

Share
Senior MTS Software Engineer, Data Platform
Job Type: Full-time
About the RoleWe are seeking Data Platform Software Engineers, not Data Engineers . While familiarity with Spark, Flink, and other tools in the Hadoop environment is a definite advantage, your focus will be on building the data platform rather than just creating data pipelines.
Independently lead complex, high-impact initiatives across eBay’s Data Platforms, from conception to successful production rollout. You will collaborate with Product Managers to help define the vision for the data platform at eBay.
Architectural Leadership: Own and evolve the architecture for core data platform systems, ensuring solutions are scalable, secure, maintainable, and in alignment with enterprise standards.
System Design: Eliminate duplication across systems and ensure clear responsibility boundaries; align systems with business needs and future scalability.
Engineering Excellence: Champion clean architecture, promote use of modern frameworks, enforce quality gates, and ensure adherence to design patterns and coding standards.
Lead by Example: Write reference implementations, contribute to core libraries, and conduct in-depth code reviews to influence standards and uplift team capabilities.
Cost Optimization: Propose and drive engineering solutions that reduce operational overhead, improve resource efficiency, and automate manual processes.
Framework Development: Find opportunities to build reusable components, services, and frameworks that accelerate feature delivery across the organization
Modernization: Lead migrations of legacy systems into modern architectures and cloud-native paradigms with minimal disruption and high impact.
Collaboration: Drive complex technical discussions, build consensus across engineering, product, and operational teams, and ensure smooth delivery of cross-functional projects.
Documentation & Governance: Create well-structured Architecture Decision Records (ADRs) and contribute to technical documentation and standards.
Proactively address performance, security, compliance, and future-proofing of solutions while balancing latency, correctness, scale, and cost.
Raise the engineering bar through design/code reviews, operational excellence (SLOs, observability, incident management), and scalable practices that increase velocity across teams.
Mentorship: Act as a technical mentor, guiding senior and junior engineers on architecture best practices and advanced problem-solving.
Introduce AI-first frameworks and reusable components that reduce developer friction and enable faster iteration.
Automate diagnostics, monitoring, and remediation using intelligent assistants and prediction-based alerting.
Excellent in interpersonal communication
What you bring
Extensive experience owning large-scale distributed data platforms (multi-PB data, high-throughput streams, global systems).
Deep systems approach : you anticipate bottlenecks, design for reliability (reprocessing, idempotency, schema evolution), and think holistically across compute, storage, and APIs.
Excellent decision-making and communication skills , thriving in ambiguity while aligning diverse stakeholders on the right path forward.
Security and compliance mindset , including data privacy, RBAC/ABAC, encryption, and auditability — with the ability to partner with compliance teams on regulatory requirements.
Proven leadership in mentoring engineers, shaping team culture, and driving organizational change in engineering practices.
Growth mindset
High-impact mission : You will build and modernize eBay’s Data Platform, which powers analytics, experimentation, machine learning, personalization, and trust and compliance on a global scale.
Challenging technical problems : From real-time streaming at scale, to lakehouse correctness, governance, cost and performance optimization, and multi-cloud resiliency.
Vibrant culture : A collaborative, transparent, and inclusive environment where diverse perspectives are valued, knowledge sharing is encouraged, and every engineer has a voice.
Flexibility & support : Hybrid/remote-friendly practices, competitive compensation, global benefits ( ), and support for learning resources, conferences, and career development.
Always-on responsibility with balance
Qualifications
12+ years of experience in building and operating large-scale distributed systems, with 5+ years as a staff/architect-level technical lead across multiple domains.
Proven success in driving technical strategy and roadmaps , authoring architecture and technical vision documents, and aligning stakeholders across engineering, product, and compliance.
Strong foundation in data structures, algorithms, and distributed systems design .
Proficiency in Java/Python (or equivalent) and in infra-as-code, CI/CD, and containerized environments.
Hands-on deep internal expertise in several of the following: Kafka/Flink, Spark,, Delta/Iceberg, GraphQL/REST APIs, RDBMS/NoSQL, Kubernetes, Airflow.
Experience building both streaming and batch data platforms , improving reliability, quality, and developer velocity.
Demonstrated ability to mentor senior engineers, influence org-wide practices , and make long-term architectural decisions that unlock measurable business outcomes.
BS/MS in CS or equivalent practical experience.
The base pay range for this position is expected in the range below:
$152,400 - $247,800These jobs might be a good fit

Share
What you'll be doing:
Path-find technical innovations in Quantum Error Correction and Fault Tolerance, working with multi-functional teams in Product, Engineering, and Applied Research
Develop novel approaches to quantum error correction codes and their logical operations, including methods for implementation and logical operation synthesis
Research and co-design improved methods to achieve fault tolerance, such as techniques for logical operations, concatenation, synthesis, distillation, cultivation, or others
Collaborate with internal teams and external partners on developing technology components to enable a fault-tolerant software stack integrated with quantum hardware
Adopt a culture of collaboration, rapid innovation, technical depth, and creative problem solving
What we need to see:
Degree in Physics, Computer Science, Chemistry, Applied Mathematics, or related engineering field or equivalent experience (Ph.D. preferred)
Extensive background in Quantum Information Science with 8+ overall years of experience in the Quantum Computing industry
A demonstrated ability to deliver high impact value in quantum error correction and fault tolerance
Ways to stand out from the crowd:
Hands-on experience in scientific computing, high-performance computing, applied machine learning, or deep learning
Experience with co-design of quantum error correction with quantum hardware or quantum applications
Experience with CUDA and NVIDIA GPUs
Passion to drive technology innovations into NVIDIA software and hardware products to support Quantum Computing
You will also be eligible for equity and .

Share
What you'll be doing:
As a senior member in our team, you will work with pre-silicon and post-silicon data analytics - visualization, insights and modeling.
Design and uphold sturdy data pipelines and ETL processes for the ingestion and processing of DFX Engineering data from various origins
Lead engineering efforts by collaborating with cross-functional teams (execution, analytics, data science, product) to define data requirements and ensure data quality and consistency
You will work on hard-to-solve problems in the Design For Test space which will involve application of algorithm design, using statistical tools to analyze and interpret complex datasets and explorations using Applied AI methods.
In addition, you will help develop and deploy DFT methodologies for our next generation products using Gen AI solutions.
You will also help mentor junior engineers on test designs and trade-offs including cost and quality.
What we need to see:
BSEE (or equivalent experience) with 5+, MSEE with 3+, or PhD with 1+ years of experience in low-power DFT, Data Visualization, Applied Machine Learning or Database Management.
Experience with SQL, ETL, and data modeling is crucial
Hands-on experience with cloud platforms (AWS, Azure, GCP)
Design and implement highly scalable, fault tolerant distributed database solutions
Lead data modeling, performance tuning, and capacity planning for large-scale, mission-critical storage workloads
Excellent knowledge in using statistical tools for data analysis & insights.
Strong programming and scripting skills in Perl, Python, C++ or Tcl is expected
Outstanding written and oral communication skills with the curiosity to work on rare challenges.
Ways to stand out from the crowd:
Experience in data pipeline and database architecture for real-world systems
Experience in application of AI for EDA-related problem-solving
Good understanding of technology and passionate about what you do
Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic environment
You will also be eligible for equity and .

Share
What you'll be doing:
Develop and implement the business logic in the new End-to-End Data systems for our Planning, Logistics, Services, and Sourcing initiatives.
Lead discussions with Operations stakeholders and IT to identify and implement the right data strategy given data sources, data locations, and use cases.
Analyze and organize raw operational data including structured and unstructured data. Implement data validation checks to track and improve data completeness and data integrity.
Build data systems and data pipelines to transport data from a data source to the data lake ensuring that data sources, ingestion components, transformation functions, and destination are well understood for implementation.
Prepare data for AI/ML/LLM models by making sure that the data is complete, has been cleansed, and has the necessary rules in place.
Build/develop algorithms, prototypes, and analytical tools that enable the Ops teams to make critical business decisions.
Build data and analytic solutions for key initiatives to set up manufacturing plants in US.
Support key strategic initiatives like building scalable cross-functional datalake solutions.
What we need to see:
Master’s or Bachelor’s degree in Computer Science or Information System, or equivalent experience
8+ years of relevant experience including programming knowledge (i.e SQL, Python, Java, etc)
Highly independent, able to lead key technical decisions, influence project roadmap and work effectively with team members
Experience architecting, designing, developing, and maintaining data warehouses/data lakes for complex data ecosystems
Expert in data and database management including data pipeline responsibilities in replication and mass ingestion, streaming, API and application and data integration
Experience in developing required infrastructure for optimal extraction, transformation, and loading of data from various sources using Databricks, AWS, Azure, SQL or other technologies
Strong analytical skills with the ability to collect, organize, and disseminate significant amounts of information with attention to detail and accuracy
Knowledge of supply chain business processes for planning, procurement, shipping, and returns of chips, boards, systems, and networking.
Ways to stand out from the crowd:
Self-starter, collaborative, positive mindset, committed to growth with integrity and accountability, highly motivated, driven, and high-reaching
Solid ability to drive continuous improvement of systems and processes
A consistent record to work in a fast-paced environment where good interpersonal skills are crucial
You will also be eligible for equity and .

Share
NVIDIA is searching for a world-class researcher in generative AI to join our research team. You will be conducting original research for generative AI applications, including image generation, video generation, 3D generation, and audio generation. You will be working with a team of world-class researchers eager to make great impacts with generative AI models. You will be building research prototypes and scaling them with large datasets and compute. After building prototypes that demonstrate the promise of your research, you will work with product teams to help them integrate your ideas into products.
What you'll be doing:
Conduct original research in the space of generative AI
Implement and train large-scale generative AI models for various content creation applications
Collaborate with other research team members, a diverse set of internal product teams, and external researchers
Have a broader impact through the transfer of the technology you've developed to relevant product groups
What we need to see:
Ph.D. in Computer Science/Engineering, Electrical Engineering, or a related field (or equivalent experience).
5+ years of relevant research experience.
Excellent collaboration and interpersonal skills
Excellent python/C++ programming skills
Great knowledge of common deep-learning frameworks
Experience in processing or curating large-scale datasets
Excellent knowledge of theory and practice of deep learning, computer vision, natural language processing, or computer graphics
Track record of research excellence or significant product development
You will also be eligible for equity and .

Share
What you'll be doing:
Lead sophisticated programs focused on improving the quality and efficiency of data center infrastructure, hardware, and software domains with multi-year strategic roadmaps and cross-
Drive technical execution from requirements gathering through production launch, including writing technical specifications, coordinating release schedules, and ensuring operational readiness across multiple team dependencies
Own server hardware development, testing, and integration efforts for computing products, working closely with original design manufacturers and contract manufacturers on new product introductions at global manufacturing scale
Partner with software development teams to build automation programs for large-scale infrastructure testing and develop solutions that enhance operational performance across highly concurrent, high-throughput distributed systems
Guide enterprise network infrastructure and data center operations initiatives covering servers, storage, networking, power, and cooling systems while serving as domain leader for manufacturing test infrastructure
Lead continuous improvement initiatives for engineering processes, quality management, and operational excellence while leading risk mitigation strategies and critical path oversight
Build trusted partnerships across hardware teams, security professionals, supply chain, operations, and product management to drive technical decisions and resolve sophisticated multi-functional dependencies
What we need to see:
Bachelor's degree in Engineering, Computer Science, Electrical Engineering, Mechanical Engineering, or related technical field, or equivalent experience
12+ years working directly with engineering teams with demonstrated technical program management experience
More than 7 years of practical program or project management expertise being responsible for intricate technology ventures involving teams with multifaceted strengths
5+ years of software development experience with proficiency in programming languages.
5+ years leading hardware product development and new product introduction on a global manufacturing scale
Deep technical expertise in server, network, or storage product architecture and manufacturing test development
Strong understanding of large-scale distributed systems, data center infrastructure, and enterprise network architecture
Experience with Linux/Unix or Windows system administration, database management, and infrastructure automation
Demonstrated ability to lead programs across multiple teams, handle project scope, schedule, budget, and quality, and maintain executive-level relationships
Ways to stand out from the crowd:
8+ years directly leading sophisticated technology projects with experience designing and architecting highly reliable, scalable systems
Track record launching AI or ML server products with new technology enablement such as Liquid Cooling
Experience leading manufacturing test engineering teams within the server, network, or storage sector with expertise in Design for Excellence methodologies
Knowledge of security engineering, cryptography, quality management systems, and supply chain operations
Demonstrated single-threaded ownership of strategic programs with demonstrated ability to deliver groundbreaking systems independently in fast-paced, ambiguous environments
You will also be eligible for equity and .

Share
What you'll be doing:
Path-find technical innovations in Quantum Error Correction and Fault Tolerance, working with multi-functional teams in Product, Engineering, and Applied Research
Develop novel approaches to decoding quantum error correction codes and their logical operations, including researching advanced implementations in hardware
Research and co-design improved methods to achieve more scaled decoders
Collaborate with internal teams and external partners on developing technology components to enable a fault-tolerant software stack integrated with quantum hardware
Adopt a culture of collaboration, rapid innovation, technical depth, and creative problem solving
What we need to see:
Masters degree in Physics, Computer Science, Chemistry, Applied Mathematics, or related engineering field or equivalent experience (Ph.D. preferred)
Extensive background in Quantum Information Science with 6+ overall years of experience in the Quantum Computing industry
A demonstrated ability to deliver high impact value in quantum error correction and decoding
Ways to stand out from the crowd:
Hands-on experience in scientific computing, high-performance computing, applied machine learning, or deep learning
Experience with co-design of quantum error correction with quantum hardware or quantum applications
Experience with CUDA and NVIDIA GPUs
Passion to drive technology innovations into NVIDIA software and hardware products to support Quantum Computing
You will also be eligible for equity and .

Share
Senior MTS Software Engineer, Data Platform
Job Type: Full-time
About the RoleWe are seeking Data Platform Software Engineers, not Data Engineers . While familiarity with Spark, Flink, and other tools in the Hadoop environment is a definite advantage, your focus will be on building the data platform rather than just creating data pipelines.
Independently lead complex, high-impact initiatives across eBay’s Data Platforms, from conception to successful production rollout. You will collaborate with Product Managers to help define the vision for the data platform at eBay.
Architectural Leadership: Own and evolve the architecture for core data platform systems, ensuring solutions are scalable, secure, maintainable, and in alignment with enterprise standards.
System Design: Eliminate duplication across systems and ensure clear responsibility boundaries; align systems with business needs and future scalability.
Engineering Excellence: Champion clean architecture, promote use of modern frameworks, enforce quality gates, and ensure adherence to design patterns and coding standards.
Lead by Example: Write reference implementations, contribute to core libraries, and conduct in-depth code reviews to influence standards and uplift team capabilities.
Cost Optimization: Propose and drive engineering solutions that reduce operational overhead, improve resource efficiency, and automate manual processes.
Framework Development: Find opportunities to build reusable components, services, and frameworks that accelerate feature delivery across the organization
Modernization: Lead migrations of legacy systems into modern architectures and cloud-native paradigms with minimal disruption and high impact.
Collaboration: Drive complex technical discussions, build consensus across engineering, product, and operational teams, and ensure smooth delivery of cross-functional projects.
Documentation & Governance: Create well-structured Architecture Decision Records (ADRs) and contribute to technical documentation and standards.
Proactively address performance, security, compliance, and future-proofing of solutions while balancing latency, correctness, scale, and cost.
Raise the engineering bar through design/code reviews, operational excellence (SLOs, observability, incident management), and scalable practices that increase velocity across teams.
Mentorship: Act as a technical mentor, guiding senior and junior engineers on architecture best practices and advanced problem-solving.
Introduce AI-first frameworks and reusable components that reduce developer friction and enable faster iteration.
Automate diagnostics, monitoring, and remediation using intelligent assistants and prediction-based alerting.
Excellent in interpersonal communication
What you bring
Extensive experience owning large-scale distributed data platforms (multi-PB data, high-throughput streams, global systems).
Deep systems approach : you anticipate bottlenecks, design for reliability (reprocessing, idempotency, schema evolution), and think holistically across compute, storage, and APIs.
Excellent decision-making and communication skills , thriving in ambiguity while aligning diverse stakeholders on the right path forward.
Security and compliance mindset , including data privacy, RBAC/ABAC, encryption, and auditability — with the ability to partner with compliance teams on regulatory requirements.
Proven leadership in mentoring engineers, shaping team culture, and driving organizational change in engineering practices.
Growth mindset
High-impact mission : You will build and modernize eBay’s Data Platform, which powers analytics, experimentation, machine learning, personalization, and trust and compliance on a global scale.
Challenging technical problems : From real-time streaming at scale, to lakehouse correctness, governance, cost and performance optimization, and multi-cloud resiliency.
Vibrant culture : A collaborative, transparent, and inclusive environment where diverse perspectives are valued, knowledge sharing is encouraged, and every engineer has a voice.
Flexibility & support : Hybrid/remote-friendly practices, competitive compensation, global benefits ( ), and support for learning resources, conferences, and career development.
Always-on responsibility with balance
Qualifications
12+ years of experience in building and operating large-scale distributed systems, with 5+ years as a staff/architect-level technical lead across multiple domains.
Proven success in driving technical strategy and roadmaps , authoring architecture and technical vision documents, and aligning stakeholders across engineering, product, and compliance.
Strong foundation in data structures, algorithms, and distributed systems design .
Proficiency in Java/Python (or equivalent) and in infra-as-code, CI/CD, and containerized environments.
Hands-on deep internal expertise in several of the following: Kafka/Flink, Spark,, Delta/Iceberg, GraphQL/REST APIs, RDBMS/NoSQL, Kubernetes, Airflow.
Experience building both streaming and batch data platforms , improving reliability, quality, and developer velocity.
Demonstrated ability to mentor senior engineers, influence org-wide practices , and make long-term architectural decisions that unlock measurable business outcomes.
BS/MS in CS or equivalent practical experience.
The base pay range for this position is expected in the range below:
$152,400 - $247,800These jobs might be a good fit