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.

USA – Austin, San Jose

Overview

Arm technology is becoming the platform of choice for compute and AI. The Arm System Engineering team’s mission is to architect, design, and develop scalable compute platforms. Our capabilities span hardware and software, interconnects, system management, storage, physical infrastructure, and performance engineering. We lead customer collaborations, technology evaluation, end-to-end architecture, network strategy, and rigorous performance analysis. The team is developing advanced technologies to deliver innovative, high-performance solutions to power high-performance AI/ML applications. Job Overview:

The Performance Engineering Team plays a central role in enabling and optimizing performance across Arm’s compute systems. The team’s charter is to model, measure, and optimize performance at scale, ensuring Arm-based solutions achieve world-class efficiency and throughput for diverse workloads—from AI training and inference to scientific and data-intensive computing Responsibilities:

The System Engineering team is looking for AI/ML, Software, and Performance Engineers that will be responsible for application performance and benchmarking to enable ARM’s customer base in the datacenter space. Ownership of system performance for AI workloads and related software tools Collaboration with platform, interconnect, software, storage and system management engineering teams to perform system-scale testing and validation Oversight of support functions such as programs management, quality, and DevOps. Core Hiring Focus:

We are expanding our Performance Engineering team and seeking individuals passionate about pushing the limits of AI performance on systems built around Arm platforms. Key areas of recruitment include: Performance Modeling Engineers: Develop analytical and simulation-based performance models for large-scale AI/ML systems. AI and ML Performance Engineers: Optimize LLM and generative model training/inference workloads on Arm-based systems. Systems and Networking Engineers: Advance interconnect and collective communication performance across multi-node clusters, reduce system jitter. Storage Performance Engineers: Design and optimize parallel file system and near computer storage solutions for AI/ML workloads. Resilience and Reliability Engineers: Innovate in checkpointing, recovery, and resilient distributed training. Benchmarking Specialists: Lead evaluation and comparison of Arm-based performance using industry-standard metrics. In Return:

Be part of a groundbreaking team influencing the next generation of Arm systems for AI/ML computing! Collaborate with top engineers and vendors to develop industry-leading AI systems. Access professional growth through sophisticated project involvement and multidisciplinary teamwork. Join a company committed to diversity and inclusion, where your work matters and drives global progress!

About Kumo.ai

Kumo.ai is redefining enterprise AI with foundation models for relational data, enabling organizations to predict, optimize, and act with speed and confidence.
Our mission is simple yet ambitious: make the world’s most important data also its most useful.

At Kumo, we are committed to building cutting-edge products that are also intuitive and easy to use. Our work blends deep technical innovation with thoughtful user-centric design.

Our Culture

We foster an inclusive, collaborative culture where every individual contributes to our shared mission.
We value:

• Diversity of thought
• Open and transparent communication
• Working together to solve meaningful problems
• Serving our customers with excellence
• Building a supportive and thriving community

We’re Hiring

We are looking for ML/AI Engineers with experience in one or more of the following:

• Graph Neural Networks (GNNs)
• Graph Transformers
• Agentic Frameworks
• Applied Machine Learning

If you're excited about building the next generation of AI for relational data, we’d love to talk.

Remote - Americas

Machine Learning Engineer - HSTU

Join Shopify's innovative team as we work on the development and implementation of state of the art HSTU models (Hierarchical Sequential Transduction Unit) to recommend the best growth drivers and action for merchants and buyers. You'll play a pivotal role in solving high-impact data problems that directly improve merchant success and consumer experience.  As a Machine Learning Engineering (MLE) lead or individual contributor, you'll be at the forefront of building AI solutions that anticipate both merchant needs and personalization for 100M+ shoppers. 

Key Responsibilities:

• Develop and deploy Generative AI, natural language processing, and HSTU-based recommendation models at scale 
• Design and implement scalable AI/ML system architectures supporting models 
• Build sophisticated inference pipelines that process billions of events and deliver real-time recommendations 
• Implement data pipelines for model training, fine-tuning, and evaluation across diverse data sources (merchant events, consumer interactions, payment sequences) 
• Experiment with novel architectures 
• Optimize for production through advanced techniques like negative sampling, ANN search, and distributed GPU training 
• Collaborate cross-functionally with product teams, data scientists, and infrastructure engineers to deliver measurable business impact 
• Communicate effectively with both technical and non-technical audiences, translating complex ML concepts into actionable insights

Qualifications:

• Mastery in recommendation systems, Gen AI or LLMs 
• End-to-end experience in training, evaluating, testing, and deploying machine learning products at scale.
• Experience in building data pipelines and driving ETL design decisions using disparate data sources.
• Proficiency in Python, shell scripting, streaming and batch data pipelines, vector databases, DBT, BigQuery, BigTable, or equivalent, and orchestration tools.

• Experience with running machine learning in parallel environments (e.g., distributed clusters, GPU optimization).

• This role may require on-call work.*

At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you’re ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a pair programming interview, using your own IDE.

This role may require on-call work.



Ready to redefine e-commerce through AI innovation? Join the team that’s making commerce better for everyone.

Palo Alto

Our formula for success is to hire exceptional people, encourage their ideas and reward their results.

As an AI Research Intern, you will be an integral member of a team of experienced technologists, quantitative researchers, and traders. You will collaborate closely with other researchers to solve challenging AI and machine learning problems. Your projects will vary depending on priorities at the start of your employment and could include solving forecasting problems or developing large language models (LLMs). We are looking for individuals eager to learn new AI technologies, create innovative solutions, and choose the right tools to directly impact our business. You will be surrounded by cutting-edge technology, given immediate responsibility, mentored by industry-leading experts, and attend a robust training program to ensure your success at DRW.

How you will make an impact… Algorithm Development: Creating and testing new AI models and algorithms to solve specific problems or improve existing methods. Data Engineering: Building data pipelines for model training and evaluation, including data collection, cleaning, preprocessing, and labeling, while contributing to better data management practices. Model Testing & Evaluation: Designing and implementing rigorous testing frameworks to assess model performance and identify areas for improvement. Collaboration: Working closely with team members to establish and refine research methodologies, promoting peer reviews, testing, and thorough documentation. Research & Learning: Staying updated on the latest AI techniques and advancements, sharing insights, and actively bringing improvements to research processes.

What you bring to the team… Are pursuing a PhD in artificial intelligence, machine learning, computer science, or a related field graduating between December 2026 and June 2027. Strong foundation in AI concepts. Strong knowledge of machine learning. Solid technical and programming skills (Python, Java, GitHub). Familiarity with machine learning framework (Spark, PyTorch, etc.). Excellent analytical, problem-solving, and communication skills. Deep interest in financial markets.

Preferred Skills: Experience with NLP tasks Knowledge of TensorFlow or PyTorch. Basic understanding of MLOps principles (monitoring, versioning, model serving).

Learning Opportunities: Gain in-depth experience with cutting-edge ML/AI techniques and model deployment. Develop robust machine learning research skills, from data engineering to model evaluation, while contributing to advancements in AI methodologies and practices. Contribute to research projects with potential impact on financial decision-making and other applied domains. Engage in fostering a collaborative research culture, driving improvements in research quality, and interdisciplinary collaboration.

What to expect during the internship Meaningful projects: Each project, advised by a trader, promotes a comprehensive learning experience and provides you with real-world work experience. Community: Throughout the summer, we host a variety of educational, social and team-building activities to explore the city, foster friendships and camaraderie. Housing: DRW provides fully furnished apartments located close to the office – making your morning commute as easy as possible. Mentorship: You’ll build a professional relationship with an experienced mentor in your field. Mentors and mentees meet to discuss goals, challenges and professional development and explore the city together at our mentor outings. Education: As the trading industry continually evolves, both in terms of new products and transaction methods, the future will present us with unique opportunities and challenges. You’ll complete an options course taught by an experienced trader and participate in a technology immersion course to better understand how technology and trading intersect.

USA or International

The Renaissance Philanthropy Engineering Hub provides on-demand development technical assistance in support of grant-funded educational technology projects. Our support allows mission-driven teams to overcome hurdles and achieve their technical and impact goals. As a Full Stack Software Engineer, you will act as a full-service consultant and developer to support projects through strategy advice, technical reviews, prototyping, evaluation, and development of new product functionality.

Bala Cynwyd (Philadelphia Area), Pennsylvania United States

Overview

We’re looking for a Machine Learning Systems Engineer to strengthen the performance and scalability of our distributed training infrastructure. In this role, you'll work closely with researchers to streamline the development and execution of large-scale training runs, helping them make the most of our compute resources. You’ll contribute to building tools that make distributed training more efficient and accessible, while continuously refining system performance through careful analysis and optimization. This position is a great fit for someone who enjoys working at the intersection of distributed systems and machine learning, values high-performance code, and has an interest in supporting innovative machine learning efforts.

What You’ll Do

Collaborate with researchers to enable them to develop systems-efficient models and architectures Apply the latest techniques to our internal training runs to achieve impressive hardware efficiency for our training runs Create tooling to help researchers distribute their training jobs more effectively Profile and optimize our training runs

What we're looking for Experience with large-scale ML training pipelines and distributed training frameworks Strong software engineering skills in python Passion for diving deep into systems implementations and understanding fundamentals to improve their performance and maintainability Experience improving resource efficiency across distributed computing environments by leveraging profiling, benchmarking, and implementing system-level optimizations

Why Join Us?

Susquehanna is a global quantitative trading firm that combines deep research, cutting-edge technology, and a collaborative culture. We build most of our systems from the ground up, and innovation is at the core of everything we do. As a Machine Learning Systems Engineer, you’ll play a critical role in shaping the future of AI at Susquehanna — enabling research at scale, accelerating experimentation, and helping unlock new opportunities across the firm.

Remote - Americas

Applied Machine Learning Engineer - Gen AI/LLM 

Join Shopify's innovative team as we develop an AI Personal Shopper to transform the online shopping experience. Leveraging cutting-edge AI, including Large Language Models (LLM) and advanced machine learning algorithms, you'll play a pivotal role in delivering personalized recommendations and insightful suggestions tailored to individual preferences. Our goal is to redefine e-commerce by creating a concierge service that enhances how customers interact with Shop and Storefronts. As a Machine Learning Engineering (MLE) lead or individual contributor, you'll be at the forefront of implementing AI systems at scale, directly empowering merchants and creating tangible solutions with real-world impact.

Key Responsibilities:

• Develop and deploy Generative AI, natural language processing, and machine learning models.
• Design and produce scalable AI/ML system architectures.
• Implement data pipelines for fine-tuning LLMs.
• Solve high-impact data problems, delivering business impact through data and machine learning products.
• Prioritize and communicate effectively with both technical and non-technical audiences.

Qualifications:

• Mastery in building data products using generative AI, RLHF, and fine-tuning LLMs.
• End-to-end experience in training, evaluating, testing, and deploying machine learning products at scale.
• Experience in building data pipelines and driving ETL design decisions using disparate data sources.
• Proficiency in Python, shell scripting, streaming and batch data pipelines, vector databases, DBT, BigQuery, BigTable, or equivalent, and orchestration tools.
• Experience with running machine learning in parallel environments (e.g., distributed clusters, GPU optimization).

At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you’re ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a pair programming interview, using your own IDE.



This role may require on-call work



Ready to redefine e-commerce through AI innovation? Join the team that’s making commerce better for everyone.

London

Flow Traders is committed to leveraging the most recent advances in machine learning, computer science, and AI to generate value in the financial markets. We are looking for Quantitative Researchers to join this challenge.

As a Quantitative Researcher at Flow Traders, you are an expert in mathematics and statistics. You are passionate about translating challenging problems into equations and models, and have the ability to optimize them using cutting-edge computational techniques. You collaborate with a global team of researchers and engineers to design, build, and optimize our next generation of models and trading strategies.

Are you at the top of your quantitative, modeling, and coding game, and excited by the prospect of demonstrating these skills in competitive live markets? Then this opportunity is for you.

Faculty Positions in Electrical and Electronics Engineering – Koç University, Istanbul, Türkiye

Koç University invites exceptional candidates to apply for full-time faculty positions in Electrical and Electronics Engineering. We seek outstanding researchers in all areas of electrical and electronics engineering, including artificial intelligence, machine learning, computational neuroscience, intelligent systems, and signal processing.

Applicants should have a bold, interdisciplinary research vision capable of making transformative impacts across multiple domains. Successful candidates will leverage Koç University’s state-of-the-art research ecosystem, including the Koç University İş Bank Artificial Intelligence Research Center (KUIS AI), the Translational Medicine Research Center (KUTTAM), and the Nanofabrication and Nanocharacterization Center (n2STAR). KUIS AI provides a high-performance computation facility and scholarship support for KUIS AI graduate fellows, fostering close collaboration between faculty and students.

Koç University is a leading private, nonprofit institution in Istanbul, supported by the Vehbi Koç Foundation, with English as the medium of instruction. It hosts the highest number of ERC grant recipients in Türkiye and offers exceptional opportunities for interdisciplinary collaboration across engineering, medicine, and natural sciences. We offer competitive salaries, housing support, K–12 education assistance, private health insurance, and research startup funds.

We will be attending NeurIPS 2025 — interested candidates are welcome to reach out and schedule an informal discussion during the conference at alperdogan@ku.edu.tr.

Application materials: CV, research statement, teaching statement, and three references. Deadline: March 20, 2026 (applications reviewed on a rolling basis). Apply at: https://ee.ku.edu.tr/open-positions/faculty-positions/