AI Research Scientist

About Visceral
Visceral, newly empowered by our seed round, is reinventing market research. Our AI-native platform automates and orchestrates the process of getting new, proprietary market data with surveys and related research instruments. Led by the former Chief Strategy Officer of Capital One and a co-founder who took a leading consumer product company from inception to IPO, our team is redefining how global markets are understood. We’re seeking an AI Research Scientist to push the boundaries of machine learning and shape a platform that transforms decision-making.

• Advance AI Innovation: Develop novel machine learning models to process proprietary survey data and secondary sources, delivering predictive and actionable market insights.
• Optimize Data Pipelines: Design and implement scalable AI systems for automated surveys, interviews, and analytics, ensuring robustness and efficiency at scale.
• Collaborate with Experts: Work with engineers and industry leaders in a high-intensity, remote environment to integrate AI solutions into a market-leading platform.
• Redefine Research Paradigms: Build AI that reshapes how economies are analyzed, demanding relentless commitment to groundbreaking impact.

What You Bring

• Unrelenting Ambition: Total dedication to advancing AI for unique, high-stakes insights—no work-life balance expected in this mission-driven role.
• Technical Excellence: Deep expertise in machine learning, proficiency in Python and frameworks like TensorFlow or PyTorch, and experience with large-scale data processing; familiarity with TypeScript a plus.
• Contrarian Mindset: Ability to challenge conventional AI approaches and devise first-principles solutions that redefine research capabilities.
• Self-Direction: In this role, you will set and drive Visceral’s research agenda.

Requirements

• Ph.D. in AI/ML-related field, 5-10 years industry experience in AI/ML, or equivalent competency
• Strong mathematical foundation in AI/ML, including proficiency in areas such as linear algebra, calculus, probability, statistics, and optimization, with the ability to apply these concepts to design and analyze machine learning algorithms (e.g., deriving loss functions, optimizing neural networks, or modeling uncertainty).
• Demonstrated ability to translate mathematical principles into practical AI/ML solutions, evidenced in research publications, open-source contributions, or complex projects.

Compensation
$250-500k (commensurate with experience), with a generous equity package and insurance.

Application Prompt
Tell us: What area of AI/ML research is everyone ignoring? Why is it important?

Send your thoughts to christian@visceral.ai.

Our Graduate programs range from 10-week internships to two-year programs. Put your knowledge and skills to work innovating new products and creatively solving the problems that impact our customers and our business. It’s direct experience that will challenge you, develop you professionally and grow your network.

More information about internships here: https://www.capitalonecareers.com/graduate-programs

About Metaphysic

Metaphysic is the industry leader in developing AI technologies and machine learning research to create photorealistic content at internet scale. We were recently named TIME100 Most Influential Companies for 2023 and are focused on the ethical development of AI to support the genius of human performance. We're run by experienced founders and backed by some of the top investors in the world. We’re only just getting started in defining the next generation of content creation. Join our fast growing team and help bring our groundbreaking vision to life.

Job Description:

As a Machine Learning Research Scientist at Metaphysic, you will be instrumental in advancing the boundaries of AI-driven content creation while upholding our unwavering commitment to ethical AI practices, particularly in the domain of Hyperrealistic Content Generation.

Location: EMEA/NORAM (Remote)

Key Responsibilities:

• Cutting-Edge Research: Lead innovative research initiatives in the field of artificial intelligence, with a focus on advancing AI applications in Hyperrealistic Content Generation, including but not limited to body swaps, face swaps, and deepfakes.
• Model Development: Drive the development of state-of-the-art deep learning models for Hyperrealistic Content Generation, harnessing the power of PyTorch and other relevant tools.
• Publication and Collaboration: Contribute to the scientific community through publication in renowned conferences and journals. Collaborate closely with cross-functional teams to integrate AI technologies into various applications, such as virtual and augmented reality.
• Coding Excellence: Demonstrate your coding prowess by creating clean, efficient, and well-documented code for implementing and optimizing machine learning models. Leverage Python and data science libraries to achieve exceptional results.
• Model Evaluation: Rigorously evaluate model performance, fine-tune algorithms, and ensure the robustness and efficiency of AI applications in real-world scenarios.

Qualifications:

• Educational Background: Hold a Ph.D. or equivalent in a relevant field such as Computer Science, Machine Learning, or Data Science, accompanied by a strong research foundation.
• Fundamental Knowledge: Demonstrate a profound grasp of the fundamentals and the latest developments in relevant areas of machine learning, deeplearning, and generative AI.
• Extensive Experience: Possess over 5 years of hands-on experience in ML research and ML systems. Experience with Generative AI techniques, such as GANs, Auto Encoders, Transformers, and Diffusion Models for Image or video Generation.
• Deep Learning Mastery: Exhibit profound expertise in deep learning, encompassing a comprehensive understanding of neural network architectures, optimization techniques, and advanced training methodologies, including clip-stable diffusion models, and their role in advancing the field of Hyperrealistic Content Generation.
• Coding Proficiency: Demonstrate proficiency in Python. Possess familiarity with key data science libraries (NumPy, Matplotlib, Scikit-learn, Pandas, PyTorch or Tensorflow).
• Research Experience: Be well-versed in the field of Data Centric AI and data augmentation techniques, particularly in the time series domain.
• Innovation Enthusiasm: Display a passion for pushing the boundaries of technology, applying research to real-world scenarios, and driving creative AI solutions in Hyperrealistic Content Generation.
• Collaborative Spirit: Thrive in a multidisciplinary team environment, collaborating effectively with engineers, researchers, and developers.
• Model Interpretability: Familiarity with model interpretability techniques and tools to explain model predictions and ensure transparency.

As part of our team, you’ll enjoy:

• The hustle of a startup with the impact of a global business.
• Tremendous opportunity to join one of the best and fastest growing AI companies in the world.
• Working with an extraordinary team of smart, creative, fun and highly motivated people.
• You will be joining a fantastic culture & a team, all highly supportive, collaborative, transparent and are all very passionate about our tech and mission.
• Flexible working hours, including remote working - this role is solely remote :)

Metaphysic is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Machine Learning Engineer (Toronto / Remote)

About Agnostiq

Agnostiq is a Toronto based startup developing software with a mission to democratize access to the world’s most advanced computing resources. Agnostiq is the team behind Covalent, an open source distributed computing platform built for AI and HPC. 

Your Role 

As a Machine Learning Engineer specializing in Large Language Models (LLMs) at Agnostiq, you will play a pivotal role in developing and enhancing our AI-driven solutions. With a strong emphasis on LLMs, you will focus on the training and tuning of these models to achieve unprecedented levels of performance and efficiency. This position requires a deep understanding of machine learning principles, particularly in the context of natural language processing and generation. Due to our startup nature, the candidate must be comfortable initiating and taking on new projects independently and with limited supervision.

Key responsibilities

Required Technical & Professional Expertise

Nice-to-haves:

At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue delivering our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Participation in the program requires that you are located in the continental United States with in-person attendance at your assigned location, in accordance with Capital One’s hybrid working model.

This is a paid internship. This is a limited-time internship position, and Capital One will not sponsor a new applicant for employment authorization for this position. However, a full-timeApplied Researchrole, for which you may be considered upon completion of the internship (subject to business need, market conditions, and other factors) is eligible for employer immigration sponsorship.

Team Description:

The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business.
 

In this role, you will:

• Join Capital One for a full-time, 12 week, summer applied research experience, discovering solutions to real world, large-scale problems.

• Engage in high impact applied research with the goal of taking the latest AI developments and pushing them into the next generation of customer experiences, or contributing to publications in this field.

• Partner with a cross-functional team of applied researchers, data scientists, software engineers, machine learning engineers and product managers to test and design AI- powered products that change how customers interact with their money.

• Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data.

• Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

• Partner with leading researchers to publish papers at top academic conferences.

• Develop Professionally through networking sessions, technical deep dives and executive speaker sessions from across Capital One. 

The Ideal Candidate:

• You love the process of analyzing and creating, but also share our passion to do the right thing. You want to work on problems that will help change banking for good. 

• Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.

• Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.

• Technical. You possess a strong foundation in mathematics, deep learning theory, and the engineering required for contributing to the development of AI.

• Determined. Strengthen your field of study by applying theory to practice. Bring your ideas to life in industry. 

Basic Qualifications:

• Currently enrolled in an accredited PhD Program 
• Completed 2nd year of PhD coursework by program start date

Preferred Qualifications:

• Completed 3rd or 4th year of PhD Program
• PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields
• Programming experience in Python, PyTorch, C++, and other deep learning frameworks
• Publications in leading conferences such as KDD, ICML, NeurIPs, ICLR, ACL, NAACL and EMNLP, or ICLR 
• Focused area of researchin one of the following areas:
  • LLM Pre-training
    • PhD focus on Natural Language Processing 
    • Publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization)
    • Publications in deep learning theory 
  • LLM Finetuning
    • PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) 
    • Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance
  • Behavioral Models
    • PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series)
    • Contributions to common open source frameworks (pytorch-geometric, DGL) 
    • Proposed new methods for inference or representation learning on graphs or sequences 
  • Optimization (Training & Inference)
    • PhD focused on topics related to optimizing training of very large deep learning models 
    • Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression 
    • Deep knowledge of deep learning algorithmic and/or optimizer design 
  • Large Scale Data Preparation
    • Publications studying tokenization, data quality, dataset curation, or labeling

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

New York City: 

$250,000 - $250,000 for Applied Research Intern

San Francisco, California: 

$264,800 - $264,800 for Applied Research Intern

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.

No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Capital One’s Summer 2024 Applied Research PhD Internship Program

Students interested in the Summer 2024 Applied Research PhD Internship Program can apply here.

This is a paid internship. This is a limited-time internship position, and Capital One will not sponsor a new applicant for employment authorization for this position. However, a full-timeApplied Researchrole, for which you may be considered upon completion of the internship (subject to business need, market conditions, and other factors) is eligible for employer immigration sponsorship.

Team Description:

The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business.
 

In this role, you will:

• Join Capital One for a full-time, 12 week, summer applied research experience, discovering solutions to real world, large-scale problems.

• Engage in high impact applied research with the goal of taking the latest AI developments and pushing them into the next generation of customer experiences, or contributing to publications in this field.

• Partner with a cross-functional team of applied researchers, data scientists, software engineers, machine learning engineers and product managers to test and design AI- powered products that change how customers interact with their money.

• Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data.

• Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

• Partner with leading researchers to publish papers at top academic conferences.

• Develop Professionally through networking sessions, technical deep dives and executive speaker sessions from across Capital One. 

The Ideal Candidate:

• You love the process of analyzing and creating, but also share our passion to do the right thing. You want to work on problems that will help change banking for good. 

• Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.

• Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.

• Technical. You possess a strong foundation in mathematics, deep learning theory, and the engineering required for contributing to the development of AI.

• Determined. Strengthen your field of study by applying theory to practice. Bring your ideas to life in industry. 

Basic Qualifications:

• Currently enrolled in an accredited PhD Program 
• Completed 2nd year of PhD coursework by program start date

Preferred Qualifications:

• Completed 3rd or 4th year of PhD Program
• PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields
• Programming experience in Python, PyTorch, C++, and other deep learning frameworks
• Publications in leading conferences such as KDD, ICML, NeurIPs, ICLR, ACL, NAACL and EMNLP, or ICLR 
• Focused area of researchin one of the following areas:
  • LLM Pre-training
    • PhD focus on Natural Language Processing 
    • Publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization)
    • Publications in deep learning theory 
  • LLM Finetuning
    • PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) 
    • Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance
  • Behavioral Models
    • PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series)
    • Contributions to common open source frameworks (pytorch-geometric, DGL) 
    • Proposed new methods for inference or representation learning on graphs or sequences 
  • Optimization (Training & Inference)
    • PhD focused on topics related to optimizing training of very large deep learning models 
    • Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression 
    • Deep knowledge of deep learning algorithmic and/or optimizer design 
  • Large Scale Data Preparation
    • Publications studying tokenization, data quality, dataset curation, or labeling

Current projects they might be working on: 

• Creating a proof of concept for a personalized chatbot using GPT-3

• Reducing the training time for our Stable Diffusion model deployment

• Working with our backend engineers to expose Stable Diffusion fine-tune training and inference via the Vana API

Future roadmap/vision: 

At Vana, users come to create, share, monitor, and manage AI models trained on their Digital Self. Identity has taken on new meaning in the fast paced world of Generative AI. Vana is the entry point for Users to explore what their AI likeness is capable of, as everything from video games to social media to business becomes transformed and personalized to a degree we’ve never seen. Our AI needs to be cutting edge, and our Users need to know that we have their back every step of the way. 

You Will: (Responsibilities)

• Create proofs of concept for different product ideas enabled by Generative AI technology

• Investigate emergent generative AI technologies for inclusion in the Platform

• Build text, image, and video input and output processes to increase the quality and safety of the generative AI algorithms

• Build pipelines to execute deep learning inference and training requests. 

• Benchmark and optimize ML infrastructure for performance and cost.

Minimum Qualifications:

• Bachelor’s Degree in Computer Science or related field

• 4+ years of professional experience in ML/AI.

• Proven ability to ship end-to-end solutions for ambiguous problems using ML with specific emphasis on discovering and prototyping solutions

• GCP, AWS, Azure, or equivalent cloud machine learning platform experience

• Proven ability to deploy ML models to the cloud to rapidly iterate on new features or apps

Preferred Qualifications:

• Previous experience with Generative AI

• Experience with Vertex AI and Google Cloud Platform

• Experience in a startup environment

What we offer
We are building a foundational piece of the user-owned internet and would love for you to be a part of our team. We are a diverse group of driven, smart, and ambitious individuals, constantly challenging each other to grow, learn and iterate faster. We are experts across our fields and experienced entrepreneurs looking to scale our success in something deeply mission-driven.

For more information, see our Vana Hiring FAQ [External]. 

At Vana, we are big on collaboration and supporting each other to learn, grow, and excel in our individual pursuits. In addition to joining the Vana family, the successful candidate will receive: 

• A competitive base salary, plus equity. The salary range for this position is $140,000 - $220,000.

  • Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance.

• A generous benefits package including health insurance, dental, vision & wellness plan

• Flexible work schedule

• Unlimited PTO

We at Best Buy work hard every day to enrich the lives of customers through technology, whether they come to us online, visit our stores or invite us into their homes. We do this by solving technology problems and addressing key human needs across a range of areas, including entertainment, productivity, communicating with coworkers and loved ones, preparing nutritious food, providing security for your home and family, and helping you take your health to the next level.
 

This role is intended to be hybrid, which means you must be located within a drivable distance to Boston, Seattle, or Minneapolis Corporate locations.

As a Machine Learning Scientist/Engineer Intern, you’ll have the opportunity to work alongside industry experts researching, developing, and applying cutting-edge machine learning and artificial intelligence algorithms to build innovative technologies, services, and products that solve the company's hardest problems and accelerate Best Buy's core growth.  In this role you will combine your passion for software engineering and ML/AI algorithms to contribute to a team developing and operationalizing ML models and production quality code to unleash next generation of customer experiences and transform the way Best Buy operates day-to-day. 

Join us if you like to:

• Developing Machine Learning solutions and services leveraging state-of-the-art techniques
• Applying software engineering skills to develop and deploy solutions that can scale to millions of requests per second with millisecond latency
• Utilizing broad and deep knowledge of machine learning and software engineering to contribute to the roadmap of Best Buy’s core machine learning capabilities
• Building real products that influence and enhance the lives of millions of people and drive and deliver tens of millions of dollars in impact to Best Buy’s bottom line
• Having fun!

Basic Qualifications:

• Pursuing a master’s or PHD degree graduating between Fall 2023 and Spring 2024 
• Must be able to work out of one of the following HUB locations; Seattle, Boston, or Minneapolis.
• Foundational machine learning and algorithmic background with some understanding of at least one of the following areas: supervised and unsupervised learning methods, reinforcement learning, deep learning, Bayesian inference, graphical modeling, or nonlinear/stochastic optimization
• Experience with at least one data science/analytics programming language (e.g. Python, R, Julia)
• Foundational software engineering skills and programming experience with one of more programming languages - Python, R, Julia, Scala or Java

Preferred Qualifications:

• Experience using high performance machine learning libraries and/or deep learning frameworks like PyTorch or Tensorflow
• Fluency with Python and SQL
• Experience working over cloud
• Knowledge of functional programming

DESCRIPTION

The Machine Learning Department has openings for researchers with a passion for developing the next generation of machine intelligence. Expertise in machine learning with a proven track record of original research are prerequisites for this position.

The Machine Learning Department has been at the forefront of research in such areas as deep learning, support vector machines, and semantic analysis for almost two decades. The research in our department has been published in premier venues and has won numerous awards, including the 2010 IEEE Neural Networks Pioneer Award, the 2012 IEEE Frank Rosenblatt Award, the 2012 Benjamin Franklin Medal, the 2013 NEC C&C Prize, ICML 2018 Test of Time Award, and NeurIPS 2018 Test of Time Award. A lot of our research has been translated into NEC’s businesses, leading to innovative products and services of NEC, such as semantic analysis of job applications and product reviews, accident prevention, anomaly detection, and digital pathology.

Currently our department is tackling challenges in imparting abstract reasoning capabilities to machine learning and facilitating effective human-machine collaboration, and how these enable new applications in sustainable environment, smart manufacturing, safe cities, natural language processing, and personalized healthcare.
https://www.nec-labs.com/research/machine-learning/home/

POSITION REQUIREMENTS
• PhD in computer science, electrical engineering, statistics, or equivalent
• Research experience in machine learning with strong publication record
• Strong algorithm and numeric computation background
• Programming experience in Python, C/C++, or other languages
• Experience with deep learning libraries and platforms a plus, e.g. PyTorch, TensorFlow

We also have summer/fall internships available: https://www.appone.com/MainInfoReq.asp?R_ID=4955548