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JOB SUMMARY: NORC at the University of Chicago is seeking a qualified Data Scientist I to join the Methodology and Quantitative Social Sciences department and support innovative research and analytics. The Data Scientist I works collaboratively with methodologists, researchers, statisticians, software developers, and subject matter experts throughout the research lifecycle, including study design, data collection, quality assessment, quantitative analysis, and dissemination of results. This role combines strong foundations in data management, research methodology, and computational social science to develop methodological and data science solutions that improve research, operational efficiency, and decision-making. The Data Scientist I will contribute to projects involving structured and unstructured data, survey data, administrative records, commercial data, text data, and other novel data sources. Responsibilities may include developing data pipelines, implementing data management approaches, maintaining analytical workflows, conducting analysis and creating data visualizations, and assisting in the writing and dissemination of results. The ideal candidate possesses strong social science research and data expertise, written and communication skills, R programming expertise, experience building reproducible analytical workflows, and an interest in applying advanced methods to solve complex research and business problems. Data Scientists are expected to manage multiple assignments, contribute to projects and proposals, stay current with emerging analytic tools, and work effectively in a collaborative, interdisciplinary environment. Location: This is a hybrid role based in our Chicago Loop office, with a minimum of six days per month in the office. Qualified applicants must be eligible to work in the U.S. We regret that we are unable to offer visa sponsorship for this position. DEPARTMENT: Methodology and Quantitative Social Sciences (MQSS) The Methodology and Quantitative Social Sciences (MQSS) department implements state-of-the-art methodologies and develops innovations to deliver reliable data and rigorous analysis to guide critical programmatic, business and policy decisions for NORC clients. The department provides leadership throughout the project lifecycle on study design, data collection, assessment of data quality, quantitative analysis, and dissemination of results. The Methodological and Quantitative Social Sciences department also conducts its own research and is a leader in designing and implementing rigorous, efficient methods for gathering, evaluating, and analyzing data from primary and secondary sources. The department provides expertise and leads NORC strategy on the use of a broad range of methods and techniques, including research and experimental design, recruitment and retention, instrument design and testing, assessing data quality, evaluating measurement properties of new measures, causal inference methods, machine learning, analysis of clustered data, data visualization, use of novel data sources and technologies to improve data gathering, and building AI solutions that support NORC's research. The department collaborates with the Statistics and Data Science Department on areas of synergy and intersection and with all NORC subject matter departments, in addition to leading its own projects. RESPONSIBILITIES: Apply computational and machine learning methods to support survey research, evaluation studies, and other social science research initiatives Contribute to and review the methodological/analytical sections of reports, tables/graphics, presentations, dashboards, and other deliverables Assist with proposal and business development activities related to methodological, analytic, and/or study design tasks. Establish reproducible, quality assured analytic workflows; implement version control (Git), environment management, peer code review, automated testing, and validation checks. Develop robust data pipelines that integrate, transform, and analyze structured and unstructured data from multiple sources to support research and operational objectives. Design and implement data products, dashboards, applications, and automated tools that enable data-driven decision making. Write and implement R programs to extract/manipulate data, link complex datasets, and execute machine learning and statistical analyses. Present research papers at professional conferences and submit articles for publication in journals. Work with relational databases, cloud platforms, and large-scale computing environments to manage and analyze complex datasets efficiently. Uphold data disclosure limitation and data privacy best practices. Perform other duties as assigned. REQUIRED SKILLS: Bachelor's degree in computational social science, data science, computer science or a related quantitative field with social science emphasis. At least 4 years of relevant experience (graduate research, internships, and applied professional experience may be considered). Demonstrated proficiency developing production-quality code in R. Strong foundation in areas of social science research, analytic methods, data engineering, machine learning, and scientific methods of inquiry. Must be detail-oriented and quality-focused, with demonstrated written and oral communication skills Strong interpersonal communication, analytic capability, technical writing, problem identification and resolution, and task management Ability to work on multiple projects simultaneously, effectively organize and manage time, including ability to set priorities to meet all project, proposal, and administrative needs in a timely fashion Experience developing software, data pipelines, or analytical applications. Experience conducting statistical analysis and machine learning using real-world datasets. Experience working with Git and collaborative development workflows. Enthusiasm for teamwork and collaboration across disciplinary boundaries. Preferred Skills: Demonstrated experience programming in Python Experience analyzing survey, administrative, or other large-scale observational datasets, and/or working with longitudinal survey data. Experience with interactive data visualization and mapping libraries such as R Shiny, D3.js or other JavaScript data visualization libraries and HTML/CSS. Experience with large-scale data platforms such as Databricks, Spark, Hadoop, or Hive. Experience developing, evaluating, or deploying machine learning and AI solutions, including work with large language models, and cloud environments (e.g., AWS, Azure, GCP). SALARY AND BENEFITS: The pay range for this position is $90,000-$100,000. This position is classified as regular. Regular staff are eligible for NORC's comprehensive benefits program. Benefits include, but are not limited to: Generously subsidized health insurance, effective on the first day of employment Dental and vision insurance A defined contribution retirement program, along with a separate voluntary 403(b) retirement program Group life insurance, long-term and short-term disability insurance Benefits that promote work/life balance, including generous paid time off, holidays; paid parental leave, bereavement leave, tuition assistance, and an Employee Assistance Program (EAP). NORC is committed to equity and transparency in its pay practices. We publish salary ranges and benefit information for every job. The listed hiring range reflects what we, in good faith, expect to pay at the time of posting, though actual compensation may vary and may be adjusted over time. A candidate's placement within the range depends on factors such as competencies, education, qualifications, experience, skills, performance, and organizational needs. WHAT WE DO: NORC at the University of Chicago is an objective, non-partisan research institution that delivers reliable data and rigorous analysis to guide critical programmatic, business, and policy decisions. Since 1941, our teams have conducted groundbreaking studies, created and applied innovative methods and tools, and advanced principles of scientific integrity and collaboration. Today, government, corporate, and nonprofit clients around the world partner with us to transform increasingly complex information into useful knowledge. WHO WE ARE: For over 80 years, NORC has evolved in many ways, moving the needle with research methods, technical applications and groundbreaking research findings. But our tradition of excellence, passion for innovation, and commitment to collegiality have remained constant components of who we are as a brand, and who each of us is as a member of the NORC team. With world-class benefits, a business casual environment, and an emphasis on continuous learning, NORC is a place where people join for the stellar research and analysis work for which we're known, and stay for the relationships they form with their colleagues who take pride in the impact their work is making on a global scale. EEO STATEMENT: NORC is an equal opportunity employer. NORC evaluates qualified applicants without regard to race, color, religion, sex, gender, national origin, disability, status as a protected veteran, sexual orientation, and other legally protected characteristics.

Applied Researcher 5 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 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. 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. What You'll Do: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies; Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more, to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. Lead cross-functional research threads that bridge prototype model development and deployment with ML engineering partners, ensuring scientific insights translate to production impact The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers 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 A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms Has a deep understanding of the foundations of AI methodologies Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes Experience in delivering libraries, platform level code or solution level code to existing products A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. Basic Qualifications: Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, High Performance Computing, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on Generative AI (LLMs, Diffusion models and related approaches) or Masters with 5 years of industrial research experience in deep learning based techniques Multiple publications at top-tier venues (e.g., KDD, SIGIR, RecSys, NeurIPS, ICLR) on topics related to generative recommendation, retrieval-augmented generation (RAG), LLM-based agents, or large-scale semantic search Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Behavioral Models PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series) Multiple papers on topics relevant to training models on graph and sequential data structures at KDD, ICML, NeurIPs, ICLR Experience training foundation models from scratch or significantly adapting large-scale models (10B+ parameters) for complex financial data, transactional sequences, or user behavior graphs Track record of scaling graph models to greater than 50M nodes and operating within high-velocity, real-time streaming data environments Contributions to common open source frameworks (pytorch-geometric, DGL) Proposed new methods for inference or representation learning on graphs or sequences Worked datasets with 100m+ users Optimization (Training & Inference) Multiple years of experience or publications focused on model sparsification, quantization, training parallelism/partitioning design, or gradient checkpointing for 10B+ parameter models Hands-on experience with large-scale orchestration systems (Kubernetes, KubeRay) and contributions to common open-source ML frameworks (PyTorch-Geometric, DGL, HuggingFace) Experience building and deploying deep learning-based recommender systems at scale (100M+ users or items), ideally within travel, personalization, or e-commerce contexts Finetuning PhD focused on topics related to aligning Large Language Models for recommendation and search tasks via Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), or Direct Preference Optimization (DPO) Experience deploying a fine-tuned large language model optimized for serving performance Proven ability to design and lead small-scale research initiatives, guiding junior researchers or engineers through experimental design and evaluation Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. 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. Cambridge, MA: $262,500 - $299,600 for Applied Researcher 5 McLean, VA: $262,500 - $299,600 for Applied Researcher 5 New York, NY: $286,400 - $326,800 for Applied Researcher 5 San Francisco, CA: $286,400 - $326,800 for Applied Researcher 5 San Jose, CA: $286,400 - $326,800 for Applied Researcher 5 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. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital 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 (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. 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 . click apply for full job details

Applied Researcher 5 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 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. 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. What You'll Do: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies; Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more, to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. Lead cross-functional research threads that bridge prototype model development and deployment with ML engineering partners, ensuring scientific insights translate to production impact The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers 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 A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms Has a deep understanding of the foundations of AI methodologies Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes Experience in delivering libraries, platform level code or solution level code to existing products A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. Basic Qualifications: Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, High Performance Computing, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on Generative AI (LLMs, Diffusion models and related approaches) or Masters with 5 years of industrial research experience in deep learning based techniques Multiple publications at top-tier venues (e.g., KDD, SIGIR, RecSys, NeurIPS, ICLR) on topics related to generative recommendation, retrieval-augmented generation (RAG), LLM-based agents, or large-scale semantic search Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Behavioral Models PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series) Multiple papers on topics relevant to training models on graph and sequential data structures at KDD, ICML, NeurIPs, ICLR Experience training foundation models from scratch or significantly adapting large-scale models (10B+ parameters) for complex financial data, transactional sequences, or user behavior graphs Track record of scaling graph models to greater than 50M nodes and operating within high-velocity, real-time streaming data environments Contributions to common open source frameworks (pytorch-geometric, DGL) Proposed new methods for inference or representation learning on graphs or sequences Worked datasets with 100m+ users Optimization (Training & Inference) Multiple years of experience or publications focused on model sparsification, quantization, training parallelism/partitioning design, or gradient checkpointing for 10B+ parameter models Hands-on experience with large-scale orchestration systems (Kubernetes, KubeRay) and contributions to common open-source ML frameworks (PyTorch-Geometric, DGL, HuggingFace) Experience building and deploying deep learning-based recommender systems at scale (100M+ users or items), ideally within travel, personalization, or e-commerce contexts Finetuning PhD focused on topics related to aligning Large Language Models for recommendation and search tasks via Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), or Direct Preference Optimization (DPO) Experience deploying a fine-tuned large language model optimized for serving performance Proven ability to design and lead small-scale research initiatives, guiding junior researchers or engineers through experimental design and evaluation Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. 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. Cambridge, MA: $262,500 - $299,600 for Applied Researcher 5 McLean, VA: $262,500 - $299,600 for Applied Researcher 5 New York, NY: $286,400 - $326,800 for Applied Researcher 5 San Francisco, CA: $286,400 - $326,800 for Applied Researcher 5 San Jose, CA: $286,400 - $326,800 for Applied Researcher 5 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. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital 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 (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. 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 . click apply for full job details

Job Description Job Description Altamira brings a commercial mindset to solving the most complex national security problems by delivering mission application development, multi-intelligence analysis, and data science technologies and solutions to the defense, intelligence, and homeland security communities. Altamira's culture of innovation and excellence, and mid-market-size, positions us as the premier next generation leader bringing technology solutions to mission. Position Description We are seeking an experienced R&D Technical Lead to bridge the gap between AI/ML research and production-ready solutions. In this role, you will provide technical leadership across AI/ML and software engineering, guiding teams from early-stage research concepts through successful customer delivery. The ideal candidate brings a broad software engineering background combined with strong AI/ML expertise, with the ability to translate machine learning models and research into scalable, integrated software architectures. You will collaborate across disciplines to drive technical decisions, mentor development teams, and ensure solutions meet real-world customer needs. Our work focuses on applied AI/ML solutions for real-world object tracking, detection, and characterization, enabling advanced data triaging and system automation. These capabilities help our customers manage increasing volumes of data and address the challenges associated with data saturation. Core Responsibilities Team Leadership: Provide technical guidance to engineering teams, aligning project requirements to technical tasking System Architecture: Design and implement scalable, high-performance software systems that integrate AI/ML capabilities Collection Coordination: Architect multi-agent or agentic workflows to synchronize data collection efforts across various projects, optimizing resource allocation. Technical Mentorship: Lead a high-performing team of engineers, conducting code reviews and setting engineering standards for MLOps and production pipelines. Strategic Integration: Collaborate with project managers to translate complex client requirements into actionable AI/ML roadmaps. Qualifications & Skills Education: Bachelor's or above in Computer Science, AI, or a related quantitative field. Experience: 7+ years of professional experience in machine learning, with at least 3 years leading teams from research or prototyping through production deployment. Computer Vision Expertise: Proven track record in developing computer vision models for object tracking (e.g., CNNs, Transformers) and real-time video analytics. Advanced Programming: Expert-level proficiency in Python and high-performance languages (C++/Rust/Java) alongside familiarity with backend deployment tools (Docker, Kubernetes). Data Management: Experience overseeing the full data lifecycle, from acquisition and cleaning to high-fidelity labeling for specialized collections. Communication: Ability to articulate complex AI concepts to non-technical stakeholders and executive leadership.

Job Description Job Description What Impact You'll Have GRVTY is seeking a motivated and experienced Data Manager to provide technical and managerial leadership over our overhead satellite imagery preprocessing operations. The ideal candidate is an experienced data operations leader with a passion for solving complex pipeline challenges, ensuring data integrity, and delivering mission-critical results in support of the DoW and Intelligence Community. This role serves as the primary communication interface between the customer and the team, translating requirements into successful execution across the full data operations lifecycle. What You'll be Owning Oversee and manage data, databases, and pipelines across the full data acquisition, curation, and preprocessing lifecycle, ensuring compliance with specified requirements and priorities Conduct regular Quality Control (QC) of data holdings to: Manage the data operations pipeline to include: Apply engineering best practices to optimize data pipeline efficiency and performance across all sensor modalities including: EO, FMV, HMI, and SAR Lead and manage team members by providing: Ensure data dictionaries, Entity Relationship Diagrams (ERDs), software comments, and documentation are regularly maintained and updated Serve as the primary customer communication interface to relay tasks and requirements and ensure successful work execution What You Must Have Active TS/SCI Clearance with the ability to obtain a CI/Poly People management experience, including: Team lead or project lead roles Independently initiating and driving projects to completion Strategic problem solver with excellent communication skills Experience in quantitative analysis and data operations, to include: Developing visualizations and processing complex data to create data-driven insights Data manipulation and ETL procedures Working knowledge of SQL and NoSQL database technologies Demonstrated experience managing databases and data pipelines Experience working with cloud architectures Experience working with large, complex geospatial data files and formats What Would be Nice to Have Experience using Agile/SAFe methodologies Experience with NGA enterprise technology systems such as NGA CORE and MLOps GEOINT Professional Certification - Fundamentals (F) Experience working with AI/ML technologies applied to geospatial data Pay Range: At GRVTY, we understand that compensation is influenced by many factors-such as geographic location, federal contract labor categories, wage rates, prior experience, skillsets, education, and certifications. We're proud to offer a work environment that empowers our team to achieve a strong work-life balance. GRVTY provides competitive pay, comprehensive benefits, and meaningful opportunities for professional growth. Our benefits package is designed to support the well-being of our employees and their families, and includes coverage in areas such as healthcare, financial wellness, retirement planning, family assistance, continued education, and paid time off. The pay range for this position is: $160,000 - $190,000 Pay Range: At GRVTY, we understand that compensation is influenced by many factors-such as geographic location, federal contract labor categories, wage rates, prior experience, skillsets, education, and certifications. We're proud to offer a work environment that empowers our team to achieve a strong work-life balance. GRVTY provides competitive pay, comprehensive benefits, and meaningful opportunities for professional growth. Our benefits package is designed to support the well-being of our employees and their families, and includes coverage in areas such as healthcare, financial wellness, retirement planning, family assistance, continued education, and paid time off. Virginia Pay Range $160,000-$190,000 USD Why Choose GRVTY The toughest national security challenges demand vision and ingenuity, not just resources. We deliver mission and technical expertise to outpace our adversaries. We're purpose-built to tackle the most entrenched, systemic national security issues around the world. We partner with our customers to help them overcome challenges in every corner of technology and defense-including the ones still being explored. Our growing capabilities create complementary advantages, giving on-the-ground operations the edge they need to succeed. We muster everything we have to answer every challenge presented, every day of our lives. At GRVTY, we believe that when our employees thrive, our company thrives. That's why we offer a comprehensive and competitive benefits package designed to support your well-being, growth, and work-life balance. • Robust health plan including medical, dental, and vision • Health Savings Account with company contribution • Annual Paid Time Off and Paid Holidays • Paid Parental Leave • 401k with generous company match • Training and Development Opportunities • Award Programs • Variety of Company Sponsored Events EEO Statement GRVTY, is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran and will not be discriminated against on the basis of disability. Anyone requiring reasonable accommodations should email or call with requested details. A member of the HR team will respond to your request within 2 business days. Know Your Rights: Workplace Discrimination is Illegal (eeoc.gov) Please review our current job openings and apply for the positions you believe may be a fit. If you are not an immediate fit, we will also keep your resume in our database for future opportunities.

Job Description Job Description Material Bank is the world's largest material marketplace for the architecture and design industry. Operating in 37 countries, our platform has become the standard for design professionals around the globe. Every day, Material Bank connects thousands of designers with tens of thousands of materials from leading brands. Material Bank is the fastest and most powerful way for design professionals to search, sample, and specify materials. About the role As an Applied AI Engineer, you will drive the design, build, and deployment of next-generation AI-powered experiences across Material Bank's platform. You will work as part of the team responsible for taking ideas from concept to production - building intelligent systems and user experiences that blend cutting-edge AI capabilities with the high standards of quality, aesthetics, and usability expected in the architecture and community. This is a senior-level individual contributor role focused on applied AI product development. You will work across the stack to architect and deploy scalable AI systems that enhance how users discover, understand, and engage with products, materials, and creative content. Your work will span areas such as multimodal search and understanding, AI-assisted content generation, intelligent workflows, personalization, creative tooling, and agentic systems. We are looking for someone who not only understands modern AI systems technically, but also has strong product instincts, visual sensibility, and genuine passion for building AI experiences that feel thoughtful, polished, and useful. AI will play a foundational role in the future of Material Bank's platform, and you will help define and build that future. What you'll do Design, build, and deploy end-to-end AI-powered product experiences from concept through production. Architect and implement scalable AI systems leveraging LLMs, embeddings, multimodal models, retrieval systems, agent frameworks, and modern data infrastructure. Build production-grade multi-agent workflows and orchestration systems using frameworks such as LangGraph, LangChain, Mastra, and custom tooling. Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector search, retrieval pipelines, chunking strategies, and relevance tuning. Build multimodal AI workflows that analyze and reason over images, creative assets, and visual datasets using modern multimodal LLMs, embedding models, and specialized tooling such as SAM2/SAM3. Create AI-assisted experiences for search, discovery, content generation, personalization, and creative workflows across Material Bank's platform. Evaluate, refine, and improve AI-generated outputs for quality, tone, accuracy, and creative alignment through testing, iteration, and human-in-the-loop evaluation strategies. Partner closely with Product, Design, Engineering, Data, and Executive Leadership to identify high-impact opportunities and translate ambiguous ideas into production-ready AI capabilities. Make architectural decisions that balance speed, scalability, latency, cost, accuracy, and long-term maintainability. Continuously evaluate emerging AI technologies, models, frameworks, and workflows to identify opportunities that create meaningful business and user value. What you'll bring 8+ years of experience building and shipping production software, including significant full-stack engineering experience. Demonstrated success designing and deploying production-grade AI/ML systems and AI-powered product experiences. Deep hands-on experience with LLMs, embeddings, multimodal AI systems, RAG architectures, and multi-agent frameworks such as LangGraph, LangChain, Mastra, or equivalent custom tooling. Strong engineering fundamentals across backend systems, APIs, data pipelines, cloud infrastructure, and modern JavaScript/TypeScript and Python ecosystems. Experience working with multimodal models, visual analysis systems, and image-based AI workflows at scale, including familiarity with modern image-generation tooling and services. Strong systems thinking with the ability to balance trade-offs across latency, cost, scalability, accuracy, reliability, and user experience. Proven ability to independently take ambiguous problems from idea to shipped product with minimal oversight. Strong product instincts, visual sensibility, and a high bar for quality, usability, and craftsmanship in AI-generated experiences. Genuine interest in creative industries such as architecture, design, fashion, media, photography, or art, with an appreciation for aesthetics and taste. Open-source contributions, side projects, or publicly demonstrable AI work that reflects curiosity, experimentation, and passion for applied AI are strongly preferred. Strong communication and collaboration skills, with the ability to work effectively across both technical and non-technical teams. What you'll get from us: Our people : We are a growth-driven team that values efficiency, builds smart automation, operates in small empowered teams, and moves quickly from idea to execution. Relaxation and Celebrations : Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect). Health Benefits : We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program. Plan for your Retirement : 401(k) eligible after your first 90 day's employed! Giving Back : We sponsor multiple events throughout the year to help out our communities. Growth : We'll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters! Flexible Work Schedules : With business units and employees across the globe, Material Technologies has embraced a hybrid working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both. Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.

Job Description Job Description Material Bank is the world's largest material marketplace for the architecture and design industry. Operating in 37 countries, our platform has become the standard for design professionals around the globe. Every day, Material Bank connects thousands of designers with tens of thousands of materials from leading brands. Material Bank is the fastest and most powerful way for design professionals to search, sample, and specify materials. About the role As an Applied AI Engineer, you will drive the design, build, and deployment of next-generation AI-powered experiences across Material Bank's platform. You will work as part of the team responsible for taking ideas from concept to production - building intelligent systems and user experiences that blend cutting-edge AI capabilities with the high standards of quality, aesthetics, and usability expected in the architecture and community. This is a senior-level individual contributor role focused on applied AI product development. You will work across the stack to architect and deploy scalable AI systems that enhance how users discover, understand, and engage with products, materials, and creative content. Your work will span areas such as multimodal search and understanding, AI-assisted content generation, intelligent workflows, personalization, creative tooling, and agentic systems. We are looking for someone who not only understands modern AI systems technically, but also has strong product instincts, visual sensibility, and genuine passion for building AI experiences that feel thoughtful, polished, and useful. AI will play a foundational role in the future of Material Bank's platform, and you will help define and build that future. What you'll do Design, build, and deploy end-to-end AI-powered product experiences from concept through production. Architect and implement scalable AI systems leveraging LLMs, embeddings, multimodal models, retrieval systems, agent frameworks, and modern data infrastructure. Build production-grade multi-agent workflows and orchestration systems using frameworks such as LangGraph, LangChain, Mastra, and custom tooling. Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector search, retrieval pipelines, chunking strategies, and relevance tuning. Build multimodal AI workflows that analyze and reason over images, creative assets, and visual datasets using modern multimodal LLMs, embedding models, and specialized tooling such as SAM2/SAM3. Create AI-assisted experiences for search, discovery, content generation, personalization, and creative workflows across Material Bank's platform. Evaluate, refine, and improve AI-generated outputs for quality, tone, accuracy, and creative alignment through testing, iteration, and human-in-the-loop evaluation strategies. Partner closely with Product, Design, Engineering, Data, and Executive Leadership to identify high-impact opportunities and translate ambiguous ideas into production-ready AI capabilities. Make architectural decisions that balance speed, scalability, latency, cost, accuracy, and long-term maintainability. Continuously evaluate emerging AI technologies, models, frameworks, and workflows to identify opportunities that create meaningful business and user value. What you'll bring 8+ years of experience building and shipping production software, including significant full-stack engineering experience. Demonstrated success designing and deploying production-grade AI/ML systems and AI-powered product experiences. Deep hands-on experience with LLMs, embeddings, multimodal AI systems, RAG architectures, and multi-agent frameworks such as LangGraph, LangChain, Mastra, or equivalent custom tooling. Strong engineering fundamentals across backend systems, APIs, data pipelines, cloud infrastructure, and modern JavaScript/TypeScript and Python ecosystems. Experience working with multimodal models, visual analysis systems, and image-based AI workflows at scale, including familiarity with modern image-generation tooling and services. Strong systems thinking with the ability to balance trade-offs across latency, cost, scalability, accuracy, reliability, and user experience. Proven ability to independently take ambiguous problems from idea to shipped product with minimal oversight. Strong product instincts, visual sensibility, and a high bar for quality, usability, and craftsmanship in AI-generated experiences. Genuine interest in creative industries such as architecture, design, fashion, media, photography, or art, with an appreciation for aesthetics and taste. Open-source contributions, side projects, or publicly demonstrable AI work that reflects curiosity, experimentation, and passion for applied AI are strongly preferred. Strong communication and collaboration skills, with the ability to work effectively across both technical and non-technical teams. What you'll get from us: Our people : We are a growth-driven team that values efficiency, builds smart automation, operates in small empowered teams, and moves quickly from idea to execution. Relaxation and Celebrations : Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect). Health Benefits : We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program. Plan for your Retirement : 401(k) eligible after your first 90 day's employed! Giving Back : We sponsor multiple events throughout the year to help out our communities. Growth : We'll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters! Flexible Work Schedules : With business units and employees across the globe, Material Technologies has embraced a hybrid working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both. Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.

Job Description Job Description Material Bank is the world's largest material marketplace for the architecture and design industry. Operating in 37 countries, our platform has become the standard for design professionals around the globe. Every day, Material Bank connects thousands of designers with tens of thousands of materials from leading brands. Material Bank is the fastest and most powerful way for design professionals to search, sample, and specify materials. About the role As an Applied AI Engineer, you will drive the design, build, and deployment of next-generation AI-powered experiences across Material Bank's platform. You will work as part of the team responsible for taking ideas from concept to production - building intelligent systems and user experiences that blend cutting-edge AI capabilities with the high standards of quality, aesthetics, and usability expected in the architecture and community. This is a senior-level individual contributor role focused on applied AI product development. You will work across the stack to architect and deploy scalable AI systems that enhance how users discover, understand, and engage with products, materials, and creative content. Your work will span areas such as multimodal search and understanding, AI-assisted content generation, intelligent workflows, personalization, creative tooling, and agentic systems. We are looking for someone who not only understands modern AI systems technically, but also has strong product instincts, visual sensibility, and genuine passion for building AI experiences that feel thoughtful, polished, and useful. AI will play a foundational role in the future of Material Bank's platform, and you will help define and build that future. What you'll do Design, build, and deploy end-to-end AI-powered product experiences from concept through production. Architect and implement scalable AI systems leveraging LLMs, embeddings, multimodal models, retrieval systems, agent frameworks, and modern data infrastructure. Build production-grade multi-agent workflows and orchestration systems using frameworks such as LangGraph, LangChain, Mastra, and custom tooling. Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector search, retrieval pipelines, chunking strategies, and relevance tuning. Build multimodal AI workflows that analyze and reason over images, creative assets, and visual datasets using modern multimodal LLMs, embedding models, and specialized tooling such as SAM2/SAM3. Create AI-assisted experiences for search, discovery, content generation, personalization, and creative workflows across Material Bank's platform. Evaluate, refine, and improve AI-generated outputs for quality, tone, accuracy, and creative alignment through testing, iteration, and human-in-the-loop evaluation strategies. Partner closely with Product, Design, Engineering, Data, and Executive Leadership to identify high-impact opportunities and translate ambiguous ideas into production-ready AI capabilities. Make architectural decisions that balance speed, scalability, latency, cost, accuracy, and long-term maintainability. Continuously evaluate emerging AI technologies, models, frameworks, and workflows to identify opportunities that create meaningful business and user value. What you'll bring 8+ years of experience building and shipping production software, including significant full-stack engineering experience. Demonstrated success designing and deploying production-grade AI/ML systems and AI-powered product experiences. Deep hands-on experience with LLMs, embeddings, multimodal AI systems, RAG architectures, and multi-agent frameworks such as LangGraph, LangChain, Mastra, or equivalent custom tooling. Strong engineering fundamentals across backend systems, APIs, data pipelines, cloud infrastructure, and modern JavaScript/TypeScript and Python ecosystems. Experience working with multimodal models, visual analysis systems, and image-based AI workflows at scale, including familiarity with modern image-generation tooling and services. Strong systems thinking with the ability to balance trade-offs across latency, cost, scalability, accuracy, reliability, and user experience. Proven ability to independently take ambiguous problems from idea to shipped product with minimal oversight. Strong product instincts, visual sensibility, and a high bar for quality, usability, and craftsmanship in AI-generated experiences. Genuine interest in creative industries such as architecture, design, fashion, media, photography, or art, with an appreciation for aesthetics and taste. Open-source contributions, side projects, or publicly demonstrable AI work that reflects curiosity, experimentation, and passion for applied AI are strongly preferred. Strong communication and collaboration skills, with the ability to work effectively across both technical and non-technical teams. What you'll get from us: Our people : We are a growth-driven team that values efficiency, builds smart automation, operates in small empowered teams, and moves quickly from idea to execution. Relaxation and Celebrations : Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect). Health Benefits : We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program. Plan for your Retirement : 401(k) eligible after your first 90 day's employed! Giving Back : We sponsor multiple events throughout the year to help out our communities. Growth : We'll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters! Flexible Work Schedules : With business units and employees across the globe, Material Technologies has embraced a hybrid working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both. Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.

Job Description Job Description Material Bank is the world's largest material marketplace for the architecture and design industry. Operating in 37 countries, our platform has become the standard for design professionals around the globe. Every day, Material Bank connects thousands of designers with tens of thousands of materials from leading brands. Material Bank is the fastest and most powerful way for design professionals to search, sample, and specify materials. About the role As an Applied AI Engineer, you will drive the design, build, and deployment of next-generation AI-powered experiences across Material Bank's platform. You will work as part of the team responsible for taking ideas from concept to production - building intelligent systems and user experiences that blend cutting-edge AI capabilities with the high standards of quality, aesthetics, and usability expected in the architecture and community. This is a senior-level individual contributor role focused on applied AI product development. You will work across the stack to architect and deploy scalable AI systems that enhance how users discover, understand, and engage with products, materials, and creative content. Your work will span areas such as multimodal search and understanding, AI-assisted content generation, intelligent workflows, personalization, creative tooling, and agentic systems. We are looking for someone who not only understands modern AI systems technically, but also has strong product instincts, visual sensibility, and genuine passion for building AI experiences that feel thoughtful, polished, and useful. AI will play a foundational role in the future of Material Bank's platform, and you will help define and build that future. What you'll do Design, build, and deploy end-to-end AI-powered product experiences from concept through production. Architect and implement scalable AI systems leveraging LLMs, embeddings, multimodal models, retrieval systems, agent frameworks, and modern data infrastructure. Build production-grade multi-agent workflows and orchestration systems using frameworks such as LangGraph, LangChain, Mastra, and custom tooling. Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector search, retrieval pipelines, chunking strategies, and relevance tuning. Build multimodal AI workflows that analyze and reason over images, creative assets, and visual datasets using modern multimodal LLMs, embedding models, and specialized tooling such as SAM2/SAM3. Create AI-assisted experiences for search, discovery, content generation, personalization, and creative workflows across Material Bank's platform. Evaluate, refine, and improve AI-generated outputs for quality, tone, accuracy, and creative alignment through testing, iteration, and human-in-the-loop evaluation strategies. Partner closely with Product, Design, Engineering, Data, and Executive Leadership to identify high-impact opportunities and translate ambiguous ideas into production-ready AI capabilities. Make architectural decisions that balance speed, scalability, latency, cost, accuracy, and long-term maintainability. Continuously evaluate emerging AI technologies, models, frameworks, and workflows to identify opportunities that create meaningful business and user value. What you'll bring 8+ years of experience building and shipping production software, including significant full-stack engineering experience. Demonstrated success designing and deploying production-grade AI/ML systems and AI-powered product experiences. Deep hands-on experience with LLMs, embeddings, multimodal AI systems, RAG architectures, and multi-agent frameworks such as LangGraph, LangChain, Mastra, or equivalent custom tooling. Strong engineering fundamentals across backend systems, APIs, data pipelines, cloud infrastructure, and modern JavaScript/TypeScript and Python ecosystems. Experience working with multimodal models, visual analysis systems, and image-based AI workflows at scale, including familiarity with modern image-generation tooling and services. Strong systems thinking with the ability to balance trade-offs across latency, cost, scalability, accuracy, reliability, and user experience. Proven ability to independently take ambiguous problems from idea to shipped product with minimal oversight. Strong product instincts, visual sensibility, and a high bar for quality, usability, and craftsmanship in AI-generated experiences. Genuine interest in creative industries such as architecture, design, fashion, media, photography, or art, with an appreciation for aesthetics and taste. Open-source contributions, side projects, or publicly demonstrable AI work that reflects curiosity, experimentation, and passion for applied AI are strongly preferred. Strong communication and collaboration skills, with the ability to work effectively across both technical and non-technical teams. What you'll get from us: Our people : We are a growth-driven team that values efficiency, builds smart automation, operates in small empowered teams, and moves quickly from idea to execution. Relaxation and Celebrations : Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect). Health Benefits : We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program. Plan for your Retirement : 401(k) eligible after your first 90 day's employed! Giving Back : We sponsor multiple events throughout the year to help out our communities. Growth : We'll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters! Flexible Work Schedules : With business units and employees across the globe, Material Technologies has embraced a hybrid working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both. Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.

Job Description Job Description Lead / Principal Process ML Engineer Job Title: Lead / Principal Process ML Engineer Job Type: Full-time Location: San Diego, CA Summary We are building AI platforms that run on real factory floors, predicting, optimizing, and controlling manufacturing processes in real time. This role is needed to expand our process optimization capability - we need a technical leader who can own the full lifecycle of ML-driven process optimization products, from causal modeling to productization and customer deployment. Currently there is no dedicated technical lead for this product area, and growing customer demand requires a senior leader to set the technical vision and drive execution. Roles and Responsibilities Own the technical direction for key projects - set vision, define what to build, manage priorities, and be accountable for delivery Lead development of ML-driven process optimization products - from causal modeling to productization and customer deployment Make architecture decisions: select modeling approaches, define system boundaries, and evaluate trade-offs between physical fidelity, inference speed, and product constraints Define modeling strategy - decide which physics to encode, which architectures to use, and how to validate against real process data Drive architecture reviews and technical decision-making across the process optimization team Hire, mentor, and grow engineers - build a high-performing team through hiring, code reviews, and technical coaching Coordinate across HQ (Seoul) and overseas R&D labs - aligning research with product roadmaps across time zones Own production-grade delivery - models must run reliably inside equipment operating 24/7 on customer lines Requirements Doctorate (Ph.D.) Mechanical Engineering, Physics, Computer Science, Electrical Engineering, or a related field 8+ years of industry experience post-Ph.D. Proven track record of shipping process optimization or control products from problem definition through customer-facing deployment Experience leading a technical team - setting direction, managing delivery, and making architecture decisions Strong physics foundation (fluid dynamics, thermodynamics, heat transfer, mechanics) Strong ML skills (PyTorch, custom architectures, PINNs, neural operators, surrogate models) Ability to bridge physics and product - translate process understanding into model design and product features Comfort with ambiguity: able to define the problem and the approach, not just execute a spec Experience shipping ML-driven process optimization or control products in an industry setting Experience leading or managing a technical team (ML or applied science) Experience with production software systems - ML integration, data pipelines, deployment infrastructure Preferred Requirements Prior role as Tech Lead, Staff Engineer, or Team Lead in an ML or applied science team Experience productizing process optimization as a commercial product deployed on customer sites Hands-on manufacturing process experience - semiconductor, SMT, electronics assembly, or precision manufacturing Experience coordinating technical direction across distributed teams (HQ + overseas R&D) Published work in scientific machine learning, computational physics, or neural operators Experience with SPC, Cpk analysis, or 3D inspection/metrology systems Benefits • Health/Dental/Vision/Life Insurance at no employee premium (including dependent coverage) • 401K retirement plan with 5% matching • Generous PTO and paid holidays