New York

The D. E. Shaw group seeks exceptional software engineers with expertise in applied AI, AI agents, and agentic systems to join the firm. This role offers the chance to work directly with a variety of groups at the firm on innovative, greenfield projects that transform how teams operate—leveraging quantitative and programming skills to design, build, and deploy AI solutions that drive efficiency, enhance analytical capabilities, and accelerate decision-making across the firm.

What you’ll do day-to-day

You’ll join a dynamic team, with the potential to:

• Collaborate directly with internal groups and end users across various functions to build bespoke AI agents and applications tailored to nuanced, real-world business needs.
• Lead and contribute to greenfield AI projects, taking ownership from concept through production and helping shape internal AI strategy and adoption.
• Experiment with emerging AI tools and model capabilities, rapidly prototyping and integrating them across platforms to enhance usability, scalability, and effectiveness.
• Scale the adoption of AI tools firmwide by developing best practices, frameworks, and reusable components that drive innovation and productivity.
• Build foundational AI components, such as agent frameworks, reusable “skills,” and large-scale retrieval systems, to support AI tools and applications.
• Design, develop, and maintain shared AI infrastructure and agentic applications, ensuring firmwide data integration and enhancing software development efficiency.

Who we’re looking for

• A bachelor’s degree in any field is required, along with an extensive background in software development, and hands-on experience building and scaling AI solutions at the product, system, or company level.
• Solid understanding of AI technologies and an interest in developing advanced AI applications and frameworks.
• Demonstrated ability to thrive in technical or entrepreneurial environments, along with the capability to solve complex challenges and lead projects from inception to deployment.
• A record of strong academic or professional achievement, with analytical depth and creativity in AI-related projects.
• We welcome outstanding candidates at all experience levels who are excited to work in a collegial, collaborative, and fast-paced environment.
• The expected annual base salary for this position is USD 200,000 to USD 250,000. Our compensation and benefits package includes variable compensation in the form of a year-end bonus, guaranteed in the first year of hire, and benefits including medical and prescription drug coverage, 401(k) contribution matching, wellness reimbursement, family building benefits, and a charitable gift match program.

San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

Within the Ads Delivery team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. We are looking for a Machine Learning Engineer/Economist with a strong theoretical and data analysis background that understands market design concepts and has the engineering skills to bring them to market. We are looking for an economist who can get their hands dirty and work side by side with other engineers, to advance the efficiency of the Pinterest Marketplace. The nature of projects within this team require a deep understanding of trade-offs, founded on both economic theory and data analysis, from the ideation phase all the way to launch review.

What you’ll do:

• Build statistical models and production systems to improve marketplace design and operations for Pinners, Partners, and Pinterest.
• Tune marketplace parameters (e.g., utility function), optimize ad diversity and load, implement auctions, and model long‑term effects to reduce ad fatigue and improve advertiser outcomes.
• Define and implement experiments to understand long term Marketplace effects.
• Develop strategies to balance long and short term business objectives.
• Drive multi-functional collaboration with peers and partners across the company to improve knowledge of marketplace design and operations.
• Work across application areas such as marketplace performance analysis, advertiser churn/retention modeling, promotional bandwidth allocation, ranking/pricing/mechanism design, bidding/budgeting innovation, and anticipating second‑order effects for new ad offerings.

What we’re looking for:

• Degree in Computer Science, Machine Learning, Economics, Operations Research, Statistics or a related field.
• Industry experience in applying economics or machine learning to real products (e.g., ads auctions, pricing, marketplaces, or large‑scale recommendation/search systems).
• Knowledge in auction theory, market design, and econometrics with excellent data analysis skills.
• Strong software engineering and mathematical skills and proficiency with statistical methods.
• Experience with online experimentation and causal inference (A/B testing, long‑running experiments, or similar) in large‑scale systems.
• Practical understanding of machine learning algorithms and techniques.
• Impact‑driven, highly collaborative, and an effective communicator; prior ads or two‑sided marketplace experience strongly preferred.

Various locations available

Adobe is looking for a Machine Learning intern who will apply AI and machine learning techniques to big-data problems to help Adobe better understand, lead and optimize the experience of its customers.

By using predictive models, experimental design methods, and optimization techniques, you will be working on the research and development of exciting projects like real-time online media optimization, sales operation analytics, customer churn scoring and management, customer understanding, product recommendation and customer lifetime value prediction.

All 2026 Adobe interns will be co-located hybrid. This means that interns will work between their assigned office and home. Interns will be based in the office where their manager and/or team are located, where they will get the most support to ensure collaboration and the best employee experience. Managers and their organization will determine the frequency they need to go into the office to meet priorities.  

What You’ll Do
- Develop predictive models on large-scale datasets to address various business problems with statistical modeling, machine learning, and analytics techniques. - Develop and implement scalable, efficient, and interpretable modeling algorithms that can work with large-scale data in production systems - Collaborate with product management and engineering groups to develop new products and features.

What You Need to Succeed
- Currently enrolled full time and pursuing a Master’s or PhD degree in Computer Science, Computer Engineering; or equivalent experience required with an expected graduation date of December 2026 – June 2027 - Good understanding of statistical modeling, machine learning, deep learning, or data analytics concepts. - Proficient in one or more programming languages such as Python, Java and C - Familiar with one or more machine learning or statistical modeling tools such as R, Matlab and scikit learn - Strong analytical and quantitative problem-solving ability. - Excellent communication, relationship skills and a team player - Ability to participate in a full-time internship between May-September

New York

Machine Learning Research Engineer

The D. E. Shaw group seeks a machine learning research engineer to creatively apply their knowledge of ML and software engineering to design and build computational architectures for high-performance, large-scale knowledge discovery in financial data. In this dynamic role, the engineer will leverage cutting-edge ML research to turn new ideas into proof-of-concept implementations, solve tough low-level engineering problems, and set up infrastructure for broader, longer-term impact. This position will play a key role in improving the efficiency, scalability, and reliability of the firm’s ML efforts, and will directly impact the firm’s systematic research through ML engineering contributions, all within a collaborative and engaging environment.

What you'll do day-to-day

• Rapidly prototype, implement, and evaluate state-of-the-art machine learning techniques.
• Drive the computational agenda for ongoing and future ML projects.
• Tackle complex engineering problems across software and hardware layers, setting technical direction and anticipating architectural needs.
• Deploy ML models into real-world systems where they have direct, measurable impact on decision-making and trading.
• Create compelling proof-of-concept systems, demonstrate them internally, and collaborate with others for development.
• Partner with researchers to design and implement efficient training workflows, enabling rapid experimentation with deep learning models.

Who we're looking for

• Bachelor’s degree or higher is required.
• Proven track record of collaborating with researchers to translate ML ideas into high-performance solutions.
• Experience driving computational and architectural innovation by rapidly prototyping and demonstrating novel ML ideas within a high-performance environment.
• Interest in staying current with ML research and swift application of new techniques.
• Expertise in performance optimization, low-level engineering, GPU programming and libraries (e.g., Pytorch, JAX, CUDA, XLA, Triton, or PTX).
• Demonstrated ability to quickly solve complex computational problems, create inspiring technical demos, and transition work to broader teams.
• Proactive approach in driving agendas and anticipating engineering bottlenecks in large systems.
• Proficiency in modern ML frameworks, facility with deep learning tooling, and a solid understanding of hardware and architectural challenges.
• The expected annual base salary for this position is 250,000 to 350,000USD. Our compensation and benefits package includes substantial variable compensation in the form of a year-end bonus, guaranteed in the first year of hire, a sign-on bonus, and benefits including medical and prescription drug coverage, 401(k) contribution matching, wellness reimbursement, family building benefits, and a charitable gift match program.

Rochester, Minnesota, USA

Mayo Clinic seeks a highly motivated individual to advance the development, validation, and real-world implementation of generative AI systems for clinical decision support in Gastroenterology and Hepatology. This role bridges research and translation into clinical workflows, focusing on building trustworthy AI systems that augment human presence and put the needs of the patient first. Research Fellows will work within a multidisciplinary team of data scientists, physicians, and engineers to design novel generative agentic architectures, develop useful benchmarks, and work together with clinical teams to decrease time to diagnosis and time to treatment. Contact shung.dennis@mayo.edu if interested.

You are investigating the smartest way to interact with a browser page with an AI agent. You hammered a DOM based approach and sometimes dreamt of going visual. You tried out a pure visual approach and missed the good old DOM ways. You are now at the forefront. You know system thinking and how that reflects to a complex environment like in a browser agent platform. If that's you, please get in touch, we have a great opportunity waiting for you in San Francisco!

The role
Nebius is hiring a driven and industry-savvy Lifesciences Solutions Partner - US to join our growing Healthcare & Life Sciences (HCLS) team. As a strategic connector between the Global Head of HCLS and regional Account Executives (AEs), you will play a pivotal role in accelerating go-to-market execution, deepening client engagement, and ensuring our cloud and AI solutions align with the business, scientific, and regulatory needs of the life sciences ecosystem. You will manage strategic client relationships, identify and develop new business opportunities, and collaborate with partners - with a strong focus on the Pharmaceutical, Biotechnology, Drug Development, and Genomics segments. Your ability to understand complex scientific and business challenges, craft tailored solutions, and thrive in a fast-moving, innovation-led environment will define your success. This role combines consultative selling, industry expertise, and commercial execution, helping customers unlock the full potential of the Nebius platform.

You’re welcome to work remotely from United States.

Your responsibilities will include:
- Demonstrate a deep understanding of Nebius and the value to our customers. - Own and grow your territory: Maintain and deliver against a strategic plan for region/territory. Help AE’s qualify and prioritise opportunities through an HCLS and compliance lens. Lead and - support strategic discussions with pharma and biotech. - Client Engagement: Develop deep relationships with key stakeholders across the enterprise, positioning our AI and cloud solutions to address client-specific challenges. Act as a trusted advisor to pharma and biotech clients, driving engagement and long-term relationships. Identify opportunities to apply AI/ML, HPC, and data platforms in drug discovery and clinical operations. - Deal Support & Sales Acceleration: Partner with Account Executives to shape account strategy, value messaging, and proposal content that will secure deals to meet revenue targets. Help qualify and prioritise opportunities through an HC&LS and compliance lens. Support complex deal cycles where domain credibility and regulatory insight are critical. - Solution Selling: Demonstrate the value of AI and cloud solutions through consultative selling, product demonstrations, and presentations. - Regional Representation: Represent Nebius AI at regional and industry events, and customer meetings. - Market Knowledge: Stay updated on industry trends, emerging technologies, and competitive landscape to position our solutions effectively. - Forecast with accuracy; progress deals through the Salesforce sales process and deliver against ACV / activity targets.

We expect you to have:
- Proven Experience: 8+ years of experience in B2B sales, particularly in AI, cloud, or data infrastructure, with a clear hunter track record. - Passion and desire to work in a startup culture, directly impacting the growth of the company -Comfortable selling cloud platforms (AWS, Azure, Google Cloud), AI solutions, and related technologies. - Strong commercial acumen: value mapping, negotiation, multi‑year deals, and exec-level‑ storytelling. - High energy, enthusiasm, and evidence of consistent growth vs. quota. - CRM Proficiency: Experience with CRM tools such as Salesforce, HubSpot, or similar.

Ability to travel as needed. - It will be an added bonus if you have:
- 5 - 10 years in pharma, biotech, or life sciences, ideally in consulting, GTM, product, or pre-sales roles. - Deep understanding of drug discovery and development processes, scientific data workflows, and regulatory frameworks. - Proven ability to communicate complex scientific and technical concepts to non-technical stakeholders. - Previous experience in a high-growth, start-up environment ideally selling cloud, AI/ML or HPC solutions. - Exposure to SaaS models or cloud infrastructure sales. - Experience selling to mid-market or enterprise-level clients

San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

Pinterest helps more than half a billion users discover new ideas to help design their lives. Our users come to Pinterest to explore ideas and run more than 6 billion search queries every month. Many of these queries represent exploratory search intent and are broad, which means that the search system should be able to deeply understand this intent, and then help people explore content, personalize results, harness visual signals effectively, and show the most engaging content up front. In addition, the team also owns query refinements and modules that help Pinners narrow their search intent from broad exploratory queries, to help them narrow their results down. All of this means that Pinterest search presents a unique challenge quite unlike other search systems and the opportunity to innovate on a product that only Pinterest can build.

The Closeup Relevance team owns Closeup recommendations (a.k.a. related pins), which help pinners explore topics they are interested in and get continuous inspirations. This is the largest recommendation surface on Pinterest and we work with some of the largest datasets in the world, creating unique experiences for hundreds of millions of pinners. Our system serves billions of daily impressions and is critical for company business. We are looking for a highly motivated Staff ML engineer to work as a cross-team technical leader.

What you will do:

• Work in a cross-team environment with many talented ML engineers.
• Use a state-of-the-art recommendation tech stack and lead innovation and/or redesign of the full recommendation funnel.
• Act as a leader in ML innovations whose impact is felt across the organization.
• Work closely with other engineering teams in Pinterest to bring superior Closeup experience to our users, such as ATG, ML Platform, Closeup Product, Content Quality and Core Infrastructure.
• Develop an inspiring technical vision and ambitious but grounded strategy for the team, and deliver outstanding results.
• Provide visibility for senior leadership into the team’s global impact.
• Partner with stakeholders to expand impact across the company, including product management and data scientists.
• Mentor and grow senior engineers on the team.
• Build a culture of innovation and excellence.

What we are looking for:

• 7+ years of professional experience in Machine Learning.
• 5+ years of proposing and delivering innovations from original research or adopting cutting edge ML research.
• 3+ years of experience in leading large-scale and mature ML recommendation systems teams, in an end-to-end fashion.
• Bachelor’s/Master’s degree in a relevant field such as computer science, or equivalent experience.
• Thrives in ambiguity; skilled in defining and exploring open ended problems.
• Experience in setting and delivering technical directions at both team and organizational level.
• Expertise in machine learning modeling and infrastructure.
• Adept in statistics, backend, batch and realtime processing systems.
• Ability to drive the team roadmap end to end.
• A knack for product and impact on users of a consumer product.

San Francisco / New York / Toronto

About Ideogram Ideogram’s mission is to make world-class design accessible to everyone, multiplying human creativity. We build proprietary generative media models and AI native creative workflows, tackling unsolved challenges in graphic design. Our team includes builders with a track record of technology breakthroughs including early research in Diffusion Models, Google’s Imagen, and Imagen Video. We care about design, taste, and craft as much as research and engineering – shipping experiences that creatives actually love.

We’ve raised nearly $100M, led by Andreessen Horowitz and Index Ventures. Headquartered in Toronto with a growing team in NYC, we're scaling fast, aiming to triple over the next year. We're a flat team with a culture of high ownership, collaboration, and mentorship.

Explore Ideogram 3.0, Canvas, and Character blog posts, and try Ideogram at ideogram.ai.

The Opportunity

In this role, you'll push the frontier of visual generative models. You’ll work on large-scale pre-training for our text-to-image foundation models, shaping objectives, algorithms, data, and systems, and turn novel ideas into models that power products used by millions of users. You'll work with a creative and ambitious team of researchers and engineers who are building the future of the creative economy.

What We're Looking For

• PhD or Master’s degree in Computer Science or equivalent industry experience.

• 5+ years of experience in AI research, including training, fine-tuning, and experimenting with foundation models beyond black-box use.

• Track record of first-author publications at top-tier AI conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ECCV, ICCV, ACL, EMNLP).

• Strong proficiency in one or more deep learning frameworks (e.g., JAX, PyTorch).

• Experience communicating complex research to peers.

• Solid knowledge of programming languages and experience in developing, debugging, and optimizing beyond ML systems.

Our Culture

We’re a team of exceptionally talented, curious builders who love solving tough problems and turning bold ideas into reality. We move fast, collaborate deeply, and operate without unnecessary hierarchy, because we believe the best ideas can come from anyone.

Everyone at Ideogram rolls up their sleeves to make our products and our customers successful. We thrive on curiosity, creativity, and shared ownership. We believe that small, dedicated teams working together with trust and purpose can move faster, think bigger, and create amazing things.

Ideogram is committed to welcoming everyone — regardless of gender identity, orientation, or expression. Our mission is to create belonging and remove barriers so everyone can create boldly.

What We Offer 💸Competitive compensation and equity designed to recognize the value and impact of your contributions to Ideogram’s success. 🌴 4 weeks of vacation to recharge and explore. 🩺 Comprehensive health, vision, and dental coverage starting on day one. 💰 RRSP/401(k) with employer match up to 4% to invest in your future from the moment you join. 💻 Top-of-the-line tools and tech to fuel your creativity and productivity. 🔍 Autonomy to explore and experiment — whether you’re testing new ideas, running large-scale experiments, or diving into research, you’ll have access to compute/resources you need when there’s a clear business or creative use case. We encourage curiosity and bold thinking. 🌱 A culture of learning and growth, where curiosity is encouraged and mentorship is part of the journey. 🏡 Fully remote flexibility across North America, with regular in-person team meetups and collaboration opportunities.iption

The role We seek an experienced Senior ML Solutions Architect to support customers leveraging Nebius Token Factory's serverless inference platform for open-source LLMs across multiple modalities. In this role, you will be collaborating with clients to design and implement customized LLM-based solution and architect scalable AI applications using our served models, and working together with our backend team to improve our platform to match the clients' needs.

You’re welcome to work remotely from the United States or Canada.

Your responsibilities will include: - Design and implement LLM-based solutions using Nebius Token Factory’s inference services to drive business value and support customer goals. - Build production-ready applications leveraging our serverless LLM APIs, including multimodal models (text, vision, audio) and domain-specific models. - Provide technical expertise in prompt engineering, RAG architectures, model selection, and inference optimization. - Collaborate with product and engineering teams to surface customer feedback and shape the platform roadmap. - Guide customers in scaling from POC to production with a focus on performance, reliability, and cost efficiency.

We expect you to have: - 5+ years of experience in ML/AI systems, with at least 2 years focused on LLMs and generative AI. - Deep knowledge of the LLM ecosystem, including model architectures and fine-tuning approaches.

Hands-on experience with: - Prompt engineering and LLM pipeline development, including evaluation. - Agentic frameworks such as Langchain, Langsmith, smolagents, or equivalent. - Vector databases and RAG implementation patterns. - Deploying LLM-powered applications using APIs from OpenAI, Anthropic, or open-source models. - Strong Python programming skills. - Excellent communication skills, with the ability to clearly explain technical concepts to diverse audiences.

It will be an added bonus if you have: - Experience with inference frameworks and libraries (e.g., vLLM, SGLang, TensorRT-LLM, Transformers). - Familiarity with inference optimization techniques such as quantization, batching, caching, and routing. - Work with multimodal AI models (e.g., vision-language, speech). - Proficiency with DevOps tools (Docker, Kubernetes). - Contributions to open-source ML/AI projects.

Preferred tooling: - Programming Languages – Python - ML Frameworks and Libraries– vLLM, SGLang, TensorRT-LLM, Transformers, OpenAI/Anthropic SDKs - Frameworks for Agentic Pipelines : Langchain / Langsmith / smolagents / equivalent - API and Web Frameworks– FastAPI, Flask - MLOps and DevOps tools– Kubernetes (K8s), Docker, Git - Cloud Platforms– AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML)