Data Center Cooling and Thermodynamics Engineer

Join our innovative team at neo-tax as a Front-end Data Science Engineer, where you will play a crucial role in developing cutting-edge web applications. Collaborate closely with UI/UX designers to create intuitive user interactions and ensure a seamless experience across various devices. Your responsibilities will include:Optimizing applications for mobile and tablet users, ensuring responsiveness across platforms.Collaborating with data scientists and engineers to design novel UI/UX methodologies that highlight the value of data science within web applications.Analyzing collected data to identify strengths and weaknesses, and implementing user interfaces to effectively communicate these insights.Creating custom UI/UX solutions tailored to unique data models and algorithms.Researching and implementing suitable data science algorithms and user interface tools.Staying updated on the latest research and selecting effective UI and data representation methods.This position allows for full-time telecommuting.

Join 360itprofessionals1 as a Front-End/UI Quality Engineer and play a critical role in enhancing user experience across our digital platforms. We are seeking a detail-oriented professional who is passionate about quality assurance and has a strong understanding of front-end technologies.

Databricks is seeking a skilled Senior Manager in Infrastructure Data Science to revolutionize our infrastructure through the power of data science. In this role, you will address intricate challenges associated with capacity planning, performance enhancement, reliability engineering, infrastructure optimization, and customer satisfaction. You will lead a talented team of data scientists and collaborate closely with engineering leaders to provide them with actionable, data-driven insights and solutions.At Databricks, our mission is to empower data teams to tackle the world's most pressing issues, from detecting security threats to advancing cancer treatments. We achieve this by creating and managing the leading data and AI infrastructure platform, allowing our clients to concentrate on the high-impact challenges that are vital to their missions.Founded in 2013 by the original creators of Apache Spark, Databricks has evolved from a small office in Berkeley, CA to a global powerhouse with over 7,000 employees. Numerous organizations, ranging from startups to Fortune 100 companies, depend on Databricks for their critical workloads, positioning us as one of the fastest-growing SaaS firms worldwide.Our engineering teams develop highly technical products that meet significant, real-world needs. We continuously push the limits of data and AI technology, all while maintaining the resilience, security, and scalability that are essential for ensuring our customers' success on our platform.

Join Waymo as a Senior Back-End Software Engineer in our Simulation team, where you will play a vital role in building and enhancing our cutting-edge autonomous driving technologies. You will be responsible for designing and implementing robust back-end systems that support our simulation environments, helping to ensure the safety and efficiency of our self-driving vehicles.Your contributions will directly impact the future of transportation and make a difference in how people move through the world.

Join LinkedIn as a Senior Staff Applied Scientist specializing in Infrastructure Data Science. In this pivotal role, you will leverage your expertise to drive innovation and enhance the efficiency of our infrastructure systems. You will collaborate with cross-functional teams, developing cutting-edge data solutions that significantly impact our global user base.Your responsibilities will include conducting advanced data analyses, modeling complex systems, and implementing machine learning algorithms to optimize performance. You will also mentor junior scientists and contribute to a vibrant research culture, ensuring that LinkedIn remains at the forefront of technology and data science.

Aera Technology is at the forefront of Decision Intelligence Platforms, recognized as a leader in the Gartner® Magic Quadrant™ for 2026. Our innovative technology empowers organizations to digitize, enhance, and automate their decision-making processes using cutting-edge AI and machine learning. Through our Aera Decision Cloud™, we assist some of the most renowned global brands in making more intelligent and rapid decisions. As a privately-held, VC-backed company, we boast a diverse, global team of over 400 skilled Aeranauts and are on an exciting growth trajectory. We are dedicated to delivering innovative Decision Intelligence solutions and services that empower enterprises to streamline their decision-making with precision and agility. Our commitment to generating value has made us the preferred partner for market leaders seeking to unlock previously unattainable opportunities. The Principal Data Scientist is a pivotal role in advancing Aera’s data science strategy. This position spearheads impactful machine learning projects, architects and implements scalable AI solutions, and ensures that our data-driven capabilities evolve in alignment with business objectives. As a thought leader, the Principal Data Scientist collaborates with Product, Engineering, and Client Success teams to address complex business challenges, enhance product intelligence, and steer the overall data science vision for the organization. The ideal candidate will reside in the San Francisco Bay Area and be available to work in the office with the Senior Vice President of Data Science and Chief Technology Officer at our headquarters in Mountain View three days per week.

About CommerceIQ CommerceIQ builds AI-driven solutions that help brands improve their digital commerce performance. The platform supports over 2,200 brands, including Coca-Cola, Nestle, Colgate-Palmolive, and Mondelez, across more than 900 retailers in 50+ countries. CommerceIQ’s tools help optimize marketing, supply chain, and sales operations to grow market share. The company has raised over $200M from investors such as SoftBank, Insight Partners, and Madrona. Learn more at commerceiq.ai. Role Overview CommerceIQ is hiring a Director of Engineering - AI Solutions to lead the development of advanced AI-powered SaaS products. This leader will shape the technical architecture of the AI platform while guiding and mentoring a team of engineers. The role combines hands-on engineering with team leadership. What You Will Do Drive the design and implementation of AI and agentic applications for digital commerce. Work closely with co-founders to push the boundaries of applied AI in the industry. Scale AI systems from research through production, ensuring real business impact for global brands. Mentor and develop engineering talent within the AI team. Who We’re Looking For Experienced technical leader in Data Science and Machine Learning. Background in training and deploying machine learning models at scale. Experience developing agentic applications. Comfortable working both as a hands-on contributor and as a mentor. Location and Work Schedule This is an onsite role based at CommerceIQ’s headquarters in Mountain View, California. The team works in the office Monday through Friday.

Harness is at the forefront of AI-driven software delivery, founded by technologist and entrepreneur Jyoti Bansal, who previously founded AppDynamics, which was acquired by Cisco for an impressive $3.7 billion. With around $570 million in funding and a valuation of $5.5 billion, Harness is supported by top investors such as Goldman Sachs, Menlo Ventures, IVP, Unusual Ventures, and Citi Ventures. In a landscape where AI is revolutionizing code generation, the focus has shifted to enhancing the post-code processes, including testing, deployments, application security, reliability, compliance, and cost management. Harness leverages AI and automation to streamline this "outer loop" of software delivery, empowering teams to accelerate their software releases while ensuring robust security and governance throughout the entire lifecycle. Utilizing Harness AI and the Software Delivery Knowledge Graph, our platform integrates deep context and intelligent automation across the software delivery lifecycle, embedding governance and policy-driven controls seamlessly. Over the past year, Harness has facilitated more than 185 million deployments, 82 million builds, 18 trillion flag evaluations, 8 million security scans, 9.1 billion optimized tests, and protected 3 trillion API calls, managing $2.8 billion in cloud expenditure. Our clients, including United Airlines, Morningstar, and Choice Hotels, have experienced up to 75% faster release cycles, reduced cloud costs by as much as 60%, and achieved an impressive 10x efficiency in their DevOps practices. With a diverse global team spread across 14 offices in 25 countries, Harness is poised to redefine the future of AI software delivery, and we are eager to welcome exceptional talent to propel us forward.

About GranicaGranica is a pioneering AI research and infrastructure firm dedicated to creating reliable, steerable representations for enterprise data.We build trust through Crunch, a policy-driven health layer that ensures large tabular datasets are efficient, reliable, and reversible. Leveraging this foundation, we are developing Large Tabular Models—systems designed to learn cross-column and relational structures, providing trustworthy answers and automation with inherent provenance and governance.Engineering Manager – Foundational Data Systems for AILocation: Mountain View, CA (in-office, 5 days a week)Team: Foundational Data SystemsRole OverviewWe are seeking an Engineering Manager to spearhead Granica's Foundational Data Systems—the essential infrastructure layer upon which all other systems rely.You will oversee a globally distributed team of approximately 15-20 senior engineers based in the US, India, and Canada, with direct accountability for long-lived systems encompassing storage, metadata, and distributed computing. This role transcends traditional people management; it is a hands-on leadership position with significant architectural influence, responsible for crafting systems that must be accurate, durable, and efficient at an enterprise scale.The systems developed by this team are pivotal in determining Granica’s ability to convert cutting-edge research into dependable products, ensuring our customers trust the data foundations that their analytical and AI workloads rely upon.This position is perfect for a technically adept leader who is passionate about team building, designing long-lasting systems, and operating with high levels of trust and ownership.Why This Role MattersContemporary AI and analytics systems face constraints not from models, but from the inefficiency and fragility of the underlying data infrastructure. Redundant data layouts, fragile metadata, and costly execution paths lead to increased expenses, slower iterations, and operational risks.Granica’s mission is to eliminate these inefficiencies at the foundational level.We engineer self-optimizing data systems that perpetually reorganize, compress, and manage structured data to remain efficient, reliable, and reversible as it evolves. These systems act as a resilient substrate for analytics, automation, and AI workloads—where accuracy, provenance, and governance are paramount.

Please complete the attached Internal Transfer Request Form and submit.Ensure that you apply using your Coupang email address.This role is open to both Mountain View and Seattle locations.At Coupang, we are dedicated to astonishing our customers. When we hear our customers exclaim, “How did we ever live without Coupang?” we know we are on the right track. Fueled by a commitment to simplify shopping, dining, and living, we are revolutionizing the multi-billion-dollar e-commerce sector from the ground up. As one of the fastest-growing e-commerce companies, we are seeking passionate individuals to join our innovative team.

ECL has revolutionized the industry with the launch of the world’s first hydrogen-powered, off-grid green data center, boasting an impressive 99.999% uptime. As demand surges for state-of-the-art data centers capable of supporting the needs of AI and Machine Learning, what once seemed like a distant vision has become a reality. Our innovative end-to-end construction platform and modular architecture allow us to scale from 1-2MW to accommodate even the largest data center sites. This is a unique opportunity to contribute to the development of a fully sustainable power generation system in the evolving landscape of disruptive technology advancements in Machine Learning and Artificial Intelligence.Join us at ECL, a company founded by experts from leading tech giants such as Facebook, Microsoft, LinkedIn, Cisco, HPE, and Bloom Energy, and be part of our exciting journey as we prepare for exponential growth.Data Center EngineerLocation: Mountain ViewReports To: Director, Data Center Site Services Position OverviewThe Data Center Engineer (KTLO) will ensure the ongoing operational readiness of all critical infrastructure systems within a mission-critical data center environment. This role is pivotal in guaranteeing uptime, maintaining system redundancy, and enforcing strict procedural and safety protocols across electrical, mechanical, and supporting site systems.This operations-centric position requires a focus on stability, execution, and adherence to compliance. The engineer will implement approved procedures, assist with structured change management processes, monitor system health, and maintain documentation that is ready for audits in a tightly controlled, high-availability environment.The candidate must possess a working knowledge of electrical distribution systems, critical cooling infrastructures (including liquid cooling technologies), structured governance of MOP/SOP/EOP, and regulated operational settings. Success in this role hinges on procedural discipline, sound judgment in escalation situations, and effective risk mitigation practices. Key ResponsibilitiesElectrical Systems Operations· Operate and maintain UPS systems, switchgear, transformers, PDUs, generators, fuel cells, and BESS (as applicable)· Support switching activities under approved MOPs· Monitor...

Join Our TeamWe are seeking a Senior Data Engineer to become an integral part of our Data Platform team at Otter.ai. In this pivotal role, you will construct the essential data infrastructure that fuels analytics, experimentation, and decision-making across our organization. Your expertise will guide the design and ownership of foundational data models, pipelines, and platforms, enabling self-serve analytics and delivering trustworthy insights at scale.As a technical thought leader, you will collaborate closely with teams in Growth, Product, Sales, Marketing, Data Insights, and Engineering, helping them derive meaningful value from data. This is a high-impact role within a dynamic company, allowing you to influence how data is collected, modeled, and utilized to propel our business forward.Your ContributionsConstruct and manage foundational data models that facilitate self-serve analytics and critical business metrics.Design, operate, and enhance robust data pipelines and platforms.Collaborate with stakeholders to convert business requirements into reliable data products.Establish standards for data collection and logging across production systems.Promote best practices for data modeling, quality, and governance.Implement data quality checks, statistical validation, and anomaly detection processes.Provide technical leadership that enhances data reliability and literacy across teams.

Join LinkedIn as a Distinguished Software Engineer specializing in Data Infrastructure, where you will lead innovative projects that enhance our data capabilities and support millions of users worldwide. This role requires a deep understanding of data architecture and an ability to design scalable solutions.

P-186 At Databricks, we are passionate about empowering data teams to tackle some of the world's most challenging problems, from detecting security threats to advancing cancer drug development. Our mission is to build and operate the premier data and AI infrastructure platform, allowing our customers to concentrate on the high-value challenges central to their missions. Since our inception in 2013 by the original creators of Apache Spark™, Databricks has transformed from a small office in Berkeley, California, into a global powerhouse with over 1,000 employees. Today, thousands of organizations—from startups to Fortune 100 companies—trust Databricks with their mission-critical workloads, solidifying our status as one of the fastest-growing SaaS companies worldwide. Our engineering teams are dedicated to developing highly technical products that address real-world needs. We continuously push the limits of data and AI technology while ensuring the resilience, security, and scale essential for our customers' success on our platform. We manage one of the largest-scale software platforms, comprising millions of virtual machines that generate terabytes of logs and process exabytes of data daily. At this scale, we routinely encounter cloud hardware, network, and operating system faults, and our software must adeptly shield our customers from these challenges. In modern data analysis, sophisticated techniques such as machine learning extend far beyond the traditional SQL query engine's roll-up and drill-down capabilities. As a software engineer on the Runtime team at Databricks, you will contribute to building next-generation distributed data storage and processing systems that not only surpass specialized SQL query engines in relational query performance but also offer the expressiveness and programming abstractions necessary to support varied workloads, ranging from ETL to data science. Here are some example projects you might work on: Apache Spark™: Develop the de facto open-source standard framework for big data. Data Plane Storage: Provide reliable and high-performance services and client libraries for storing and accessing massive amounts of data on cloud storage backends like AWS S3 and Azure Blob Store. Delta Lake: A storage management system that merges the scale and cost-efficiency of data lakes with the performance and reliability of data warehouses, along with the low latency of streaming. Its higher-level abstractions, including ACID transactions and time travel, significantly simplify real-world data engineering architecture. Delta Pipelines: Managing a single data engineering pipeline can be challenging. The objective of the Delta Pipelines project is to streamline this process.

P-59 At Databricks, we are driven by a mission to empower data teams to tackle some of the most pressing challenges facing our world. Whether it's transforming transportation or accelerating medical innovations, we achieve this by creating and operating the foremost data and AI infrastructure platform. Our customers leverage deep data insights to enhance their business operations. Founded by engineers with a relentless commitment to customer satisfaction, we eagerly embrace every opportunity to address technical challenges—from designing cutting-edge UI/UX for data interaction to scaling our services across millions of virtual machines. And this is just the beginning. In modern data analysis, advanced techniques such as machine learning surpass the capabilities of conventional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be instrumental in developing next-gen distributed data storage and processing systems that not only outperform specialized SQL query engines in relational query performance but also offer the flexibility and programming abstractions necessary to support a diverse range of workloads, from ETL processes to data science applications. Key projects you might work on include: Apache Spark™: Contribute to the leading open-source framework for big data. Data Plane Storage: Deliver reliable, high-performance services and client libraries for managing vast amounts of data on cloud storage solutions like AWS S3 and Azure Blob Store. Delta Lake: A sophisticated storage management system that merges the scalability and cost-effectiveness of data lakes with the performance and reliability of data warehouses, offering features such as ACID transactions and time travel to simplify complex data engineering architectures. Delta Pipelines: Simplify the management of extensive data engineering pipelines, allowing customers to effortlessly orchestrate, deploy, test, and upgrade thousands of data pipelines while minimizing operational burdens. Performance Engineering: Develop the next-generation query optimizer and execution engine that is fast, tuning-free, scalable, and robust.

Moveworks, a part of ServiceNow based in Mountain View, is looking for a Senior Data Scientist. This position focuses on using advanced analytics to guide decision-making and enhance product features. Collaboration is central, as the Senior Data Scientist works with multiple teams to identify opportunities and shape solutions that use AI to transform customer service. Key responsibilities Analyze complex datasets to inform business and product strategies Partner with engineering, product, and other groups to address challenges and drive improvements Create new methods to strengthen AI-powered support tools Support ongoing initiatives to advance customer service through artificial intelligence Role overview This role centers on both technical analysis and cross-functional teamwork. The Senior Data Scientist will play a part in shaping how AI is used to improve customer experiences at Moveworks and ServiceNow.

At Intrinsic Robotics, a part of Alphabet, we are on a mission to revolutionize industrial robotics. We believe that advancements in artificial intelligence, perception, and simulation will redefine the capabilities of industrial robotics in the near future, with software and data at the heart of this transformation. Our vision is to make industrial robotics more intelligent, accessible, and user-friendly for countless businesses, entrepreneurs, and developers. We are a vibrant team of engineers, roboticists, designers, and technology enthusiasts dedicated to unlocking the creative and economic potential of industrial robotics.Role OverviewAs a Software Engineer on our Data Infrastructure team, you will play a pivotal role in designing, developing, and maintaining the data infrastructure that drives our state-of-the-art robotics systems. Your contributions will facilitate the design, development, and operational workflows for robotics, integrating with Kubernetes-based cloud and on-device services. This includes the systems responsible for collecting and processing real-world data from our robots, feeding that information into our machine learning pipelines to train and assess the models that empower our robots with intelligence. You will collaborate closely with an enthusiastic Product and Engineering team to create software that enhances the capabilities of fleets of robots.Your Impact on Our MissionDesign, develop, and maintain scalable and reliable data pipelines for the collection, processing, and storage of vast amounts of robotics data (including sensor data, telemetry, and logs).Construct data pipelines to train the next generation of functional robot models.Develop and support tools and infrastructure for data exploration, analysis, and visualization.Implement and uphold best practices for data security and privacy.Collaborate with Customers, Product Managers, and Researchers to tailor data pipelines for analysis and research.

Join our team of passionate Science Tutors at AJ Tutoring! We offer a stunning office environment and comprehensive training programs. Earn between $32.50 and $40 per hour as you engage with students in person. If you are bright, energetic, and enthusiastic about education, we are eager to meet you!

About Contextual AI At Contextual AI, we are pioneering a transformation in the way AI Agents operate by tackling the most pressing challenge in AI: context. By providing the right context at the right moment, we enable enterprises to achieve the precision and scalability they need from AI. Our robust enterprise AI development platform bridges the gap between cutting-edge AI research and the practical needs of developers. Our comprehensive platform simplifies the process for AI developers to seamlessly ingest and query documents from enterprise data sources, integrating retrieval outcomes into their business workflows effortlessly. Founded by the trailblazers of Retrieval-Augmented Generation (RAG), the foundational technology that links foundational models to timely and relevant data, Contextual AI is backed by some of the most innovative venture capitalists in the industry. We are not merely a part of the enterprise AI revolution; we are at its forefront. Join us in creating a future where AI transcends mere question answering to genuinely transform businesses. Job Overview The Data Platform team within Contextual AI is integral to powering product development, applied research, and managing data-heavy workloads for our customers. This is a unique opportunity to influence the technical vision of the data engineering team, contributing to groundbreaking projects within a greenfield environment. What You’ll Do: Design and develop scalable services, APIs, and databases to efficiently handle the daily processing and ingestion of petabytes of data. Enhance state-of-the-art multimodal LLMs to maximize document understanding capabilities. Create and implement thorough evaluation pipelines for end-to-end agentic RAG workflows. Architect and construct streaming infrastructure and data orchestration systems, including vector databases. Collaborate with machine learning researchers to interpret state-of-the-art requirements for RAG systems, translating them into actionable service specifications. Engage directly with product managers and application engineers to gather customer requirements for end-to-end RAG systems, and convert these into viable technical solutions. Ensure seamless integration with machine learning models and pipelines, facilitating effective model deployment and management. Provide mentorship and guidance to junior team members, fostering a culture of knowledge sharing and professional development. What We’re Seeking: Education: A Bachelor’s degree in Computer Science, Software Engineering, or a related field. Experience: Minimum of 2 years of relevant experience in data engineering or a related field. Strong understanding of scalable data architectures and design principles. Proficiency in modern programming languages and frameworks. Experience with machine learning principles and practices is a plus.