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deep learning engineer

Hayden AI

<div>
 
 About Us
 
 
 
 At Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.
 
 
 From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future.
 
 
 
 About The Deep Learning Team
 
 
 
 The Deep learning team&rsquo;s work is at the crux of Hayden AI&rsquo;s solutions to its customers. The team is responsible for building and maintaining advanced models that are able to perceive the world and the knowledge produced by the models is used downstream to implement various customer use-cases. The team runs a number of models both in the cloud as well as on the edge device serving different scenarios. The team also works closely with the platform team to build out Hayden AI&rsquo;s MLOps infrastructure to achieve better scale and reliability.
 
 
 
 About The Role
 
 
 
 As a Deep Learning Engineer at Hayden, you will make key contributions towards building foundational AI capabilities for Hayden that will enable solving complex problems for Hayden AI Customers. In this role, you will build, train, evaluate and deploy state of the art ML models in production at scale. You will report into the Director of AI within the Perception Org and work closely with other engineering as well as product teams to deliver value to Hayden AI customers. We are looking for someone who has familiarity with or growing expertise in at least one of the verticals below &mdash; depth in a specific area is valued but not required on day one.
 
 
 <ul>
 <li>
 3D vision models to predict depth and 3D structure,
 </li>
 <li>
 Video/temporal behavior models to predict intent,
 </li>
 <li>
 Deep understanding of Vision language models and hands-on experience fine tuning them,
 </li>
 <li>
 Deep understanding of foundation models in perception.
 </li>
 <li>
 Deep knowledge of Nvidia edge device stack for running ML models and cuda know-how in terms delivering highly optimized models
 
 
 </li>
 </ul>
 This position is based in San Francisco and follows a hybrid schedule with at least 3 days in-office per week.
 
 
 
 
 Key Responsibilities
 
 
 
 
 Below are your primary responsibilities. These represent the core areas where you&rsquo;ll make an impact. As part of a rapidly evolving team, we look forward to your impact expanding over time.
 
 
 <ul>
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 Come up with solutions to complex problems in perception using deep learning.
 </li>
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 Articulate ideas both verbally and in written form culminating in clear design and project plan docs for their work
 </li>
 <li>
 Contribute to team roadmap and planning
 </li>
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 Work with cross functional teams across the company and contribute towards delivery of end to end solutions for the customer
 
 
 </li>
 </ul>
 
 Required Qualifications
 
 
 
 The qualifications below outline the experience and skills most relevant to success in this role. We recognize that skills and potential come in many forms, and we welcome diverse experiences that advance our mission.
 
 
 <ul>
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 Experience: 1-2 years experience building and deploying machine learning models for perception in production settings.
 </li>
 <li>
 Core Skills: Solid hands-on experience designing, training, and evaluating machine learning models for perception. Demonstrated ability to independently build ML pipelines and deploy models to cloud environments (AWS, GCP, or Azure); familiarity with MLOps practices including experiment tracking, model versioning, and automated workflows. Hands-on experience in PyTorch, Python, and related skills.
 </li>
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 Personal Attributes:Good communicator, self starter and ability to collaborate with others, quick learner who can adapt to a fast paced startup culture
 </li>
 <li>
 Education: Bachelors or Masters in Computer Science or related field
 </li>
 <li>
 Nice to Have: Experience working in perception problems in self driving car companies that aligns closely with the work of this team.
 
 
 </li>
 </ul>
 Compensation Range: $161,637 - $175,000
 
 
</div>

Deep Learning Engineer

Apple

The Apple Services Engineering AI/ML organization is hiring a Machine Learning Engineer to join the Search team for Video catalog. 
 
Our team builds the core intelligence that powers search discovery experiences in the Apple TV App, Siri, and Spotlight cross platforms, helping users effortlessly find and enjoy the content they love. We are a collaborative, high-impact team that values innovation, craftsmanship, and end-to-end ownership from idea to launch. Our systems combine large-scale data, modern retrieval and ranking models, and a deep commitment to user privacy. 
 
Join us, you&rsquo;ll develop scalable systems and machine learning models that drive search relevance, personalization, and understanding of content at scale. Working closely with cross-functional partners in product and design, you&rsquo;ll translate cutting-edge research in advanced machine learning and generative AI into secure and delightful production features used by millions every day. 
 
Description 
 
As a Machine Learning Engineer on the Video Search team, within the Apple Services Engineering AI/ML organization, you will design and deploy large-scale ML systems that power search and discovery across Apple platforms. 
 
You&rsquo;ll apply machine learning, natural language understanding, and generative AI to model user intent and deliver relevant, personalized results. Your work will involve building and optimizing cutting edge data processing, ML models, retrieval pipelines, and ranking systems that operate at global scale and under strict privacy standards. 
 
This is a hands-on role where you will collaborate closely with cross-functional teams to bring advanced ML technologies into production-shaping how users discovery content they love in Apple TV app, cross Apple TV partners on Apple Platforms, also through Siri and Spotlight.&quot;,&quot;responsibilities&quot;:&quot;Solve complex research problems and implement solutions from concept to execution. 
 
Design and implement retrieval and ranking systems using semantics and user context. 
 
Build and deploy ML, NLP and LLM models to improve search relevance and personalization. 
 
Analyze data and model performance to identify opportunities for search quality enhancement. 
 
Develop automated tests for continuous integration and ensure successful production deployment. 
 
Conduct A/B tests to measure search improvements. 
 
Collaborate with cross-functional teams to innovate intelligent video catalog text search. 
 
Enhance search recall and ranking for global Apple devices across all platforms and languages. 
 
Utilize big data tech to evaluate content discovery features. 
 
Ensure systems meet Apple&rsquo;s privacy, efficiency, and user experience standards. 
 
Preferred Qualifications 
 
Experience with search or recommendation systems, and semantic retrieval or vector databases. 
 
Expertise in transformer architectures, embeddings, and retrieval or ranking models. 
 
Experience in applying or fine-tuning LLMs for understanding and generation tasks. Familiarity with prompt design, context management, RAG and Agentic architectures and solutions. 
 
Exposure to evaluation and safety frameworks for LLM-based systems. 
 
Knowledge of reinforcement learning and other modern post training practices for LLMs. 
 
Passion for developing intelligent, human-centered experiences to enhance content discovery. 
 
Minimum Qualifications 
 
Experience in machine learning, NLP, IR, or more recently Large Language Model ( LLMs). 
 
Strong programming skills in Python, Java and Go for building scalable ML systems. 
 
Hands-on expertise in ML libraries such as PyTorch, JAX, TensorFlow for model training and deployment. 
 
Ability to translate product goals into technical solutions, improving user experience. 
 
Strong communication, collaboration, and analytical problem-solving skills. 
 
In-depth knowledge of search and information retrieval fundamentals, including indexing and ranking. Experience with retrieval and ranking algorithms and building big data pipelines using Hadoop, Java, Scala, Spark and more. 
 
Industrial experience in search, classification, recommendation systems, or related fields. 
 
Familiarity with A/B testing and data-driven product development. 
 
Passionate about creating products loved by customers at Apple. 
 
Bachelor&rsquo;s degree or higher (or equivalent practical experience) in Computer Science, Machine Learning, Natural Language Processing, Artificial Intelligence, or a related field. 
 
Pay &amp; Benefits 
 
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 $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
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 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Machine Learning Engineer, ASE Search Team

Whatnot

<div>
 
 
 🚀 Join the Future of Commerce with Whatnot!
 
 
 
 
 Whatnot is the largest livestream shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops.
 
 
 As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact.
 
 
 We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce.
 
 
 
 💻 Role
 
 
 
 At Whatnot data engineers build foundational data systems that power product development, experimentation, machine learning, and operational decision-making across the company. As an Data Engineer on the Notifications Platform, you will play a critical role in owning and evolving one of the highest-volume and highest-impact data domains at Whatnot.
 
 
 Notifications generate hundreds of millions of events per day, and the underlying data systems support everything from ML iteration and experimentation to adhoc engineering debugging. In this role, you will define the technical direction for the Notifications data mart, harden it to production-grade reliability, and set new patterns for domain-owned data engineering.
 
 
 Working in a highly cross-functional role, you will collaborate closely with Product Engineers, Data Scientists, ML Engineers, and the Analytics Platform team. You&rsquo;ll make key architectural decisions around data modeling, reliability, latency, and cost &mdash; and then make them real.
 
 
 
 On Any Given Day, You Will
 
 
 
 <ul>
 <li>
 Own data architecture end-to-end. Define how we capture, model, and serve critical business data&mdash;then implement it in production. You&rsquo;ll make architectural decisions around storage formats, compute patterns, and SLAs that balance cost, scalability, and consistency.
 </li>
 <li>
 Build mission-critical pipelines. Develop and operate batch data workflows that process high-volume events related to notifications with tight guarantees for latency, completeness, and accuracy.
 </li>
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 Design and implement canonical models. Create domain-oriented data models that serve as the source of truth for analytics, ML, and production applications. Establish and enforce modeling standards, ownership boundaries, and data contracts across teams.
 </li>
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 Enforce data quality at scale. Build tests, lineage, monitoring, and reconciliation systems that make every dataset observable and every anomaly actionable.
 </li>
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 Automate operational workflows. Partner with business systems and platform teams to eliminate manual data handoffs and reconcile data across services, warehouses, and external systems.
 </li>
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 Enable insights and experimentation. Support analytics, ML, and product engineering teams by exposing high-quality, self-healing, maintainable data assets.
 
 
 </li>
 </ul>
 
 We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our New York, Seattle, Los Angeles, and San Francisco hubs.
 
 
 
 
 👋 You
 
 
 
 Curious about who thrives at Whatnot? We&rsquo;ve found that embodying a low ego, growth mindset, and high-impact drive goes a long way here.
 
 
 As our next Data Engineer, you bring deep experience designing reliable, scalable data systems and are excited to take true ownership of a complex product domain.
 
 
 You should have 5+ years of experience in the data or software engineering domain, plus:
 
 
 <ul>
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 Strong experience building and maintaining production-grade data pipelines with clear SLAs, monitoring, and alerting
 </li>
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 Deep expertise in SQL, including complex model graphs, dependency management, and performance optimization
 </li>
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 Are comfortable writing production-grade code in Python or SQL languages, and integrating with CI/CD and infrastructure-as-code workflows.
 </li>
 <li>
 Have deep hands-on expertise with modern data tooling across ingestion (e.g., Kafka, Debezium), transformation (dbt, Spark, Flink), orchestration (Dagster, Airflow), and observability (Monte Carlo, Great Expectations).
 </li>
 <li>
 Have operated cloud data warehouses such as Snowflake, BigQuery, or Redshift, including schema design, cost optimization, and workload tuning.
 </li>
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 Proven track record working with large-scale datasets (hundreds of millions of rows per day)
 </li>
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 Experience designing data models that balance analytics, ML, and operational debugging use cases
 </li>
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 Strong systems thinking &mdash; you consider correctness, latency, cost, and maintainability together
 </li>
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 Self-starter ethic, thriving under a high level of autonomy
 </li>
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 Exceptional interpersonal and communication skills in cross-functional environments
 
 
 </li>
 </ul>
 
 💰Compensation For Full-Time (Salary)
 
 
 
 
 US based applicants:
 
 $195,000/year to $230,000/year + benefits + equity.
 
 
 The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity.
 
 
 
 🎁 Benefits
 
 
 
 <ul>
 <li>
 Generous Holiday and Time off Policy
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 Health Insurance options including Medical, Dental, Vision
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 Work From Home Support
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 Home office setup allowance
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 Monthly allowance for cell phone and internet
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 </ul>
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 Care benefits
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 <li>
 Monthly allowance for wellness
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 Annual allowance towards Childcare
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 Lifetime benefit for family planning, such as adoption or fertility expenses
 </li>
 </ul>
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 Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
 </li>
 <li>
 Monthly allowance to dogfood the app
 </li>
 <ul>
 <li>
 All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!).
 </li>
 </ul>
 <li>
 Parental Leave
 </li>
 <ul>
 <li>
 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.
 </li>
 </ul>
 </ul>
 
 
 💛 EOE
 
 
 
 
 Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.
 
 
 Compensation Range: $180K - $260K
 
 
</div>

Data Engineer, Notifications

reddit

<div><div><div><div><div><div><div><div>Reddit is a community of communities. It's built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet's largest sources of information. For more information, visit www.redditinc.com.</div>
</div>
</div></div></div></div></div>Team overview:

The Engagement Modeling Team at Reddit focuses on building machine learning models to drive on-platform user engagement with diverse media and content, with a focus on predictive modeling to improve interactions of click-throughs and video view-throughs. This role offers a unique opportunity to shape and scale Reddit's Ads prediction models, in alignment with our product goals and driving SoTA modeling advancement.

This role is well-suited for a leader with deep machine learning expertise, strategic vision, and a collaborative mindset to engage with both technical and cross-functional stakeholders.

We're a remote-friendly company, and this position is open to candidates anywhere in the U.S.

Responsibilities:
<ul>
<li>Set Technical Vision and Strategy: Define and execute a roadmap for engagement modeling, balancing innovative modeling approaches with business objectives.</li>
<li>Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.</li>
<li>Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.</li>
<li>Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.</li>
<li>Innovate in ML Architecture: Implement and optimize model architectures tailored to engagement prediction, leveraging deep learning and advanced ML techniques.</li>
</ul>
Candidate Profile:

The EM will lead a diverse, high-impact team and will need to navigate and foster collaboration with various teams such as PM, DS, and engineering functions within Ads. Ideal candidates will have:
<ul>
<li>People Management Experience: Prior experience managing engineering teams with a strong emphasis on technical mentorship and team growth.</li>
<li>Set Technical Vision and Strategy: Ability to plan and execute a long-term technical strategy aligned with business objectives. Define and execute a roadmap for conversion modeling, balancing innovative modeling approaches with business objectives.</li>
<li>Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.</li>
<li>Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.</li>
<li>Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.</li>
<li>Innovate in ML Architecture: Implement and optimize model architectures tailored to conversion prediction, leveraging deep learning and advanced ML techniques.</li>
</ul>
Required qualifications:
<ul>
<li>At least 2+ of experience building and managing high-performing machine learning teams, ideally in the Ads domain. Will consider tech lead experience as well</li>
<li>Deep ML Expertise: Deep hands-on experience working with machine learning models and deploying them in large-scale production systems. Proven ability in training, evaluating, and deploying large-scale models.</li>
<li>End-to-End ML Lifecycle Experience: Proven ability in training, evaluating, and deploying large-scale models.</li>
<li>4+ years of hands-on experience with TensorFlow or PyTorch.</li>
<li>Strategic Thinking: Ability to develop and communicate a clear, compelling technical strategy that supports broader company objectives and addresses the needs of internal customers.</li>
<li>Impact-Driven Mindset: Passion for developing scalable, well-designed, and responsible AI solutions that drive business value.</li>
<li>Exceptional Communication &amp; Collaboration: Strong interpersonal skills and a collaborative mindset, with the ability to effectively communicate complex technical topics to diverse audiences and build strong relationships with cross-functional partners</li>
</ul><ul><li>Experience with Ads or Engagement Modeling is a plus.</li>
</ul>
Perks and Benefits:
<ul>
<li>100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)</li>
<li>Competitive salary and equity options</li>
<li>Comprehensive health benefits (medical, dental, vision) &amp; workplace perks (home office set up stipend etc)</li>
<li>Generous 401k matching</li>
<li>Flexible vacation policy</li>
<li>Paid parental leave (4+ months)</li>
<li>Family planning support</li>
<li>Paid volunteer time off</li>
</ul>
#LI-AS1<div> 
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.</div></div>

Machine Learning Engineering Manager - Ads Engagement Modeling

Hellyeah AI

AI Engineer - Learn Engine: Intelligence &amp; OptimizationLocation: San Francisco HQ; ShanghaiAddress: San Francisco, CaliforniaEmployment Type: Full timeLocation Type: HybridDepartment: EngineeringCompensation: San Francisco $200K - $1M + 0.5% - 3% equityBuild the brain of an autonomous growth OS. The system you create will manage millions in ad spend and get measurably smarter with every dollar. This is the moat: every competitor has humans optimizing campaigns manually. You are building the intelligence layer that compounds. The Platform engineer creates the tools; you create the decisions. Together you build something nobody else has.Must Have- Has built recommendation, optimization, or decision systems where outputs improve future inputs.- Strong statistical reasoning and experimentation judgment under noisy real-world data.- Strong LLM orchestration or agent-system experience for reasoning over campaign context.- Can design optimization policies, scoring systems, or automated recommendation loops.- AI-first development workflow and ability to ship production systems quickly.Nice to Have- Ad-tech optimization patterns: bid management, budget allocation, ROAS optimization.- Reinforcement learning experience.- Hyperparameter optimization experience.- Model fine-tuning experience.- Experience building agent-driven automation where LLM agents take actions.- Background in growth engineering, performance marketing, or data science.- Experience with Mastra or similar agent orchestration framework.What You Will OwnOwn the intelligence and optimization layer of Learn Engine. Build recommendation engines for bid changes, budget reallocation, pause/boost decisions, and postback optimization. Turn SSOT campaign data into high-quality optimization guidance and closed-loop decision systems. Define how the system learns from outcomes and continuously improves campaign strategy over time. This role owns decision quality, optimization policy, and learning loops, not platform plumbing or simulator infrastructure.Pay: $200,000.00 - $1,000,000.00 per yearWork Location: In person

AI Engineer - Learn Engine: Intelligence & Optimization

Notion

<div>
 Who We Are
 
 
 Notion is the collaborative AI workspace where teams and agents think together. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion.
 
 
 Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn&rsquo;t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business&rsquo;s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life&rsquo;s work.
 
 
 
 About The Role
 
 
 
 As an engineer at Notion, you&rsquo;ll help shape core user experiences and accelerate how people discover value in Notion. You'll tackle meaningful challenges with increasing autonomy, crafting code that millions of users will experience. You'll take ownership of projects that matter, make critical technical decisions, and contribute your unique perspective to our product vision. Working alongside passionate experts across design, product, and data, you'll help shape the future of how people work.
 
 
 We're looking for an New Grad AI Engineer to join as a strategic partner in shaping Notion's AI vision. You'll work on cutting-edge AI-powered features, leveraging LLMs, embeddings, and other AI technologies to make Notion more intelligent and capable.
 
 
 
 Role
 
 
 
 This role may be aligned to one of multiple AI-focused teams at Notion. Depending on team match and business needs, you could work on:
 
 
 <ul>
 <li>
 AI product engineering: building model-powered features end-to-end (UX, APIs, retrieval, orchestration, quality, and reliability)
 </li>
 <li>
 Model &amp; systems engineering: improving model integration and performance (latency, cost, safety, robustness) and building the infrastructure that supports model serving and experimentation
 </li>
 <li>
 Evaluation &amp; quality (evals): creating evaluation frameworks and automated/ human-in-the-loop testing to measure and improve model and product quality
 
 
 </li>
 </ul>
 What You&rsquo;ll Achieve
 
 
 <ul>
 <li>
 Partner with your team to prototype and ship an AI-powered product improvement
 </li>
 <li>
 Own a scoped productionization project: integrate a new model/technique into an existing workflow, add monitoring + guardrails, or improve latency/cost/reliability.
 </li>
 <li>
 Contribute to evals and iteration loops: build or extend an evaluation set, run experiments, analyze results, and translate learnings into product or system changes.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Pursuing a bachelor's or master&rsquo;s degree in computer science, engineering, or another related field. Must be able to start full time prior to July 27, 2026.
 </li>
 <li>
 Previous internship experience.
 </li>
 <li>
 Working towards a proficiency of one or more programming languages such as Typescript, React, Python, etc.
 
 
 </li>
 </ul>
 Skills You'll Need To Bring
 
 
 <ul>
 <li>
 Expertise building and prototyping: You&rsquo;re excited to build and iterate quickly, and you&rsquo;ve started exploring AI/ML through coursework, projects, internships, or hackathons. You&rsquo;re comfortable learning how different parts of a product fit together (UI, APIs, data), have some familiarity with relational databases like Postgres or MySQL, and can take an idea from prototype to a working feature with guidance.
 </li>
 <li>
 Problem-solving: You&rsquo;re curious and methodical. You ask good questions, break down ambiguous problems into smaller pieces, and iterate with feedback from teammates. You think about how what you build will impact users and the business.
 </li>
 <li>
 Communication and collaboration: You communicate clearly in writing and in meetings, and you&rsquo;re comfortable learning in public&mdash;sharing early work, asking for help, and incorporating feedback. You enjoy partnering with engineers and cross-functional teammates (product, design, data).
 </li>
 <li>
 Impact and user focus: You care about building the right thing, not just building it quickly. You prioritize work based on user needs and outcomes, and you&rsquo;re mindful that features at Notion can reach millions of people.
 
 
 </li>
 </ul>
 Nice To Haves
 
 
 <ul>
 <li>
 You have experience with any part of our technology stack: React, TypeScript, Node.js, Postgres, etc.
 </li>
 <li>
 You&rsquo;re a builder who finds joy in building software solutions for yourself or others
 </li>
 <li>
 You care about the interaction between technology and society, the ways in which they inform each other, and our responsibility as technologists to be conscious of that relationship.
 </li>
 <li>
 You've heard of computing pioneers like Ada Lovelace, Douglas Engelbart, Alan Kay, and others&mdash;and understand why we're big fans of their work.
 
 
 </li>
 </ul>
 Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role&rsquo;s scope and complexity, and the candidate&rsquo;s experience and expertise, and may vary from the range provided below. For roles based in San Francisco and New York, the estimated base salary range for this role is $126,000-$146,000.
 
 
 By clicking &ldquo;Submit Application&rdquo;, I understand and agree that Notion and its affiliates and subsidiaries will collect and process my information in accordance with Notion&rsquo;s Global Recruiting Privacy Policy.
 
 
 A Note on AI
 
 
 You don&rsquo;t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement &mdash; when that&rsquo;s the case, we'll say so explicitly in the qualifications. People who thrive here don&rsquo;t treat AI as a novelty. They use it to think better, and make their work easier for others to build on.
 
 
 Equal Opportunity &amp; Accommodations
 
 
 We hire talented people from a wide range of backgrounds. If you&rsquo;re excited about this role but don&rsquo;t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know.
 
 
 Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.
 
 
</div>

Software Engineer, New Grad (AI)

CoreWeave

<div><div><div><div><div><div><div>CoreWeave is The Essential Cloud for AI&trade;. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com.</div>
</div>
</div></div></div></div>What You'll Do:

The Customer Experience (CX) Organization at CoreWeave is dedicated to ensuring every client running AI workloads at scale has a seamless, reliable, and high-performance experience. This team supports the infrastructure that powers the AI revolution&mdash;working across data centers, hardware systems, and customer workloads to maintain the integrity of our cloud platform. The CX organization aligns closely with the internal and customer engineering teams, offering valuable insights from the field and having the chance to contribute to the CoreWeave product roadmap and development.

About the role:

As a Specialist Field Engineer at CoreWeave, you will play a vital and dynamic role. You will have the opportunity to demonstrate thought leadership and engage hands-on throughout our customers' entire lifecycle. From establishing their Kubernetes environment to developing proofs of concept, onboarding, and optimizing workloads, you will lead innovation at every turn. If you're driven by innovation, thrilled by the possibilities of what specialized compute can enable, and eager to be part of a team that's shaping the future, then CoreWeave is the place for you. Join us and let's embark on this adventure together!

In this role, you will:
<ul>
<li>Serve as the primary technical point of contact for customers, establishing strong technical relationships and ensuring their success with CoreWeave's cloud infrastructure offerings, focusing on securing Kubernetes workloads within cloud infrastructure environments</li>
<li>Collaborate closely with customers to understand their unique business needs and create, prototype, and deploy tailored solutions that align with their requirements.</li>
<li>Lead proof of concept initiatives to showcase the value and viability of CoreWeave's solutions within specific environments.</li>
<li>Drive technical leadership and direction during customer meetings, presentations, and workshops, addressing any technical queries or concerns that arise.</li>
<li>Act as a virtual member of CoreWeave's Security product and engineering teams, identifying opportunities for product enhancement and collaborating with engineers to implement your suggestions.</li>
<li>Offer valuable insights on product features, functionality, and performance, contributing regularly to discussions about product strategy and architecture.</li>
<li>Conduct periodic technical reviews and assessments of customer workloads, pinpointing opportunities for workload optimization and suggesting suitable solutions.</li>
<li>Stay informed of the latest developments and trends in Kubernetes, cloud computing and infrastructure, sharing your thought leadership with customers and internal stakeholders.</li>
<li>Lead the prototyping and initiation of research and development efforts for emerging products and solutions, delivering prototypes and key insights for internal consumption.</li>
<li>Represent CoreWeave at conferences and industry events, with occasional travel as required.</li>
</ul>
Who You Are:
<ul>
<li>B.S. in Computer Science or a related technical discipline, or equivalent experience</li>
<li>7+ years of proven experience as a Solutions Architect, engineer, researcher or technical account manager in cloud infrastructure focusing on building distributed systems or HPC/cloud services, with an expertise focused on securing Kubernetes workloads</li>
<li>Fluency in cloud computing concepts, architecture, and technologies with hands-on experience in designing and implementing cloud solutions</li>
<li>Proven track record with building customer relationships, communicating clearly and the ability to break down complex technical concepts to both technical and non-technical audiences</li>
<li>Familiar with NVIDIA GPUs typically used in AI/ML applications and associated technologies including networking</li>
<li>Deep understanding of administrating Kubernetes clusters including controls such as RBAC, admission controllers, container security, etc.</li>
<li>Proven experience describing security concepts clearly, along with best practices and an understanding of the security tooling landscape in Kubernetes environments</li>
</ul>
Preferred:
<ul>
<li>Code contributions to open-source inference frameworks</li>
<li>Experience with scripting and automation related to securing Kubernetes environments</li>
<li>Experience with building solutions across multi-cloud environments</li>
<li>Client or customer-facing publications/talks on latency, optimization, or advanced model-server architectures</li>
</ul>
Wondering if you're a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams &ndash; even if you aren't a 100% skill or experience match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk.
<ul>
<li>You love to help solve challenging technical problems</li>
<li>You're curious about the latest and greatest technologies in the AI space</li>
<li>You're an expert in managing conflict and achieving mutually beneficial technical outcomes</li>
</ul>
Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We're in an exciting stage of hyper-growth that you will not want to miss out on. We're not afraid of a little chaos, and we're constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:
<ul>
<li>Be Curious at Your Core</li>
<li>Act Like an Owner</li>
<li>Empower Employees</li>
<li>Deliver Best-in-Class Client Experiences</li>
<li>Achieve More Together</li>
</ul>
We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!
The base salary range for this role is $165,000 to $220,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).<div>
What We Offer

The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.

In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings; for roles in other locations, benefits vary and are shared during the hiring process. These include:
<ul>
<li>Medical, dental, and vision insurance - 100% paid for by CoreWeave</li>
<li>Company-paid Life Insurance</li>
<li>Voluntary supplemental life insurance</li>
<li>Short and long-term disability insurance</li>
<li>Flexible Spending Account</li>
<li>Health Savings Account</li>
<li>Tuition Reimbursement</li>
<li>Ability to Participate in Employee Stock Purchase Program (ESPP)</li>
<li>Mental Wellness Benefits through Spring Health</li>
<li>Family-Forming support provided by Carrot</li>
<li>Paid Parental Leave</li>
<li>Flexible, full-service childcare support with Kinside</li>
<li>401(k) with a generous employer match</li>
<li>Flexible PTO</li>
<li>Catered lunch each day in our office and data center locations</li>
<li>A casual work environment</li>
<li>A work culture focused on innovative disruption</li>
</ul>
California Applicants

California Consumer Privacy Act

Equal Opportunity &amp; Accommodations

CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.

As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.

Export Control Compliance

This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. &sect; 1157, or (iv) asylee under 8 U.S.C. &sect; 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.</div></div>

Senior Specialist Field Engineer - Security

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