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.

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.

AI Scientist

The Role

This AI Scientist position will drive the development and optimization of Aizen's generative AI-based peptide drug discovery platform, DaX™. You will be responsible for incorporating state-of-the-art neural network architectures and high-performance computational biology software to improve the accuracy and throughput of our drug discovery efforts. Your work will be critical in translating experimental data and scientific insights into scalable, robust models.

Our Ideal Candidate

You are passionate about the company’s mission and a self-starter with an inextinguishable fire to compete and succeed. You thrive in an environment that requires crisp judgment, pragmatic decision-making, rapid course-corrections, and comfort with market ambiguity. You discharge your duties within a culture of mutual team respect, high performance, humility, and humor.

Key Responsibilities

• Incorporate state-of-the-art neural network architectures and training methods to improve accuracy and throughput of DaX™, Aizen's generative AI-based peptide drug discovery platform.
• Develop, test, deploy, and maintain high-performance computational biology software according to the needs and feedback of experimentalists at Aizen.
• Orchestrate new and existing Aizen software tools into scalable, highly-available, and easy-to-use cloud pipelines.
• Work closely with experimental scientists at Aizen to manage storage and access of Aizen's experimental data.

Candidate Skills and Experience

• Ph.D. and/or postdoctoral studies in Computer Science, Computational Biology, Bioinformatics, or a related field.
• Deep, demonstrated expertise in advanced Generative Models (e.g., Flow Matching, Diffusion Models) for de novo design in discrete and continuous spaces.
• Experience integrating and leveraging data from physics-based simulations (e.g., Molecular Dynamics) into machine learning models.
• Experience collecting, sanitizing, and training on biological property datasets, with a preference for prior experience with peptides.
• Proficiency with Python, shell scripting, and a high-performance compiled language.
• Entrepreneurial spirit, self-starter with proper balance of scientific creativity and disciplined execution.
• Preferred: Experience designing and maintaining high-availability cloud architectures for hosting high-performance biological analysis software.
• Preferred: Experience in chemical featurization, representation, and model application for peptide chemistry, non-canonical amino acids (NCAAs), and complex peptide macrocycles.
• Preferred: Experience in protein/peptide folding dynamics, protein structural analysis, and resultant data integration to improve computation/design.

About Aizen

Aizen is an AI-driven biotechnology company pioneering Mirror Peptides, a novel class of biologic medicines. Mirror Peptides are synthetic, fully D-amino acid peptides that represent a vast, unexplored therapeutic chemical space. Backed by life science venture capital and based in the biotech hub of San Diego, CA.

Location & Compensation

• Reporting: Principal AI Scientist
• Location: This position offers fully remote work with monthly/quarterly trips to company facilities in California.
• Compensation: Competitive base salary, stock options, and a benefits package including medical coverage.

Contact

To apply, please contact us at jobs@aizentx.com.

An equal opportunity employer V1

Looking to study for a PhD?

I am looking for new students to join my ML group at the University of New South Wales, Sydney, Australia. The UNSW is ranked #19 in the QS Ranking 2025.

1. To succeed, you need an outstanding publication record, e.g., one or more first-author papers in NeurIPS, ICML, ICLR, CVPR, AAAI, ICCV, ECCV, IJCAI, SIG KDD, etc. You also need a high GPA from a very good uni (high in rankings). Patents, professional experience and non-first authors in the mix also help.

2. Topics include (non-exhaustively): (provable) machine UNlearning and model adaptation, MMLM and improving modality alignment, super-alignment, self-supervised physics-grounded models, safety in ML protein representations (also safety in general models), structured/technical diagrams understanding, structural diffusion models, next gen architectures beyond transformers, billion nodes/edges large scale graph learning.

3. Opportunities: CSC scholarships (due 16 Jan 2026) with uni. top-up, international scholarship rounds (due 17 April 2026), for exceptional candidates direct funding may be available (flex start)

Contact: Assoc. Prof. Piotr Koniusz: p.koniusz@unsw.edu.au See: www.koniusz.com (if you are attending NeurIPS, you can try reach me for an informal chat)

ABOUT POOLSIDE

In this decade, the world will create Artificial General Intelligence. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will define the winners. These companies will move faster than anyone else. They will attract the world's most capable talent. They will be on the forefront of applied research, engineering, infrastructure and deployment at scale. They will continue to scale their training to larger & more capable models. They will be given the right to raise large amounts of capital along their journey to enable this. They will create powerful economic engines. They will obsess over the success of their users and customers.

poolside exists to be this company - to build a world where AI will be the engine behind economically valuable work and scientific progress.

ABOUT OUR TEAM

We are a remote-first team that sits across Europe and North America and comes together once a month in-person for 3 days and for longer offsites twice a year.

Our R&D and production teams are a combination of more research and more engineering-oriented profiles, however, everyone deeply cares about the quality of the systems we build and has a strong underlying knowledge of software development. We believe that good engineering leads to faster development iterations, which allows us to compound our efforts.

ABOUT THE ROLE

You would be working on our pre-training team focused on building out our distributed training of Large Language Models and major architecture changes. This is a hands-on role where you'll be both programming and implementing LLM architectures (dense & sparse) and distributed training code all the way from data to tensor parallelism, while researching potential optimizations (from basic operations to communication) and new architectures & distributed training strategies. You will have access to thousands of GPUs in this team.

YOUR MISSION

To train the best foundational models for source code generation in the world in minimum time and with maximum hardware utilization.

RESPONSIBILITIES

• Follow the latest research on LLMs and source code generation. Propose and evaluate innovations, both in the quality and the efficiency of the training
• Do LLM-Ops: babysitting and analyzing the experiments, iterating
• Write high-quality Python, Cython, C/C++, Triton, CUDA code
• Work in the team: plan future steps, discuss, and always stay in touch

SKILLS & EXPERIENCE

• Experience with Large Language Models (LLM)
• Deep knowledge of Transformers is a must
• Knowledge/Experience with cutting-edge training tricks
• Knowledge/Experience of distributed training
• Trained LLMs from scratch
• Coded LLMs from scratch
• Knowledge of deep learning fundamentals
• Strong machine learning and engineering background
• Research experience
• Author of scientific papers on any of the topics: applied deep learning, LLMs, source code generation, etc. - is a nice to have
• Can freely discuss the latest papers and descend to fine details
• Is reasonably opinionated
• Programming experience: Linux, Strong algorithmic skills, Python with PyTorch or Jax, C/C++, CUDA, Triton
• Use modern tools and are always looking to improve
• Strong critical thinking and ability to question code quality policies when applicable
• Prior experience in non-ML programming, especially not in Python - is a nice to have

PROCESS

• Intro call with one of our Founding Engineers
• Technical Interview(s) with one of our Founding Engineers
• Team fit call with the People team
• Final interview with Eiso, our CTO & Co-Founder

BENEFITS

• Fully remote work & flexible hours
• 37 days/year of vacation & holidays
• Health insurance allowance for you and dependents
• Company-provided equipment
• Wellbeing, always-be-learning and home office allowances
• Frequent team get togethers
• Great diverse & inclusive people-first culture

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.

Bala Cynwyd (Philadelphia Area), Pennsylvania United States & New York, New York United States

Overview

Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and markets.

As a Machine Learning Intern at Susquehanna, you’ll work on high-impact projects that closely reflect the challenges and workflows of our full-time research team. You’ll apply your technical expertise in machine learning and data science to real-world financial problems, while developing a deep understanding of how machine learning integrates into Susquehanna’s research and trading systems. You will leverage vast and diverse datasets and apply cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling to strategic execution.

What You Can Expect

 • Conduct research and develop ML models to identify patterns in noisy, non-stationary data

 • Work side-by-side with our Machine Learning team on real, impactful problems in quantitative trading and finance, bridging the gap between cutting-edge ML research and practical implementation

 • Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches

 • Design and run experiments using the latest ML tools and frameworks

 • One-on-one mentorship from experienced researchers and technologists

 • Participate in a comprehensive education program with deep dives into Susquehanna’s ML, quant, and trading practices

 • Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior

 • Explore various aspects of machine learning in quantitative finance from alpha generation and signal processing to model deployment and risk-aware decision making

What we're looking for

 • Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a closely related field

 • Proven experience applying machine learning techniques in a professional or academic setting

 • Strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR

 • Hands-on experience with machine learning frameworks, including PyTorch and TensorFlow

 • Deep interest in solving complex problems and a drive to innovate in a fast-paced, competitive environment

Why Join Us?

 • Work with a world-class team of researchers and technologists

 • Access to unparalleled financial data and computing resources

 • Opportunity to make a direct impact on trading performance

 • Collaborative, intellectually stimulating environment with global reach

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

Location Beijing CHINA

Description

1. Mission and Positioning： The Beijing Academy of Artificial Intelligence (BAAI) invites strategic scientists from the global AI community to join us as a Chief Scientist. In this role, you will chart the future course for the Academy's and the discipline's development, guiding our exploration of the AI frontier and establishing yourself as an academic leader shaping the global AI landscape.

2. Qualifications：

3. A distinguished research background at world-leading universities, national-level research institutions, or corporate R&D labs of global renown.
4. A proven record of publishing a series of highly influential research findings in top-tier AI journals and conferences, with the ability to define the frontiers of the discipline.

5. Visionary strategic insight and exceptional academic leadership, with a demonstrated capacity to identify and tackle the field's most fundamental challenges.

6. We Offer：

7. A globally competitive compensation package and comprehensive benefits (customized arrangements are available).
8. Full academic autonomy supported by substantial, long-term research funding and access to world-class computing infrastructure.
9. Full support to assemble and lead an elite research team from around the world.
10. Expedited Beijing residency registration for eligible candidates and access to a premium medical "Green Channel" for senior talent.

11. Customized supplementary health insurance plans for experts and their immediate family members.

12. How to Apply： Please send your detailed CV, representative publications, and a brief research vision statement to: [recruiting@baai.ac.cn] Use the email subject line: "Chief Scientist Application - [Name] - [Primary Research Field]"

Johns Hopkins University

The Department of Biostatistics is seeking outstanding colleagues to join our tenure track faculty at the assistant professor level. We seek candidates to strengthen us in advancing statistical and data science, making discoveries to improve health, and providing an innovative biostatistics education. Responsibilities include methodological and collaborative research, teaching, and mentorship of graduate students. We are particularly interested in candidates with expertise in biostatistics, data science, and AI and a passion for public health. Johns Hopkins University has recently made a transformative investment launching a Data Science and AI institute that will serve the hub for interdisciplinary data collaborations with faculties and students from across Johns Hopkins and will build the nation’s foremost destination for emerging applications, opportunities and challenges presented by data science, machine learning and AI. We anticipate the individual hired into this position will have strong links with the Data Science and AI Institute.