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Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work-work that changes the world-is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Despite the "Engineer" title, this isn't a typical back-end coding job. This is a pre-sales and architectural advisory role for someone who is part scientist, part consultant, and part communicator. At the Staff / Principal level, you are expected to be a hybrid heavy hitter - someone who can talk shop with PhD data scientists and then walk into a boardroom and explain the ROI to a CEO. We aren't looking for your average expert. We're building a team of T-shaped professionals with: Deep Technical Roots - You know PyTorch, Kubernetes, and GPU clusters (NVIDIA/AMD) inside and out, and you know when XGBoost is a better choice than the latest frontier model. Broad Business Acumen - You understand verticals, e.g. how a hospital's AI needs differ from a hedge fund's, and can navigate both conversations with credibility. Collaborative Autonomy - With a global remit and potential for 30-60% travel, you are in charge of driving results within diverse collaborations. We're building a small, global Applied AI team to work directly with enterprise customers and partners - helping them turn AI ambitions into production outcomes on Pure's platform. This team brings genuine research and production depth to customer-facing engagements: leading technical advisory sessions, shaping AI strategy for some of the world's largest companies, and contributing to Pure's growing reputation in AI through publications, conferences, and thought leadership. The team also ensures Pure's account teams can effectively qualify and position AI advisory opportunities across their territories, and provides enablement to our internal field and channel partner communities. The role requires working cross-functionally across Solutions, Marketing, Alliances, Engineering, Enablement, and Sales to align initiatives and go-to-market campaigns - all while maintaining genuine technical depth in enterprise AI. If this sounds like you, come join one of the most exciting teams at Pure. WHAT YOU'LL DO: Lead technical discovery and advisory engagements with customers to identify high-value AI use cases relevant to their industry and data Advise on end-to-end AI deployment - model selection, training/fine-tuning strategies, inference optimization, data pipeline design, and evaluation/alignment/safety frameworks - optimized for Pure's platform Collaborate cross-functionally to qualify and position AI opportunities, and develop proof-of-value prototypes that translate technical performance into business outcomes Create AI enablement content for field teams, partners, and customers - technical walkthroughs, qualification guides, workshops, and vertical-specific use case frameworks Present at industry conferences, publish technical content and peer-reviewed research, and represent Pure in engagements with strategic technology partners (NVIDIA, AMD, cloud providers, MSPs) Operate autonomously in ambiguous environments - independently scoping high-impact initiatives and driving them to completion at the right pace WHAT YOU BRING: Advanced degree in a quantitative field (Computer Science, Physics, Mathematics, Engineering, or related), or equivalent demonstrated through publications and production system experience 8+ years building and deploying AI/ML systems in cloud or on-prem environments Deep expertise in modern AI/ML - large language models, distributed training, inference optimization, agentic systems, evaluation/alignment frameworks, and classical ML Fluency with the modern AI stack (PyTorch, vLLM, Ray, Kubernetes) and data platforms (Spark, Snowflake, Kafka, etc.) Able to scope and carry out research projects that support critical business objectives, both independently and collaboratively Excellent written, verbal, and presentation skills - equally clear with hands-on data scientists and C-suite decision-makers WHAT SETS YOU APART: Experience with large-scale AI infrastructure: GPU clusters, high-performance storage, containerized deployments Experience in customer-facing technical advisory or consulting roles with enterprise accounts Experience leading independent, multi-year research from concept to publication or large-scale production deployment Exposure to multiple industry verticals (financial services, healthcare, telco, manufacturing) Publication record, conference presentations, or recognized technical presence Background combining applied research with shipping production systems Familiarity with CRM/opportunity management systems (Salesforce preferred) Salary ranges are determined based on role, level and location. For positions open to candidates in multiple geographical locations, the base salary range is reflective of the labor market across the applicable locations. This role may be eligible for incentive pay and/or equity. There is no application deadline and we accept applications on an ongoing basis until the job is filled. The annual base salary range is: $171,500 - $257,600 USD WHAT YOU CAN EXPECT FROM US: Innovation : We celebrate those who think critically, like a challenge, and aspire to be trailblazers. Growth : We give you the space and support to grow along with us and to contribute to something meaningful. We have been named Fortune's Best Workplaces in Technology , Fortune's Best Workplaces in the Bay Area , and certified as a Great Place to Work ! Team : We build each other up and set aside ego for the greater good. And because we understand the value of bringing your full and best self to work, we offer a variety of perks to manage a healthy balance, including flexible time off, wellness resources, and company-sponsored team events. Check out for more information. ACCOMMODATIONS AND ACCESSIBILITY: Candidates with disabilities may request accommodations for all aspects of our hiring process. For more on this, contact us at if you're invited to an interview. OUR COMMITMENT TO A STRONG AND INCLUSIVE TEAM: We're forging a future where everyone finds their rightful place and where every voice matters. Where uniqueness isn't just accepted but embraced. That's why we are committed to fostering the growth and development of every person, cultivating a sense of community through our Employee Resource Groups and advocating for inclusive leadership. Everpure is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or any other characteristic legally protected by the laws of the jurisdiction in which you are being considered for hire. Join us and bring your best. Bring your bold. Pure and simple.

Annapurna Labs was a startup company acquired by AWS in 2015, and is now fully integrated. If AWS is an infrastructure company, then think Annapurna Labs as the infrastructure provider of AWS. Our org covers multiple disciplines including silicon engineering, hardware design and verification, software, and operations. AWS Nitro, ENA, EFA, Graviton and F1 EC2 Instances, AWS Neuron, Inferentia and Trainium ML Accelerators, and in storage with scalable NVMe, are some of the products we have delivered, over the last few years. AWS Neuron is the complete software stack for the AWS Inferentia and Trainium cloud-scale machine learning accelerators and the Trn1 and Inf1 servers that use them. This position is for a Software Engineer that will lead the development of machine learning tools to run, optimize, and analyze machine learning workloads. This candidate must have had experience leading machine learning tool projects, preferably starting from architecture through several generations of delivery to customers. Deep knowledge of profiling and optimization, resource management, scheduling, code generation are needed. The ideal candidate will have worked on new instruction set architectures, which may include CPU, NPU, GPU and other forms of compute. Key job responsibilities This engineer will lead the design and implementation of ML infrastructure platform, building systems for capacity management, workload scheduling, and fleet orchestration across ML accelerators. They will work with ML scientists, training infrastructure engineers, hardware teams, and internal customers to ensure the ML Infra service delivers seamless ML Accelerator access with low wait times, high utilization, and zero-config deployment from various environments. A day in the life As you design and code solutions to help our team drive efficiencies in software architecture, you'll create metrics, implement automation and other improvements, and resolve the root cause of software defects. You'll also: Build high-impact solutions to deliver to our large customer base. Participate in design discussions, code review, and communicate with internal and external stakeholders. Work cross-functionally to help drive business decisions with your technical input. Work in a startup-like development environment, where you're always working on the most important stuff. About the team High-impact, high-visibility: You'll directly accelerate every Neuron team's ability to ship - your work multiplies the output of 100+ engineers Greenfield opportunities: We're actively building new capabilities with significant design ownership for SDEs Small, senior team: where every person owns major components and drives architectural decisions AI infrastructure: Work at the intersection of Kubernetes, custom silicon, and large-scale ML workloads Diverse Experiences We value diverse experiences and non-traditional career paths. If your career is just starting or includes alternative experiences, we encourage you to apply. Inclusive Team Culture Our employee-led affinity groups foster inclusion. Events like CORE and AmazeCon inspire us to embrace our uniqueness. Work/Life Balance We strive for flexibility as part of our working culture, supporting you both at work and at home. Mentorship & Career Growth We offer knowledge-sharing, mentorship, and one-on-one code reviews to help you grow as a professional. Hybrid Work This role is onsite, with flexibility to work remotely when you're unable to make it into the office. BASIC QUALIFICATIONS - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience programming with at least one software programming language PREFERRED QUALIFICATIONS - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Bachelor's degree in computer science or equivalent - Experience taking a leading role in building complex software or computing infrastructure that has been successfully delivered to customers - Experience with AWS Services including EC2, Lambda, S3, DynamoDB, SQS - Experience in Kubernetes, Docker or containers ecosystem, or experience managing full application stacks from the OS up through custom applications and experience in any Bigdata architecture - Experience with version control systems and CI/CD pipeline implementation - Strong proficiency in Go/Java, Python, and Javascript/Typescript - Application and kernel performance profiling and optimization - Proficiency in integrated software/hardware performance analysis and optimization - Experience designing and operating production services Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, WA, Seattle - 143 400.00 USD annually

Job description: We are seeking a talented, tenacious, results driven individual to work in a multi-disciplinary R&D environment with likeminded motivated electrical engineers, mathematicians, and computer scientists who are collectively responsible for creating custom geolocation and digital communications systems in support of national security defense. Core responsibilities include creative problem solving, researching or inventing advanced geolocation algorithms, implementing them in efficient software, testing with real-world data, and deploying to front-line customer facilities. Our dynamic environment and diverse projects demand flexibility to learn new technologies quickly. Our personnel can expect to work across all functional areas: systems engineering, development, integration and test, deployment and O&M. Core responsibilities include: Design/architect, develop, test, deploy, and operate fully integrated software Design, build, and maintain infrastructure for modern integration between our applications and third-party services Collaborate extremely effectively with product managers, designers, other engineers, stakeholders, and vendors on projects within the team. Communicate technical ideas and work closely with other senior members of the team. You will also provide technical leadership and guidance to junior team members and mentor others to grow in their technical abilities. A key responsibility is staying up-to-date with the latest technologies, tools, and methodologies and experimenting with new technologies to incorporate innovative solutions into our projects. Our personnel can expect to work across all functional areas: systems engineering, development, integration and test, deployment and O&M, and experience the direct mission feedback from the customer and seeing your project provide real-world contributions that make a significant difference. Youre encouraged and expected to propose things that you believe will improve the applications and frameworks youre working in. The ability to work unsupervised with minimal direction and the ability to self-start is a must. What required background will make you successful? Expert knowledge of data structures, algorithms, and modern design patterns and data layers Expert knowledge of Golang Passion to build internal solutions and own development of enterprise-wide applications Extensive knowledge of building quality APIs for internal and external products Extensive experience integrating internal and third-party services into your solution Highly proficient in modern software engineering practices for testability and readability Demonstrated ability to design the architecture of software systems to ensure they achieve functionality, performance, scalability, and maintainability requirements Degree (Bachelor's, Master's, or PhD) in Computer Engineering or Computer Science Minimum 15 years' experience in software engineering-related discipline Active TS/SCI security clearance US CITIZENSHIP REQUIRED Preferred skills: Experience providing technical leadership and guidance to junior team member and mentoring other engineers to grow in their technical abilities Highly proficient in C++ and Python for engineering and scientific applications in LINUX environments Knowledge of cloud computing platforms like Amazon Web Services (AWS) Knowledge of Javascript and web technologies such as VueJS or React Experience automating workflows across the enterprise DevOps and Cloud computing Experience (Gitlab, CI/CD, CVE mitigations, Docker, Kubernetes, PIP) Agile development processes and leadership Full relocation provided Remote work/telework is not available for this position. Qualifications: What required background will make you successful? Expert knowledge of data structures, algorithms, and modern design patterns and data layers Expert knowledge of Golang Passion to build internal solutions and own development of enterprise-wide applications Extensive knowledge of building quality APIs for internal and external products Extensive experience integrating internal and third-party services into your solution Highly proficient in modern software engineering practices for testability and readability Demonstrated ability to design the architecture of software systems to ensure they achieve functionality, performance, scalability, and maintainability requirements Degree (Bachelor's, Master's, or PhD) in Computer Engineering or Computer Science Minimum 15 years' experience in software engineering-related discipline Active TS/SCI security clearance US CITIZENSHIP REQUIRED Preferred skills: Experience providing technical leadership and guidance to junior team member and mentoring other engineers to grow in their technical abilities Highly proficient in C++ and Python for engineering and scientific applications in LINUX environments Knowledge of cloud computing platforms like Amazon Web Services (AWS) Knowledge of Javascript and web technologies such as VueJS or React Experience automating workflows across the enterprise DevOps and Cloud computing Experience (Gitlab, CI/CD, CVE mitigations, Docker, Kubernetes, PIP) Agile development processes and leadership Full relocation provided Remote work/telework is not available for this position. Why is This a Great Opportunity: We are seeking a talented, tenacious, results driven individual to work in a multi-disciplinary R&D environment with likeminded motivated electrical engineers, mathematicians, and computer scientists who are collectively responsible for creating custom geolocation and digital communications systems in support of national security defense. Salary Type : Annual Salary Salary Min : $ 160000 Salary Max : $ 260000 Currency Type : USD

Job Description Job Description Our mission is to create the Experience of a Lifetime for our employees, so they can, in turn, create the Experience of a Lifetime for our guests. We own and operate the most renowned destination resorts in the world as well as regional and local ski areas outside major cities, and connect them all through one unrivaled network. We are looking for ambitious leaders, innovators and creators to join our talented team. If you're ready to pursue your fullest potential, we want to get to know you! Candidates for year-round positions are reviewed on a rolling basis. Applications will be accepted up to 90 days after the posting date, or until the position is filled (whichever is first). Job Summary: We are looking for a curious, driven, innovative machine learning engineer who takes initiative to solve problems and create environments that accelerate the development, deployment, and usage of data science models and AI to drive greater organizational impact. The Data Science & Data Engineering team within the Enterprise Analytics organization builds data assets, predictive models, analytical applications, and platforms across the organization. Our team collaborates with business stakeholders, analysts, and technology teams to tackle high-impact use cases with state-of-the-art models and tools to grow the business, streamline costs, and improve guest experiences. Job Specifications: Starting Wage: $140,000 - $185,000 + Annual Bonus Employment Type: Year Round Shift Type: Full Time hours Minimum Age: At least 18 years of age Housing Availability: No Job Responsibilities: Productionize ML models developed by data science into reliable, monitored, maintainable systems. Build model data foundations that ensure training, inference, monitoring, and analytics data are trustworthy and scalable. Architect ML platform patterns in Databricks that bring reliability, consistency, governance, performance, and cost discipline to ML and data workflows. Identify and scope opportunities for ML engineering across the business for high-impact. Develop reusable tools , libraries, standards, documentation, and production-readiness practices to enable data science and data engineering teams. Develop analytical and model-powered applications that turn data and ML outputs into usable business workflows for end users. Prepare the platform for future AI engineering , including LLM and agent-based systems, as the organization matures. Provide technical leadership and mentoring across engineering, architecture, and development including design and code reviews. Job Requirements: Technical Skills: Quantitative Foundation : B.S. degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Economics, Operations Research, Engineering). Software Engineering Fundamentals: write clean, modular, testable, maintainable code and understand how to structure production-grade systems rather than one-off notebooks or scripts. Python and SQL Proficiency: strong in Python and SQL for building data pipelines, automation, model integrations, analytical workflows, and production services. Data Modeling and Pipeline Design: understand how to design reliable, well-structured data assets, including curated tables, feature datasets, batch pipelines, orchestration, data quality checks, and lineage. ML Lifecycle Fluency: understand the full model lifecycle: data collection, exploration, model development, validation, deployment, monitoring, retraining, and retirement. Production ML Patterns: understand core MLOps patterns such as model registries, feature/data versioning, reproducible environments, testing/validation, monitoring, and rollback. Cloud and Platform Engineering: You are comfortable working in cloud-based data and ML environments and understand the foundations of permissions, environments, jobs, services, storage, networking, and cost-aware architecture. Databricks Expertise : You're familiar and experienced with the core parts of Spark, Unity Catalog, Delta Lake, Databricks Workflows, MLflow, model registry patterns, job/cluster optimization, and governance. DevOps Practices: You use modern engineering practices such as Git, CI/CD, automated testing, code review, dependency management, environment management, and observability. Application Development : You can build applications, APIs, dashboards, or workflow tools that sit on top of data and model outputs. System Design: You can reason through tradeoffs across reliability, latency, scale, cost, governance, maintainability, and ease of use. Soft Skills: Curious : bring intellectual curiosity, an inquisitive nature, and a desire to deepen your knowledge and continue learning. Ownership : take responsibility to proactively advance projects, contribute to the organization, and develop the best solutions. Communication: explain technical concepts, risks, tradeoffs, and recommendations clearly to technical and non-technical audiences. Collaboration: work effectively cross-functionally with data scientists, data engineers, analysts, application engineers, product partners, and business stakeholders. Pragmatism : You know how to balance ideal architecture with business urgency, team maturity, operational constraints, and the need to ship. Preferred qualifications: A graduate degree (Masters or PhD) in a quantitative field Experience with dbt (Core) for modular data modeling, including testing, documentation, and dependency management Experience with AI engineer to use, build, and monitor agentic solutions The expected Total Compensation for this role is $140,000 - $185,000 + Annual Bonus. Individual compensation decisions are based on a variety of factors. Job Benefits Ski/Mountain Perks! Free passes for employees, employee discounted lift tickets for friends and family AND free ski lessons MORE employee discounts on lodging, food, gear, and mountain shuttles 401(k) Retirement Plan Employee Assistance Program Excellent training and professional development Full Time roles are eligible for the above, plus: Health Insurance; Medical Insurance, Dental Insurance, and Vision Insurance plans (for eligible seasonal employees after working 500 hours) Free ski passes for dependents Critical Illness and Accident plans Employees can work remotely from British Columbia, Washington D.C., and the 16 U.S. states in which we currently operate. This includes: California, Colorado, Indiana, Michigan, Minnesota, Missouri, New Hampshire, New York, Nevada, Ohio, Pennsylvania, Utah, Vermont, Washington State, Wisconsin, and Wyoming. Please note that the ability to work in person or off-site, and the particulars related to such work, are subject to change at any time; and, accordingly, the Company reserves the right to change its policies and/or require in-person/in-office work or off-site work at any time in its sole discretion. In completing this application, and when submitting related documentation, applicants may redact information that identifies their age, date of birth, and/or dates of attendance at or graduation from an educational institution. We follow all federal, state, and local laws including restrictions on child/minor labor. Minors hired into this position will not be asked or permitted to engage in any activities restricted to adult workers. Vail Resorts is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veteran status or any other status protected by applicable law. Requisition ID 517322 Reference Date: 09/05/2026 Job Code Function: Data Science

National Radio Astronomy Observatory Title: Software Engineer II-III Location: 1011 Lopezville Rd, Socorro, NM 87801, USA• 5651 Balloon Fiesta Pkwy, Albuquerque, NM 87113, USA• 155 Observatory Rd, Green Bank, WV 24944, USA Requisition Number: 279 Job Family: Software Engineer Pay Type: Salary Required Education: CPP Position Description: Position Summary The National Radio Astronomy Observatory (NRAO) is a prestigious research and development organization that plays a vital role in the study of the universe. Associated Universities, Inc. (AUI) is a nonprofit organization that manages and operates the NRAO under a cooperative agreement with the National Science Foundation. The Observatory is a hub for technological and scientific collaboration, operating state-of-the-art radio telescope facilities for use by the international scientific community. The Observatory has been instrumental in the study of black holes, galaxies, and the early universe. NRAO is seeking an experienced Software Engineer to join the Online Software Group. The online system is the real-time heart of our observing software. It is responsible for configuring, controlling, and monitoring the real-time systems of our telescopes, including the the Very Large Array (VLA) in New Mexico, the Very Long Baseline Array (VLBA) spread across the US and its territories, and the Green Bank Telescope (GBT) in West Virginia. This software is responsible for taking scientific-domain configuration parameters and decomposing them into the hardware settings and motion commands required by our antennas, and into the corresponding configurations for the associated digital signal processing instruments (e.g. VEGAS for the GBT, and correlators for the VLA and the VLBA). When an observation runs, this software is what makes it happen. This position will be based in Albuquerque, NM, Socorro, NM, Charlottesville, VA or Green Bank, WV. For well-qualified candidates, a remote work arrangement may be considered. What You Will be Doing Designing, implementing, testing, and maintaining components of the online software that configure and control the VLA, VLBA, and GBT in real time. Develop and extend the translation layer that decomposes scientific-domain observing parameters into the engineering parameters the hardware understands: IF-chain configurations, antenna motion commands, and digital signal processing configurations for instruments like VEGAS, WIDAR, and DiFX. Model the observing domain in software - frequency setups, subband and baseband layouts, polarization products, timing and integration structure - and implement the rules, constraints, and legality checks that determine which configurations are achievable on which instrument. Work from interface control documents and hardware specifications, in close collaboration with the engineers and scientists who own the underlying subsystems, to ensure the commands the online system emits are correct and complete. Diagnose and resolve issues that span the layers between a scientist's observing specification and the command stream sent to the telescope, often in collaboration with telescope operators, engineers, and scientific staff. Support the evolution of the online system to meet new observing paradigms and instrumentation, including work that informs and feeds into the next generation Very Large Array (ngVLA). Write and maintain critical documentation, including requirements, software design documents, interface control documents, and user documentation. Participate in code review, testing, and release processes for software that runs mission-critical, 24/7 scientific facilities. Work Environment The successful candidate will join a team of professionals engaged in research and development in the fields of science, engineering, software development, and education. Work is typically performed in a research or development environment. Must be able to operate a personal computer. Occasional travel (domestic and international) may be required. Who You Are: Education A Bachelor's degree in computer science, engineering, scientific or related field; highly relevant experience may be considered in lieu of a Bachelor's degree. While not required, you may have an advanced degree in a related field. Experience One or more years of experience developing software applications. Candidates with progressively more experience will be considered for a higher-level position ranking. Relevant experience with radio astronomy operating software and procedures is preferred. Knowledge of radio astronomy theories and practice would be valuable. Demonstrated experience providing technical leadership of complex data acquisition, scheduling, and operational support systems is preferred. Skills and Competencies Proficiency with Java; familiarity with C/C++ and Python is valuable A solid understanding of object-oriented design and development Demonstrated ability to learn and apply new software languages and unfamiliar domains Understanding of networking concepts and technologies: multicast, TCP, UDP, HTTP, XML, JSON, REST Experience with version control software, testing methodologies, and CI/CD Strong interpersonal and communication skills, including the ability to work effectively with scientists and hardware engineers Comfort working in a Linux (RHEL) environment The following are highly preferred: Experience translating high-level domain concepts into machine- or hardware-level representations - compilers, planners, schedulers, configuration engines, or similar systems that turn intent into instructions Skill in domain modeling and in expressing complex validation rules and constraints clearly in code Experience with distributed systems, or with control and monitoring software for scientific, industrial, or other physical instruments A working comfort with mathematics and unit-bearing quantities - coordinate transformations, frequency and time calculations, and the care required to get them right Familiarity with signal processing concepts, digital IF chains, or correlator architectures Familiarity with basic astronomical principles, radio astronomy, or interferometry Experience collaborating in an Agile/Scrum environment, including sprint planning, estimating tasks, and breaking down requirements into user stories Note that this position does not involve direct hardware or firmware development; though an understanding of these systems and real-time control principles can be valuable. Your work will live at the layer above, producing correct hardware-level configurations and commands from scientific intent, against interfaces defined and maintained by others. Additional Requirement Observatory employees must be authorized to work in the United States. The Observatory presently cannot sponsor H-1B Visas for this position. Total Rewards: Compensation The starting salary of this position is between $87,000 and $121,000. Factors which may affect starting pay within this range may include; education, experience, skills, competencies, other qualifications of the successful candidate, as well as internal equity and labor market conditions. Benefits: Associated Universities, Inc (AUI) offers a comprehensive benefits package addressing the needs of employees and their families with most benefits beginning on the first day of employment, subject to eligibility requirements. AUI provides: Excellent paid time off (13 holidays, annual accrual of up to 24 vacation days) Medical, dental and vision plans are effective on the first day of employment. AUI's retirement benefit contributes an amount equal to 10 percent of a qualified participant's base pay with no required employee contribution. Click Total Rewards for more information. Application Instructions: Select the "Apply" button above. Please be prepared to upload your current CV/Resume and a cover letter describing interest and suitability for the position . Equal Opportunity Employer Statement: AUI is an equal opportunity employer. To view our complete statement, please visit . If you require reasonable accommodation for any part of the application or hiring process, you may submit your request by sending an email to . PM20 Compensation details: 00 Yearly Salary PIf669a7c2591a-1646

What Makes a Honda, is Who makes a Honda Honda has a clear vision for the future, and it's a joyful one. We are looking for individuals with the skills, courage, persistence, and dreams that will help us reach our future-focused goals. At our core is innovation. Honda is constantly innovating and developing solutions to drive our business with record success. We strive to be a company that serves as a source of "power" that supports people around the world who are trying to do things based on their own initiative and that helps people expand their own potential. To this end, Honda strives to realize "the joy and freedom of mobility" by developing new technologies and an innovative approach to achieve a "zero environmental footprint." We are looking for qualified individuals with diverse backgrounds, experiences, continuous improvement values, and a strong work ethic to join our team. If your goals and values align with Honda's, we want you to join our team to Bring the Future! Job Purpose The Data and Solution Architect is responsible for defining, governing, and advancing the enterprise data architecture required to enable scalable, trusted, and responsible AI solutions in the AI Hub. This role ensures that data platforms, models, standards, and semantic structures are designed to support AI/ML, Generative AI, Agentic AI, experimentation (POCs), and production deployment, while aligning with enterprise data governance, security, and compliance requirements. Key Accountabilities AI Ready Data Architecture & Design Lead the design of logical, physical, and semantic data architectures to support AI, advanced analytics, GenAI and Agentic AI use cases Define AI ready data models, feature oriented structures, and analytics ready data assets aligned to enterprise data platforms Ensure architectural alignment between data platforms, AI tooling, and MLOps pipelines Support design and governance of the Foundry Ontology layer as the enterprise semantic backbone for AI use cases Data Standards, Governance & Semantics Work closely with Data Architecture and Governance teams, define and enforce data standards, metadata practices, naming conventions, and master/reference data patterns for AI use cases Establish and maintain semantic consistency (business definitions, critical data elements, feature definitions) to enable explainable and reusable AI Partner with Data Governance, Legal, and Compliance teams to ensure responsible and compliant AI data usage AI Use Case Enablement & POC Support Architect data flows and patterns supporting AI POCs, experimentation environments, and sandbox platforms Guide data sourcing, profiling, and readiness activities for AI Data Scientists, Data and AI Engineers Own the data architecture stage-gate process across POC, expanded pilot, and production phases; define and maintain AI-readiness scorecards to assess data asset maturity at each stage Data Platform, Integration and Solution Architecture Architect integrations across source systems, data platforms, analytics tools, and AI services Evaluate and onboard new data sources and technologies to meet evolving AI requirements Define reference architecture and architectural guardrails for cloud, hybrid, and global deployments Lead/support solution architecture development for projects/products, where necessary Collaboration, Review & Enablement Serve as a data and solution architecture authority for AI related initiatives and design reviews Mentor junior architects, data engineers and provide architectural guidance to delivery teams Contribute to AI Hub (COE), communities of practice, standards bodies, and architecture review forums Qualifications, Experience, and Skills Bachelor's degree in Computer Science, Information Systems, Data Engineering/ Data Science, or related field 8+ years of experience in data architecture, solution architecture, enterprise data platforms, or analytics architecture Demonstrated experience supporting AI/ML, advanced analytics, or data driven product initiatives Experience operating in federated governance or hub and spoke operating models Experience with data profiling and data quality management Workstyle This is an onsite job. One remote workday per week, may be possible with prior departmental approval. Visa sponsorship issues This position is not eligible for work visa sponsorship What differentiates Honda and makes us an employer of choice? Total Rewards: Competitive Base Salary (pay will be based on several variables that include, but not limited to geographic location, work experience, etc.) Regional Bonus (when applicable) Manager Lease Car Program (No Cost - Car, Maintenance, and Insurance included) Industry-leading Benefit Plans (Medical, Dental, Vision, Rx) Paid time off, including vacation, holidays, shutdown Company Paid Short-Term and Long-Term Disability 401K Plan with company match + additional contribution Relocation assistance (if eligible) Career Growth: Advancement Opportunities Career Mobility Education Reimbursement for Continued learning Training and Development Programs Additional Offerings: Lifestyle Account Childcare Reimbursement Account Elder Care Support Tuition Assistance & Student Loan Repayment Wellbeing Program Community Service and Engagement Programs Product Programs Honda is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, gender identity and expression, age, disability, veteran status, or any other protected factor.

Job Description Job Description About Medical Guardian: Medical Guardian is a fast-growing digital health and safety company on a mission to help people live a life without limits. With 13 consecutive years on the Inc. 5000 list of Fastest Growing Companies, we are redefining what it means to age confidently and independently. We support over 625,000 members nationwide with life-saving emergency response systems and remote patient monitoring solutions. Trusted by families, healthcare providers, and care managers, our work is powered by a culture of innovation, compassion, and purpose. Mission: This role is focused on building and leading the data engineering foundation that powers real-time decisioning, operational applications, analytics, ML/AI model development, and data services across Medical Guardian. The Principal Data Engineer will own the design, delivery, and maturity of production-grade data pipelines and data platforms, with a primary emphasis on real-time streaming, IoT telemetry, Databricks, Azure, data services for APIs and microservices, and reliable data products for downstream consumption. Role Summary: We are looking for a Principal Data Engineer to serve as a hands-on technical and people leader for data engineering, data platform architecture, real-time streaming, and production data services. This role will focus on designing, building, operating, and improving data pipelines and data products while also bringing principal-level judgment to architecture, stakeholder shaping, delivery priorities, team management, and production readiness. This is a hands-on engineering leadership role first. The ideal candidate should be comfortable spending significant time working directly with Databricks, Spark, SQL, Python/PySpark, Azure services, streaming architectures, data quality frameworks, pipeline automation, CI/CD, and production troubleshooting. They should also be able to operate with the maturity of a principal-level leader: shaping unclear requirements, making pragmatic technical decisions, managing and mentoring engineers, and driving work forward without waiting for perfect specifications. This is a fast-moving, startup-like environment. Requirements may be incomplete, priorities may evolve, and the right candidate will help create clarity while building quickly. We need someone who can move from ambiguous business need to reliable data capability with urgency, discipline, and ownership. Stakeholder shaping is a critical part of this role. The Principal Data Engineer should be able to work directly with business, product, software engineering, analytics, ML/AI, operations, and leadership stakeholders to define what data needs to exist, how it should be consumed, what production guarantees are required, and how success should be measured. A background in commercial software, SaaS, digital products, healthtech, fintech, IoT, data platforms, or other product-driven environments is strongly preferred. We want someone who understands that data pipelines and data services are not just technical artifacts. They are product capabilities that support real users, real workflows, operational decisions, ML/AI systems, APIs, analytics, and measurable business outcomes. Key Responsibilities: Hands-On Data Engineering and Platform Development Design, build, optimize, and operate production-grade batch and streaming data pipelines on Azure and Databricks, with a primary focus on real-time IoT and telemetry use cases within a Medallion architecture. Develop ETL/ELT workflows to ingest, transform, validate, and serve large volumes of structured, semi-structured, unstructured, and streaming data. Build and maintain reliable data products, data services, APIs, and microservices that support operational applications, analytics, software engineering, and ML/AI teams. Use Python, PySpark, Spark SQL, SQL, Delta Lake, Databricks Workflows, CI/CD, and related tools to build maintainable, testable, and observable data systems. Troubleshoot complex production pipeline issues across Databricks, Azure, streaming systems, APIs, and source systems, including root cause analysis, corrective action, and prevention planning. Move quickly from rough business need to prototype, pilot, and production-ready data capability while maintaining appropriate engineering discipline. Real-Time Streaming, IoT Telemetry, and Operational Data Services Lead the design and delivery of real-time streaming ingestion and processing patterns for connected medical device telemetry, event data, and operational data feeds. Implement streaming solutions using Azure Event Hubs, Azure Stream Analytics, Databricks, Delta Lake, and related Azure integration patterns. Design cost-effective throughput, partitioning, delivery, retention, and replay strategies for high-volume event and telemetry workloads. Create consumption patterns that support APIs, microservices, operational applications, near-real-time decisioning, analytics, and ML/AI use cases. Define reliability, latency, quality, observability, and supportability expectations for production streaming systems. Databricks, Lakehouse, and Data Platform Architecture Set direction for Databricks-based data engineering patterns, including Medallion architecture, Delta Lake, Spark optimization, data modeling, data quality, and reusable pipeline design. Optimize production Databricks pipelines using PySpark, Spark SQL, Delta Lake, partitioning strategies, caching, shuffle optimization, cluster/job configuration, and cost-aware design. Establish practical standards for pipeline structure, code organization, testing, deployment, monitoring, documentation, and ownership. Partner with data platform, security, infrastructure, and engineering teams to ensure the data platform is scalable, secure, reliable, and aligned with enterprise architecture. Make pragmatic architecture tradeoffs between speed, durability, cost, governance, performance, and downstream business impact. Stakeholder Shaping and Cross-Functional Partnership Work directly with business, product, analytics, ML/AI, operations, software engineering, and leadership stakeholders to clarify what data is needed, why it matters, how it will be used, and what success looks like. Translate ambiguous business needs into concrete data requirements, data product definitions, architecture options, delivery priorities, and implementation plans. Ask practical questions early: who will use the data, what decision or workflow does it support, what latency and quality are required, what happens if the data is wrong or late, and how will we know the capability is creating value? Help the organization avoid becoming a data ticket factory by shaping solutions, not just executing requests. Communicate architecture decisions, tradeoffs, risks, dependencies, and delivery options clearly to technical and non-technical stakeholders. Team Management and Principal-Level Technical Leadership Manage, mentor, and develop data engineers, providing clear expectations, technical guidance, prioritization support, feedback, and accountability. Provide technical leadership through hands-on example, strong engineering judgment, clear recommendations, and pragmatic decision-making. Lead design reviews, code reviews, production readiness reviews, incident reviews, and architecture discussions across data engineering initiatives. Establish and improve engineering standards for data quality, testing, CI/CD, observability, documentation, runbooks, cost management, privacy, and security. Proactively identify platform risks, data gaps, unclear ownership, operational weaknesses, and opportunities to improve reliability, scalability, and delivery speed. Influence without relying only on formal authority by building trust, framing tradeoffs, and helping cross-functional teams get to decisions. ML/AI, Analytics, and GenAI Enablement Partner with ML engineers, data scientists, analytics engineers, and analysts to deliver reliable data pipelines, feature pipelines, training datasets, scoring inputs, and feedback loops. Support the data foundation for predictive models, risk scores, operational decisioning, GenAI workflows, RAG, document intelligence, summarization, and AI-enabled automation. Help define data contracts, model-ready datasets, feature definitions, lineage, and monitoring expectations for ML/AI and analytics use cases. Ensure downstream consumers understand the meaning, freshness, quality, limitations, and appropriate use of the data products they depend on. Governance, Data Quality, Security, and Production Operations Apply privacy-first, security-aware, and governance-aligned practices for regulated, sensitive, and operationally critical data. Design and implement data quality checks, validation rules, anomaly detection, schema expectations, alerting, and operational monitoring. Ensure production pipelines and services are supportable, observable, documented, recoverable, and aligned with business continuity needs. Drive incident response and continuous improvement for data platform and pipeline issues, including root cause analysis and preventative remediation. Balance innovation with reliability, compliance, privacy, cost discipline, and operational usefulness. Required Qualifications: 10+ years of professional experience in data engineering . click apply for full job details

Job Description Job Description Founded in 2012, H2O.ai is on a mission to democratize AI. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built GenAI applications on their private data. With a focus on Sovereign AI-secure, compliant, and infrastructure-flexible deployments-H2O.ai delivers solutions that align with the highest standards of data privacy and control. Our open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Chipotle, Workday, Progressive Insurance, and NIH. H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS, Google Cloud Platform (GCP), VAST Data and MinIO. H2O.ai's AI for Good program supports nonprofit groups, foundations, and communities in advancing education, healthcare, and environmental conservation. With a vibrant community of 2 million data scientists worldwide, H2O.ai aims to co-create valuable AI applications for all users. H2O.ai has raised 256 million from investors, including Commonwealth Bank, NVIDIA, Goldman Sachs, Wells Fargo, Capital One, Nexus Ventures and New York Life. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in Dallas, Texas and requires onsite customer interfacing. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit