are considered when determining someone&rsquo;s compensation&ndash;including a candidate&rsquo;s professional background, experience, and location. Final offer amounts may vary from the amounts listed below.</p><b><br>
The pay range for this role is:</b><br>
189,000 - 330,750 USD per year(US Tier 1)</div>

Staff Software Engineer - Data Bridge

Clipbook

<div><h2 class="jobSectionHeader"><b>About Clipbook</b></h2><p>
Clipbook builds AI-powered media monitoring and analytics tools for communications, PR, and public affairs teams. We help them track, search, and make sense of coverage across text, audio, and video.</p><p>
We launched in 2023 and have grown to 200+ clients including BCG, Weber Shandwick, and dozens of government agencies. We bootstrapped to seven-figures in ARR before raising a $3.3M seed round (co-led by Mark Cuban). We plan to raise our Series A this year and we are aiming for eight-figures revenue by end of year.</p><p>
Our founding team has backgrounds at BCG, Bain, Harvard, Stanford, Oxford, the White House, and Congress, and has previously built startups backed by Sequoia, Tiger Global, Insight Partners, Coatue, and NFX.</p><p></p><h2 class="jobSectionHeader"><b>
The Role</b></h2><p>
You'd be one of the first engineers at Clipbook &mdash; joining a small but mighty engineering team with engineers from Meta, Stripe, and AWS. You'll have real influence over architecture and technical direction, and what you build will ship to 200+ customers quickly.</p><p></p><h2 class="jobSectionHeader"><b>
What You'll Do</b></h2><ul><li><p><b>
Architect &amp; build core backend systems.</b> Drive architectural decisions across our backend stack (Python, Node.js, PostgreSQL). Own features from concept deployment observing users rely on what you built. We're still laying critical foundations, so we value a pragmatic, &quot;strong opinions, weakly held&quot; mindset &mdash; especially when decisions are expensive to unwind later.</p></li><li><p><b>
Design scalable data infrastructure.</b> Build and maintain pipelines for ingesting, normalizing, deduplicating, indexing, and querying massive, multi-modal datasets (text, audio, video) across news, social media, policy, and more. A lot of this is normalization, deduplication, and edge case handling.</p></li><li><p><b>
Integrate AI into real-world workflows.</b> Put LLMs and ML models into production for real workflows: RAG pipelines, embeddings, prompt execution, agentic systems, fine-tuned models. Production means reliable, monitored, and cost-conscious.</p></li><li><p><b>
Design systems that scale.</b> Build systems that will hold up as we grow 10x, while being practical about what to invest in now vs. what can wait.</p></li><li><p><b>
Develop performant APIs and services.</b> Create robust interfaces and internal services that power our product end-to-end, ensuring reliability, security, and a seamless experience for customers.</p></li><li><p><b>
Collaborate closely with users.</b> Join customer calls, hear what's working and what isn't, and build in response. Rapidly iterate to deliver solutions that genuinely move the needle for comms/public affairs teams.</p></li><li><p><b>
Shape Clipbook's engineering culture.</b> As one of the first engineers, you'll influence everything &mdash; code quality, system design principles, documentation standards, and how we build as a team. We believe leaders stay hands-on: even as we grow, everyone (including managers) continues to ship.</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
What We're Looking For</b></h2><ul><li><p><b>
2&ndash;10+ years building and scaling production backend systems.</b> You've taken systems from zero to production and owned the full lifecycle. Strong across backend fundamentals (services, data models, distributed systems), with deeper expertise in one or more areas &mdash; and a desire to keep expanding your breadth over time.</p></li><li><p><b>
Genuine excitement to build quickly &amp; ship fast.</b> We care about getting things into users' hands and iterating from there.</p></li><li><p><b>
You take ownership.</b> When something is broken or unclear, you fix it or flag it without waiting to be asked.</p></li><li><p><b>
Comfortable with ambiguity.</b> You make reasonable calls with incomplete information, communicate them clearly, and adjust as you learn more.</p></li><li><p><b>
Strong experience with cloud infrastructure, containerization, and CI/CD.</b> We're building systems that will one day serve Fortune 500 executives in real-time &mdash; so reliability matters. Familiarity with AWS/GCP, containerization (Docker/K8s), and CI/CD pipelines ensures we can deliver high uptime and iterate quickly.</p></li><li><p><b>
A future leader.</b> You'll help shape our engineering culture and can quickly grow into leadership as the company scales.</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Technical Areas Where Depth Matters (one or more)</b></h2><ul><li><p><b>
Data Engineering:</b> Spark, Kafka, Flink, BigQuery, streaming pipelines, ETL at scale.</p></li><li><p><b>
Distributed Systems:</b> High-volume scaling, fault tolerance, eventual consistency.</p></li><li><p><b>
AI/ML:</b> LLMs in production, RAG, embeddings, fine-tuning, inference optimization.</p></li><li><p><b>
Backend:</b> Python, Node.js, PostgreSQL, high-concurrency systems.</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Nice-to-Haves</b></h2><ul><li><p>
Computer vision or multimodal model experience (audio, video, image). This is central to our product, so it's a meaningful differentiator.</p></li><li><p>
Semantic search, vector databases, or meaning-aware retrieval.</p></li><li><p>
LLM fine-tuning, RLHF, or eval pipelines.</p></li><li><p>
Web scraping and API integrations at scale.</p></li><li><p>
Startup founder or early-stage experience is a huge plus.</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
What This Role Is Not</b></h2><p>
We're hiring for the application and data layer. This probably isn't the right fit if your background is primarily in firmware, embedded systems, hardware engineering, networking, or infrastructure/DevOps.</p><p></p><h2 class="jobSectionHeader"><b>
A Few Things Worth Knowing</b></h2><ul><li><p>
We care more about what you ship than when or where you work, but this is an early-stage company growing fast. The pace reflects that. Our culture is intense and driven by H&amp;H (hunger and hustle).</p></li><li><p>
As one of the first engineers, you'll wear a lot of hats. There's no platform team to hand things off to yet.</p></li></ul><h2 class="jobSectionHeader"><b>
Compensation &amp; Benefits</b></h2><ul><li><p><b>
Salary:</b> $150K&ndash;$220K</p></li><li><p><b>
Equity:</b> Early-stage grant with significant upside</p></li><li><p><b>
Benefits:</b> Medical, dental, vision, 401(k), unlimited PTO</p></li></ul><p><b>
Growth:</b> A clear path to engineering leadership as we scale</p></div>

Founding Backend Engineer – AI & Data

Amazon Web Services

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Annapurna Labs team at Amazon Web Services (AWS) builds AWS Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon&rsquo;s custom machine learning accelerators, Inferentia and Trainium.<br>
<br>
The AWS Neuron SDK, developed by the Annapurna Labs team at AWS, is the backbone for accelerating deep learning and GenAI workloads on Amazon's Inferentia and Trainium ML accelerators. This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch and JAX enabling unparalleled ML inference and training performance.<br>
<br>
The Inference Enablement and Acceleration team is at the forefront of running a wide range of models and supporting novel architecture alongside maximizing their performance for AWS's custom ML accelerators. Working across the stack from PyTorch till the hardware-software boundary, our engineers build systematic infrastructure, innovate new methods and create high-performance kernels for ML functions, ensuring every compute unit is fine tuned for optimal performance for our customers' demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what's possible in AI acceleration.<br>
<br>
As part of the broader Neuron organization, our team works across multiple technology layers - from frameworks and kernels and collaborate with compiler to runtime and collectives. We not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection of machine learning, high-performance computing, and distributed architectures, where you'll help shape the future of AI acceleration technology<br>
<br>
You will architect and implement business critical features, and mentor a brilliant team of experienced engineers. We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint. We're inventing. We're experimenting. It is a very unique learning culture. The team works closely with customers on their model enablement, providing direct support and optimization expertise to ensure their machine learning workloads achieve optimal performance on AWS ML accelerators. The team collaborates with open source ecosystems to provide seamless integration and bring peak performance at scale for customers and developers.<br>
<br>
This role is responsible for development, enablement and performance tuning of a wide variety of LLM model families, including massive scale large language models like the Llama family, DeepSeek and beyond. The Inference Enablement and Acceleration team works side by side with compiler engineers and runtime engineers to create, build and tune distributed inference solutions with Trainium and Inferentia. Experience optimizing inference performance for both latency and throughput on such large models across the stack from system level optimizations through to Pytorch or JAX is a must have.<br>
<br>
You can learn more about Neuron<br>
https://awsdocs-neuron.readthedocs-hosted.com/en/latest/neuron-guide/neuron-cc/index.html<br>
https://aws.amazon.com/machine-learning/neuron/<br>
https://github.com/aws/aws-neuron-sdk<br>
https://www.amazon.science/how-silicon-innovation-became-the-secret-sauce-behind-awss-success<br>
<br>
Key job responsibilities<br>
This role will help lead the efforts in building distributed inference support for Pytorch in the Neuron SDK. This role will tune these models to ensure highest performance and maximize the efficiency of them running on the customer AWS Trainium and Inferentia silicon and servers. Strong software development using Python, System level programming and ML knowledge are both critical to this role. Our engineers collaborate across compiler, runtime, framework, and hardware teams to optimize machine learning workloads for our global customer base. Working at the intersection of software, hardware, and machine learning systems, you'll bring expertise in low-level optimization, system architecture, and ML model acceleration. In this role, you will:<br>
<br>
<ul><li>Design, develop, and optimize machine learning models and frameworks for deployment on custom ML hardware accelerators.</li><li>Participate in all stages of the ML system development lifecycle including distributed computing based architecture design, implementation, performance profiling, hardware-specific optimizations, testing and production deployment.</li><li>Build infrastructure to systematically analyze and onboard multiple models with diverse architecture.</li><li>Design and implement high-performance kernels and features for ML operations, leveraging the Neuron architecture and programming models</li><li>Analyze and optimize system-level performance across multiple generations of Neuron hardware</li><li>Conduct detailed performance analysis using profiling tools to identify and resolve bottlenecks</li><li>Implement optimizations such as fusion, sharding, tiling, and scheduling</li><li>Conduct comprehensive testing, including unit and end-to-end model testing with continuous deployment and releases through pipelines.</li><li>Work directly with customers to enable and optimize their ML models on AWS accelerators</li><li>Collaborate across teams to develop innovative optimization techniques</li></ul><br>
A day in the life<br>
You will collaborate with a cross-functional team of applied scientists, system engineers, and product managers to deliver state-of-the-art inference capabilities for Generative AI applications. Your work will involve debugging performance issues, optimizing memory usage, and shaping the future of Neuron's inference stack across Amazon and the Open Source Community. As you design and code solutions to help our team drive efficiencies in software architecture, you&rsquo;ll create metrics, implement automation and other improvements, and resolve the root cause of software defects.<br>
<br>
You will also build high-impact solutions to deliver to our large customer base and participate in design discussions, code review, and communicate with internal and external stakeholders. You will work cross-functionally to help drive business decisions with your technical input. You will work in a startup-like development environment, where you&rsquo;re always working on the most important initiative.<br>
<br>
About the team<br>
The Inference Enablement and Acceleration team fosters a builder&rsquo;s culture where experimentation is encouraged, and impact is measurable. We emphasize collaboration, technical ownership, and continuous learning. Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we&rsquo;re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Join us to solve some of the most interesting and impactful infrastructure challenges in AI/ML today.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>5+ years of non-internship professional software development experience</li><li>Bachelor's degree in computer science or equivalent</li><li>5+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>Fundamentals of Machine learning and LLMs, their architecture, training and inference lifecycles along with work experience on optimizations for improving the model execution.</li><li>Software development experience in C++, Python (experience in at least one language is required).</li><li>Strong understanding of system performance, memory management, and parallel computing principles.</li><li>Proficiency in debugging, profiling, and implementing best software engineering practices in large-scale systems.</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Familiarity with PyTorch, JIT compilation, and AOT tracing.</li><li>Familiarity with CUDA kernels or equivalent ML or low-level kernels.</li><li>Candidates with performant kernel development such as CUTLASS, FlashInfer etc., would be well suited.</li><li>Familiar with syntax and tile-level semantics similar to Triton.</li><li>Experience with online/offline inference serving with vLLM, SGLang, TensorRT or similar platforms in production environments.</li><li>Deep understanding of computer architecture, operation systems level software and working knowledge of parallel computing.</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 - 184,900.00 - 250,200.00 USD annually<br>
USA, WA, Seattle - 168,100.00 - 227,400.00 USD annually</div><p></p>

Senior Software Development Engineer - AI/ML, AWS Neuron, Multimodal Inference

<div><div><div><div><div><div>Applied Machine Learning Engineer - Media Search and Recommendation
</div></div></div></div></div><div><div><div><div><div>Location
</div><div>New York
</div></div><div><div>Business Area
</div><div>Engineering and CTO
</div></div><div><div>Ref #
</div><div>10049313
</div></div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>Description &amp; Requirements
</b></h2></div></div><div><div><div><div><h3 class="jobSectionHeader">Our Team<b>
</b></h3>
<div>Bloomberg Media empowers global business leaders with breaking news, expert opinion and proprietary data distributed with global reach. With millions of unique visitors each month, our flagship website bloomberg.com is the go-to destination for those looking to stay ahead of the curve. As one of the top 10 most visited financial and news sites on the web, we take pride in delivering top-quality content that our audience can trust.</div>
<div>
The Search and Personalization team owns the core discovery experiences on Bloomberg.com and the Bloomberg mobile app. We are responsible for how users search for, discover, and engage with content across a global audience, with a strong focus on personalization and recommendations. By powering Bloomberg&rsquo;s discovery hub, we play a critical role in helping users find the content that matters most to them, ensuring experiences are relevant, timely, and high quality. Our systems operate at web scale and sit at the intersection of backend services, data pipelines, and user-facing experiences. We are looking for a dedicated and experienced Machine Learning engineer to join the team. The ideal candidate will have a passion for Machine Learning, building distributed web scale systems and partnering with a variety of stakeholders within our expansive organization.</div>
<h3 class="jobSectionHeader"><b>
</b>What's in it for you<b>
</b></h3>
<p>As a senior engineer on the Search and Personalization team, you will play a key role in expanding Bloomberg Media&rsquo;s investment in personalization. You&rsquo;ll work closely with product managers, data scientists, and machine learning engineers to design and build systems that power personalized discovery experiences for millions of users.</p>
<p>
You&rsquo;ll have ownership over impactful projects, from shaping technical direction to delivering production systems. The role offers a mix of backend, data, and potentially some frontend work, giving you the opportunity to influence the personalization models that deliver results to users. You&rsquo;ll be working on systems that are central to Bloomberg Media&rsquo;s growth and directly visible to a global audience.</p>
<h3 class="jobSectionHeader"><b>
</b><b>We&rsquo;ll trust you to</b><b>
</b></h3>
<ul><li> Lead the design and delivery of personalization and recommendation systems that power discovery across Bloomberg.com and mobile platforms.</li></ul>
<ul><li> Build and maintain data pipelines that support personalization, experimentation, and model-driven product experiences.</li></ul>
<ul><li> Design, develop, and evolve backend services and APIs that deliver personalized content at scale with low latency.</li></ul>
<ul><li> Partner closely with the data science team to productionize models and enable rapid experimentation.</li></ul>
<ul><li> Collaborate across the stack, including with frontend engineers, to deliver cohesive and high-quality user experiences.</li></ul>
<ul><li> Make architectural decisions, drive technical discussions, and help set technical direction for the personalization platform.</li></ul>
<ul><li> Mentor other engineers and raise the overall technical bar of the team.</li></ul><br>
<br>
<h3 class="jobSectionHeader"><b>You need to have</b><b>
</b></h3>
<ul><li> 5+ years of industry experience in an Object Oriented Programming language, preferably Python or Java</li></ul>
<ul><li> 5+ years of industry experience working with large data sets, performing machine learning model experimentation, implementation and deployment.</li></ul>
<ul><li> A Bachelor&rsquo;s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent professional experience.</li></ul>
<h3 class="jobSectionHeader"><b>
</b><b>We&rsquo;d love to see</b><b>
</b></h3>
<ul><li> Exposure building and developing a content recommendation system, focusing on recommendation algorithms and machine learning capabilities</li></ul>
<ul><li> Familiarity building user behavioral models to predict users likelihood to perform high value actions like propensity to subscribe or churn</li></ul>
<ul><li> Experience with end-to-end machine learning projects, including data analysis, feature engineering, model selection, hyper-parameter tuning, model deployment and ongoing performance monitoring.</li></ul>
<h3 class="jobSectionHeader"><b>
</b><b>&middot;</b> <b>Hands-on expertise with big data systems and distributed data processing technologies such as Spark</b><b>
</b></h3><h3 class="jobSectionHeader"><b>&middot;</b> <b>Proven track record building and maintaining data pipelines that power customer-facing product features.</b><b>
</b></h3><h3 class="jobSectionHeader"><b>&middot;</b> <b>Demonstrated leadership delivering machine learning projects from inception through delivery.</b><b>
</b></h3><h3 class="jobSectionHeader"><b>&middot;</b> <b>Practical expertise with public cloud platforms such as AWS.</b><b>
</b></h3><h3 class="jobSectionHeader"><b>&middot;</b> <b>Proven ability to operate and evolve web-scale distributed systems in production.</b><b>
</b></h3>
</div></div><p></p><div><div><div>Salary Range = 165000 - 260000 USD Annually + Benefits + Bonus</div><div><br>
<div><br>
</div><div>The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.<div><br>
<br>
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.<br>
</div></div></div></div></div><div><div>Discover what makes Bloomberg unique - watch our for an inside look at our culture, values, and the people behind our success.</div></div></div></div></div></div>

Applied Machine Learning Engineer - Media Search and Recommendation

Soundcloud

<div><div>SoundCloud empowers artists and fans to connect and share through music. Founded in 2007, SoundCloud is an artist-first platform empowering artists to build and grow their careers by providing them with the most progressive tools, services, and resources. With over 400+ million tracks from 40 million artists, the future of music is SoundCloud.</div>
<div>
<div><div><p>We are looking for a Senior Machine Learning Engineer to join our Recommendations Experience team, focusing on building ML-powered features that directly improve personalization, engagement, and satisfaction for our users. While this is an MLE role, you'll bring strong engineering fundamentals and work across the full stack and end-to-end systems, from data pipelines to APIs to real-time serving, and everything in between. The Recommendations team ships ML-powered features that connect 200M+ users with music they'll love.</p>
<p>
You'll own features end-to-end: from understanding user needs with Product and Design, to architecting data pipelines processing billions of events, to building and shipping production ML systems that balance performance, cost, and user experience. This means working across BigQuery (trillion-row datasets), Airflow orchestration, real-time serving infrastructure (BigTable), APIs, and constant collaboration with Product, Design, Engineering, and Platform teams.</p>
</div>
<p><b>Key Responsibilities:</b></p>
<ul>
<li>Develop, test, and productionize ML models</li>
<li>Make technical decisions considering cost, latency, complexity, and maintainability</li>
<li>Navigate distributed systems (BigQuery, BigTable, Airflow, DynamoDB) to build reliable, scalable solutions</li>
<li>Design and implement data pipelines, feature engineering, model training, and serving infrastructure</li>
<li>Write technical RFCs and communicate trade-offs to diverse stakeholders</li>
<li>Set up monitoring, A/B testing, and metrics frameworks to measure real user impact</li>
<li>Debug complex issues across data pipelines, ML models, and distributed systems</li>
<li>Champion maintainable code over clever code - write clear, testable Scala/Python that your teammates can modify</li>
<li>Share knowledge through documentation, code reviews, and mentoring</li>
<li>Contribute to technical strategy and team best practices</li>
<li>Leverage agentic workflows and AI-assisted engineering as a force multiplier to work at 10x the speed of traditional methods</li>
</ul>
<p><b>Experience and Background:</b></p>
<ul>
<li>1-2+ years building ML systems in production - you understand the difference between a model that works in Jupyter and one that serves millions of users</li>
<li>4+ years of software engineering experience - you write production code, not just notebooks</li>
<li>Strong Scala knowledge or closely related JVM languages, with strong functional programming experience. Python and Go are a Plus.
</li><li>Deep SQL skills for massive datasets (BigQuery, Spark)</li>
<li>Cloud platform experience (AWS/GCP) and containerization (Docker, Kubernetes)</li>
<li>Familiarity with TensorFlow, PyTorch, or similar frameworks</li>
<li>Experience with distributed data processing and ETL pipelines (Airflow, Spark)</li>
<li>Understanding of data consistency patterns, eventual consistency, and the trade-offs</li>
<li>You can debug issues across multiple systems and data sources</li>
</ul>
</div><p><i>The salary range for this role is $165,000 - $195,000 annually. The final salary offered will be determined based on relative experience, skills, internal equity, and location. We also offer a generous total rewards program - read more about additional benefits and perks below!</i></p>
</div>
<h4 class="jobSectionHeader"><b>About us:</b></h4>
<ul><li>We are a multinational company with offices in the US (New York and Los Angeles), Germany (Berlin), and the UK (London)</li>
<li>We provide a flexible work culture that offers the opportunity to collaborate and connect in person at our offices as well as accommodating work from home</li>
<li>We are deeply committed to ensuring diversity, equity and inclusion at all levels of our organization and fostering a community where everyone's voice, perspective and experience is respected and heard</li>
<li>We believe a strong team is made by investing in employees through mentorship, workshops and enrichment opportunities</li>
</ul><h4 class="jobSectionHeader"><b>Benefits:</b></h4>
<ul><li>Comprehensive health benefits including medical, dental, and vision plans, as well as mental health resources</li>
<li>Robust 401k program</li>
<li>Employee Equity Plan</li>
<li>Generous professional development allowance</li>
<li>Interested in a gym membership, photography course or book? We have a Creativity and Wellness benefit!</li>
<li>Flexible vacation and public holiday policy where you can take up to 35 days of PTO annually</li>
<li>16 paid weeks for all parents (birthing and non-birthing), regardless of gender, to welcome newborns, adopted and foster children</li>
<li>Various snacks, goodies, and 2 free lunches weekly when at the office</li>
</ul><h4 class="jobSectionHeader"><b>Diversity, Equity and Inclusion at SoundCloud</b></h4>
<p><i>
SoundCloud is for everyone. Diversity and open expression are fundamental to our organization; they help us lead what's next in music by understanding and empowering our creators and fans, no matter their identity. We acknowledge the challenges in the music industry, and strive to influence an inclusive culture where everyone can contribute respectfully and thrive, especially the historically marginalized communities that many of our creators, fans and SoundClouders identify with. We are dedicated to creating an inclusive environment at SoundCloud for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or care-giver status.</i></p>
<p><i>
At SoundCloud you can find your community or elevate your allyship by joining a Diversity Resource Group. Diversity Resource Groups are employee-organized groups focused on supporting and promoting the interests of a particular underrepresented community in order to build a more inclusive culture at SoundCloud. Anyone can join, whether you share the identity or strive to be an ally.</i></p></div>

Senior Machine Learning Engineer, Recommendations (Experience)

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