Computational Geometer Jobs

Senior Low Observables (LO) Mission Systems Integration Engineer Company: The Boeing Company The Senior LO Mission Systems Integration Engineer will lead design, integration, analysis, test, and production activities for low observable materials, structures, apertures, sensors, and radomes for mission systems. The role requires strong technical leadership, independent execution of complex tasks, advanced use of computational electromagnetic (CEM) solvers, and the ability to produce and defend technical results with minimal oversight. Key Responsibilities Lead design, modeling, and analysis efforts for LO materials, coatings, structures, and integrated mission systems to meet signature reduction and performance requirements. Independently apply CEM solvers (e.g., FEKO, HFSS, CST, WIPL‑D, xFDTD, or equivalent) to model antennas, apertures, radomes, and LO treatments; perform design optimization and trade studies. Drive integration of LO treatments with mechanical, thermal, and sensor/antenna system constraints; identify and mitigate producibility, testability, and sustainment risks. Plan, execute, and oversee laboratory and field tests (anechoic chamber measurements, antenna/radome characterization, RCS measurements); lead data collection, reduction, and validation activities. Develop and validate predictive models, reconcile simulations with measurements, perform uncertainty quantification, and provide actionable recommendations to engineering and program leadership. Produce high-quality technical documentation: test plans, test reports, technical memoranda, design reviews, and customer briefings. Mentor and provide technical oversight to junior engineers and technicians; ensure adherence to engineering processes, qual

Natera’s Research team is building tests that can detect many cancers from a single blood draw. We are looking for a Staff Machine Learning and Bioinformatics Scientist to help design the models at the heart of that effort. You’ll work with large-scale, multi-modal genomic datasets from clinical cohorts and partner closely with molecular biologists and clinical scientists. Your research will advance the state-of-the-art and you will drive new methods from prototype, through scalable implementation, toward clinical validation and, ultimately, to patients. PRIMARY RESPONSIBILITIES: Lead the development of novel statistical and machine learning methods for cancer signal detection on multi-modal genomic data Build interpretable, well-calibrated models, setting the standard for uncertainty estimation and reproducibility across the group Prototype, test and productionize ML models using scalable infrastructure Own key technical deliverables within larger projects and help shape the team’s research roadmap Collaborate closely with molecular biologists and clinical experts on design and analysis of experiments and validation studies Keep raising the bar through code and design reviews across projects Translate complex results into clear stories for technical and non-technical audiences Mentor junior scientists and champion a culture of curiosity, collaboration, and scientific excellence QUALIFICATIONS: PhD in Computer Science, Mathematics, Bioinformatics, or a related quantitative field with 6-12 years of experience post-PhD Hands-on experience developing novel statistical / ML analysis methods applied to complex biological data Proven track record of innovation and technical leadership in complex method development projects Expertise in deep learning and multimodal foundation models Proficient in Python and its scientific computing ecosystem Scientific rigor throughout the R&D process, with eagerness to teach and learn new computational methods and biology Excellent co

Natera’s Research team is building tests that can detect many cancers from a single blood draw. We are looking for a Staff Machine Learning and Bioinformatics Scientist to help design the models at the heart of that effort. You’ll work with large-scale, multi-modal genomic datasets from clinical cohorts and partner closely with molecular biologists and clinical scientists. Your research will advance the state-of-the-art and you will drive new methods from prototype, through scalable implementation, toward clinical validation and, ultimately, to patients. PRIMARY RESPONSIBILITIES: Lead the development of novel statistical and machine learning methods for cancer signal detection on multi-modal genomic data Build interpretable, well-calibrated models, setting the standard for uncertainty estimation and reproducibility across the group Prototype, test and productionize ML models using scalable infrastructure Own key technical deliverables within larger projects and help shape the team’s research roadmap Collaborate closely with molecular biologists and clinical experts on design and analysis of experiments and validation studies Keep raising the bar through code and design reviews across projects Translate complex results into clear stories for technical and non-technical audiences Mentor junior scientists and champion a culture of curiosity, collaboration, and scientific excellence QUALIFICATIONS: PhD in Computer Science, Mathematics, Bioinformatics, or a related quantitative field with 6-12 years of experience post-PhD Hands-on experience developing novel statistical / ML analysis methods applied to complex biological data Proven track record of innovation and technical leadership in complex method development projects Expertise in deep learning and multimodal foundation models Proficient in Python and its scientific computing ecosystem Scientific rigor throughout the R&D process, with eagerness to teach and learn new computational methods and biology Excellent co

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Knowledge Graph Platform team builds the foundational systems that help Reddit understand entities, relationships, and context across its content. We are evolving an advanced, AI-powered knowledge graph into a reliable, scalable platform that enables teams across Reddit to build better experiences on top of shared, high-quality knowledge. This is a high-leverage team at the intersection of data, platform engineering, and AI. Our work supports emerging capabilities such as contextual grounding while creating the contracts, standards, and developer experience that make shared data dependable and easy to use. This team is strategically positioned to impact both ads and consumer roadmaps. Our data is used across ads marketplace models as well as user-facing features on reddit.com . What You’ll Do: Lead, coach, and develop a team of engineers building Reddit’s Knowledge Graph Platform; create a high-trust, high-performing environment with clear goals and strong technical ownership. Set the technical direction and roadmap for a scalable knowledge graph platform, including data and API contracts, service interfaces, reliability, observability, performance, and developer experience. Leverage SOTA LLM and agentic patterns for knowledge graph construction. Establish production-grade operating standards: defining SLOs, implementing quality measures of data within the knowledge graph, governance mechanisms, and safe change-management practices. Partner with engineering, computational linguists, and domain-expe

About the team Life sciences is one of the clearest areas where advances in intelligence can meaningfully benefit the world at large. The OpenAI Life Sciences team works at the intersection of advancing frontier life sciences model capabilities and building products to help scientists accelerate their research and leverage the full potential of AI for scientific work. We’re building platforms that connect model intelligence with practical scientific workflows. Our work covers workflows from next-gen sequencing analysis to designing new drugs, helping scientists run computational workloads as well as access laboratory services. By making these capabilities more accessible and useful, we aim to improve early discovery and support downstream progress in drug development. About the role We’re looking for experienced full-stack product engineers with strong backend skills to join our growing Life Sciences team. This is an individual contributor role with substantial ownership. You’ll help define products, design systems, and ship experiences that connect scientists with AI capabilities and laboratory workflows. You’ll work across the stack, partnering with researchers, scientists, and infrastructure engineers to turn complex needs into reliable, intuitive products. We value strong engineering fundamentals, product judgment, and experience shipping to large user bases. Life sciences experience is helpful, but you don’t need a scientific background to make a meaningful contribution. In this role, you will Design backend services, APIs, and integrations that connect users with models, scientific tools, and laboratory services. Create intuitive interfaces that help scientists navigate complex workflows. Own projects from problem definition and technical design through launch, operation, and iteration. Work with scientific and research partners to identify user needs and prioritize valuable product improvements. Partner with dedicated infrastructure engineers on performance,

Where Performance Meets Purpose Join a team that values excellence and innovation, at a company known for its iconic golf brands. At Acushnet Company, your background and experience contribute to creating the best products for dedicated golfers worldwide. Here, your performance has purpose. What You Will Be Doing: Titleist is seeking a passionate and driven Associate Research Engineer to help shape the future of golf club performance through innovation, engineering, and data-driven design. In this role, you will apply engineering principles, scientific methods, and advanced computational tools to explore emerging technologies, analyze golf club designs and biomechanical swing dynamics, and validate concepts that contribute to next-generation Titleist products. Working alongside world-class researchers, engineers, and product designers, you will leverage modeling, simulation, and testing techniques to solve complex design challenges and uncover new opportunities for performance advancement. You'll collaborate across Research, Design, Product Development, Testing, Manufacturing, Sales, and Marketing to evaluate concepts, support product innovation, and translate technical findings into meaningful product improvements. This is a unique opportunity to deepen your expertise in golf club research and development, contribute to patentable technologies, and play a direct role in creating the high-performance products trusted by golfers around the world. What You Bring: Bachelor’s degree in Mechanical Engineering, Engineering, Computer Science, or a related field required. Strong foundation in engineering analysis, problem-solving, and product development. Experience with MATLAB and/or Python required. Exposure

ROLE SUMMARY We are seeking a highly motivated individual to join our high content imaging lab within the Discovery Biology and Pharmacology (DBP) group at the vibrant Groton campus in Connecticut. DBP is responsible for hit-identification, lead optimization, and molecular characterization of our small molecules and has teams focused on high-throughput screening, DNA-encoded libraries, pharmacology, protein homeostasis platforms, cellular models, functional genomics, and high-content imaging. The group is highly integrated with other groups in Medicine Design including Chemists, Structural Biologists, and Computational Scientists, and supports the small molecule portfolio across multiple therapeutic areas. The individual in this role will bring in rich experience in high content imaging and high throughput flow cytometry, and apply them to support our diverse small molecule portfolio spanning various therapeutic areas. ROLE RESPONSIBILITIES High-content imaging assay design, development, and optimization: Apply a broad range of imaging and flow cytometry assay technologies to address project needs. Independently develop, optimize, and troubleshoot high-content imaging and flow cytometry assays. Imaging data analysis and interpretation: Design and implement advanced image-analysis workflows, build complex analysis algorithms, and streamline data processing to support medium- to high-throughput screening. Translate imaging data into clear, actionable biological insights. Imaging infrastructure management and continuous improvement: Partner with team experts to support high-content imaging and flow cytometry instrumentation, implement software solutions that enable advanced imaging applications and data analysis, and continuously improve ima

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview: Freddie Mac’s Investments & Capital Markets Division is seeking a Quantitative Analytics Senior to develop, implement, monitor, and execute quantitative models that support counterparty credit risk management, fixed-income derivatives valuation, and related business and risk management decisions. The candidate should be self-motivated, has a strong quantitative and computational background, and communicates effectively with technical and business stakeholders. As part of the Models & Analytics team, this role will primarily support Freddie Mac’s Counterparty Credit Risk Management and Asset-Liability Management functions, with responsibilities spanning model development, implementation, monitoring, data processes, documentation, and business user support. Our Impact: This role focuses on the design, development, implementation, and monitoring of quantitative models and analytics that support counterparty credit risk, exposure measurement, derivatives valuation, and related risk management activities. The models and analytics developed by the team provide key inputs into counterparty credit risk management, portfolio management, business reporting, and risk-informed decision-making across the division. Your Impact: • Develop, implement, and maintain quantitative models primarily for counterparty credit risk measurement, with additional coverage of interest rates, derivatives valuation, and valuation components related to mortgage products. • Implement models and analytics using programming languages and tools such as MATLAB,

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview: Freddie Mac’s Investments & Capital Markets Division is currently seeking a Quantitative Analytics Senior to be responsible for the creation, development, and execution of analytic models used to value Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) of various types of financial institutions. The candidate should be self-motivated, have a strong computational background, and effective communication skills. Under the Models & Analytics team, the candidate will support models primarily utilized by Freddie Mac’s Counterparty Credit Risk Management Team. The key focus is on credit risk scorecard modeling, but the tasks may also include LGD and EAD models. The position encourages continued learning and development across other modeling areas, including market risk capital, operational loss forecast, prepayment and default, and rates and derivatives . Our Impact: Key focus of this job is the design, development, and implementation of counterparty credit risk models for a variety of financial institutions, with primary focus on Probability of Default modeling. These models support multiple corporate and divisional objectives by providing key inputs into counterparty credit risk management, both at individual counterparty and portfolio levels. Y our Impact: Design, code and maintain consistent counterparty credit risk models (PD/LGD/EAD). These models must incorporate best practices while simultaneously accounting for the

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. In the Technology Development — Advanced Modeling & AI Solutions (AMAIS) organization, you will be part of a multidisciplinary team developing next-generation Digital Twins, predictive modeling solutions, and AI-driven technologies that accelerate advanced memory development and manufacturing excellence. You will create predictive digital representations of semiconductor processes, materials, structures, equipment, and products across DRAM, NAND, and advanced packaging technologies including HBM. Leveraging physics-based modeling, computational methods, machine learning, GenAI, large language models (LLMs), and agentic AI frameworks, you will enable technology co-optimization, design-space exploration, process optimization, yield improvement, and accelerated technology learning. Working at the intersection of engineering fundamentals, manufacturing data, and digital engineering, you will develop scalable predictive and prescriptive solutions that connect process, structure, performance, yield, reliability, and cost. This role offers the opportunity to influence critical technology decisions, drive fab-technology co-optimization , and advance Micron's leadership in data-driven semiconductor memory innovation. Qualifications: Independence – be comfortable executing activities and needs Experience in algorithm development, numerical methods, and scientific computing Solid experience with Plasma, FPM, HAR etching, and MC modeling Experience with Wet Pr

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the team Anthropic's Life Sciences team is building a world-class research group focused on making fundamental biological discoveries. The team combines cutting-edge AI with hands-on biological research, positioning Anthropic at the forefront of AI-accelerated scientific discovery. About the role We're seeking an exceptional Research Scientist to join the team. As a founding member of Life Sciences, you'll work in a high-impact group that operates at the intersection of computational and experimental biology. You'll help establish Anthropic as a leader in biology research while developing product intuition through direct engagement with the challenges and opportunities of laboratory science. Key responsibilities Design, execute, and iterate on the experimental programs at the core of the team's research: molecular biology, biochemistry, protein and nucleic acid characterization, high-throughput functional screens, and the assay development that makes new questions answerable Partner directly with computational biologists to design experiments that produce high-quality, analysis-ready data, and feed results back fast enough to immediately inform the next round of analysis Generate and prioritize hypotheses by combining your experimental judgment with the literature, curated biological knowledge bases, and the team's computational predictions Use Claude and our internal agent frameworks heavily in your own work — for experimental planning, protocol development, and data interpretation — and feed what you learn back to the model-improvement and product teams as evaluations, datasets, and concrete failure cases Minimum qualification

Be the visionary Perception Architect designing the sensory "nervous system" for our next generation of autonomous products. Evolve our end-to-end perception architecture, serving as the essential liaison between Sensing teams and the core ML system. Drive architectural evolution toward next-generation sensing and compute platforms by influencing Hardware-Software Co-Design. In this role, you will: System Synthesis: Define the end-to-end perception architecture—assess new sensing (LiDAR, Radar, Camera) to the final fused world model. Hardware-Software Co-Design: Partner with Compute and Sensing teams to influence the design, ensuring our algorithms have the "computational oxygen" they need. Algorithmic Strategy: Lead the transition from current pipelines to AI innovation pipelines, while maintaining the safety and interpretability required for edge deployment. Future-Proofing: Evaluate emerging technologies and determine their viability for the 3-5 year roadmap. Performance Budgeting: Collaborate on rigorous metrics for latency and accuracy across diverse edge-computing environments. Lead cross functional teams: to create a viable plan to move to new platforms and unlock further technical capabilities for Perception systems. Coordinate projects across partner teams to make sure work is aligned with the overall org direction. Qualifications Education: Ph.D. or MS in Computer Science, Robotics, Electrical Engineering, or a related field with a focus on Computer Vision . Experience: 8+ years in autonomous systems with at least 2 years in an architectural role , shipping and evolving perception systems Deep Domain Expertise: Mastery of systems focused on Computer Vision, De

We are looking for a Software Developer , preferably with commercial experience in low and ultra-low latency projects to join our dynamic team. The ideal candidate will demonstrate intelligence, steadiness, and thoughtfulness, with strong attention to detail and a passion for streamlining business processes. They should be naturally curious, approach problems with a continuous improvement mindset, and remain flexible in seeking ever-better solutions. WHAT YOU’LL BE DOING: Implementation of complex computational algorithms on GPU and CPU with demanding latency and throughput requirements Refactor existing solutions to improve their scalability WHAT WE LOOK FOR IN YOU: Commercial experience in developing and debugging high-performance GPU and CPU applications with strong focus on latency and throughput Hands-on experience with third-party libraries and designing custom CUDA kernels Proficient with profiling and performance analysis tools (Nsight Systems, Nsight Compute, nvprof) Solid understanding of data structures, algorithms, and object-oriented programming in C++ Proven ability to work effectively in remote or hybrid teams with variable, project-based responsibilities Curiosity and proactive engagement with emerging trends in GPU/HPC/ML, continuously seeking to learn and apply new techniques NICE-TO-HAVE: In-depth knowledge and expertise in low-latency and real-time development, achieving sub-microsecond latency Experience with lock-free data structures and associated design patterns Proficient in C programming, including writing Linux drivers and working with kernel-level components Strong understanding of Linux system internals and networking Knowledge of memory optimization techniques (shared memory, registers, coalesced access, persistent kernels) Experience with inference optimization frameworks WHY SHOULD YOU JOIN OUR TEAM? Great challenges with fast feedback loops A welcoming group of highly qualified international professionals Cutting-edge hardware and te

About the Team The Frontier Systems team at OpenAI builds, launches, and supports the largest supercomputers in the world that OpenAI uses for its most cutting edge model training. We take data center designs, turn them into real, working systems and build any software needed for running large-scale frontier model trainings. Our mission is to bring up, stabilize and keep these hyperscale supercomputers reliable and efficient during the training of the frontier models. About the Role As a Software Engineer on the Frontier Systems team focused on power management, you will work on critical infrastructure to support cutting-edge research. With large-scale supercomputers consuming substantial amounts of power, managing this efficiently is key to maximizing computational capacity. This role is critical to ensuring that our cutting-edge research supercomputing infrastructure runs smoothly, while maintaining reliability and grid-level power stability. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Develop and implement system-level and software-level solutions to optimize power usage in large-scale supercomputers, ensuring efficient and reliable operations. Build automation to monitor power consumption patterns during training workloads and design algorithms to stabilize these fluctuations, preventing issues with grid reliability. Work with researchers and engineers to design tools for real-time monitoring, detection, and remediation of power-related hardware and system faults. Collaborate cross-functionally to translate complex electrical system requirements into code, while driving continuous improvements in power man

Become a part of our caring community The Care Management Support Assistant contributes to administration of care management. Provides non-clinical support to the assessment and evaluation of members' needs and requirements to achieve and/or maintain optimal wellness state by guiding members/families toward and facilitate interaction with resources appropriate for the care and wellbeing of members. The Care Management Support Assistant performs basic administrative/clerical/operational/customer support/computational tasks. Typically works on routine and patterned assignments. The Care Management Support Assistant will review inbound referrals and correspondence for processing, fulfilment or resolution utilizing all appropriate software systems and resources. Screen physician’s orders and documentation to identify that all qualifying medical documentation and required information is included. When necessary, request additional applicable information from referring entity. Perform verification of benefits coverage and eligibility for services per Health Plan contract. Review referral data matching it against specified medical terms and diagnoses or procedure codes and follow established procedures for approving request or referring request for further review. Provide referral management education to members and providers regarding medical benefits, referral status and prior authorizations. Communicate with patient to confirm demographics and explain the details of the services/care requested. Coordinate the timely delivery of care and services with providers. Also communicate with referring entities, providers, and members regarding final referral determination while maintaining detailed documentation to record patient, physician, referral source and provider interactions and communications. Work with Pre-Authorization, Utilization Management, Billing, Pharmacy, and Home Care r