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This position involves evaluating architectural trade-offs, defining micro-architecture, integrating RTL into top-level designs, and ensuring full coverage and validation. The role requires working with verification, providing timing constraints, and participating in silicon bring-up and validation.
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Design and implement CI/CD pipelines on Google Cloud
Build Terraform-based IaC pipelines on GCP
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Provide business-critical support to premium accounts
Resolve complex issues with root-cause analysis
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Work on Payment Intelligence projects focused on recovery and fraud prevention.
Contribute to building GoCardless major revenue streams.
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Architect cloud infrastructure strategy
Design and implement infrastructure-as-code foundations
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Develop and ship features within a cross-functional team
Collaborate on investigations and designs with engineers, PMs, and AI scientists
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Lead global data science organization
Guide team in predictive analytics and privacy-safe insights
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Perform vulnerability assessment and scanning
Support SOC operations and incident triage
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Define and execute manual/automated tests for customer journeys
Build and run scalable automation scripts and frameworks
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Lead and mentor security teams
Enhance threat detection and incident response
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Lead global IT Operations team
Automate incident management
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Evaluate architectural trade-offs on features and system limits
Define micro-architecture and implement RTL in Verilog/SystemVerilog
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Build and maintain large-scale distributed inference systems.
Develop routing and fleet orchestration across accelerators.
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Improve map data quality and enhance route recommendations
Benchmark and measure service performance and accuracy
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Propose and execute research initiatives for Conversational AI impact
Analyze conversational datasets for optimization
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Design and implement security measures to protect data
Partner with Detection & Response teams for visibility
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Partner with Sales to communicate value to customers
Close complex opportunities through competitive knowledge
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Gain practical experience in software development
Work with cutting-edge AI tools and technologies
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Promote MongoDB AI capabilities to developers and partners
Engage with the AI community and build partnerships
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Lead end-to-end datasets, RL envs, and evals for coding agents.
Define data pipelines, validation, and review processes.
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Invent tools and processes for deployment
Provide fast software validation
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Perform detailed thermal analysis of the airframe
Develop thermal management solutions for airframe composites
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Create technical content at scale
Represent Postman publicly
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Oversee firmware and embedded software qualification processes
Write and execute test plans
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Ensure reliability, scalability, and performance of systems
Automate deployment and maintenance tasks
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Design and build production ML systems for Reddit experiences.
Improve ranking, recommendations, search relevance, and signals.
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Develop core systems and infrastructure
Handle large volumes of events
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Lead specialized GPU pods management
Execute complex workload migrations
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Design dashboard for tracking JJ yield metrics
Integrate various data sources for analytics
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Propose, plan, and execute research initiatives impacting Conversational AI.
Utilize Transformer architecture for effective prompting and orchestration.
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Architect and build next-generation Conversational AI products.
Lead and mentor engineering teams.
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Efficient implementation of AI models
Prioritizing tasks based on urgency and impact
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Guide customers through product implementation and deployment.
Build custom demos and prototypes for customer use cases.
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Develop high-impact data science projects
Design, train, and validate statistical and ML models
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Shape technical roadmap
Architect and design deployment pipelines
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Apply ML/AI techniques in healthcare SaaS.
Collaborate with cross-functional teams.
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Build backend and frontend components equally
Collaborate on defining architecture
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Translate user stories into scalable technical designs
Architect secure, scalable Salesforce solutions
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Build a full-stack application from scratch
Collaborate with team members to define system architecture
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Develop and deliver full-stack code
Ensure testing, documentation, and observability standards
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Build backend and frontend components from scratch
Define architecture with cross-functional teams
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Collaborate on backend and frontend development
Own feature lifecycle from concept to production
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Lead ML projects and client discussions
Optimize ML models for performance and scalability
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Collaborate with different teams to design control plane architecture
Contribute to reliability testing for photonic products
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Develop high-impact data science projects
Train and validate ML models
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Develop and scale Python scripts for data analysis
Ensure accurate financial and regulatory reporting
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Apply ML/AI in healthcare systems
Collaborate with a diverse team
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Build and maintain reliable and scalable data pipelines for Growth use cases
Improve data models and schemas to meet evolving needs
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To build core sensor services in Golang (Kubernetes)
To optimize data delivery to SIEM/analytics platforms
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Execute test plans and analyze data
Troubleshoot and maintain test equipment
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Architect and build next-generation AI products
Lead and mentor engineering teams