Top Tech Jobs & Startup Jobs

Design, prototype, and productionize applied ML solutions across NLP, vision, recommendation, and structured data. Translate business problems into ML formulations, run rigorous experiments, build scalable training/inference pipelines, optimize for accuracy/latency/cost, implement monitoring and safety evaluations, and mentor engineers while influencing the AI roadmap.

Design and implement high-performance backend services and APIs in Go; build cloud-native applications and Kubernetes controllers; implement gRPC/REST, observability, and security; profile and optimize Go services; integrate messaging and data stores; write automated tests and documentation; lead code reviews and mentor engineers.

Design, build, and operate GPU/accelerator infrastructure for large-scale training and inference. Implement scheduling, storage, networking (RDMA/InfiniBand/NCCL), observability, checkpointing, fault tolerance, security, automation, and developer tools. Partner with ML teams to plan capacity, optimize costs, and maintain runbooks and operational dashboards.

Optimize end-to-end training and inference for large neural networks: profile pipelines, eliminate bottlenecks, implement quantization/pruning, tune distributed training and attention kernels, drive compiler-level and hardware evaluations, build benchmarks, and embed performance best practices across teams.

Deliver Guidewire configuration, Gosu development, and integrations across PolicyCenter, BillingCenter, and ClaimCenter. Implement product model and rules, build integrations, support Guidewire Cloud upgrades, optimize performance, create automated tests, troubleshoot production issues, and collaborate with cross-functional stakeholders to deliver robust insurance-platform features.

Lead design and evolution of large-scale microservices ecosystems: define architecture standards, decompose monoliths, specify communication and data patterns, ensure resilience, observability, security, CI/CD, and scalability; mentor teams, lead reviews, and evaluate cloud-native platform technologies.

Develop and maintain enterprise AEM Sites and Assets solutions, implementing components, templates, OSGi/Sling backend logic, headless delivery, CI/CD, performance tuning, integrations with Adobe Experience Cloud, and authoring/workflow improvements for cloud-native AEM deployments.

Build and operate petabyte-scale data systems for AI training and evaluation. Design ingestion, cleaning, versioning, lineage, high-throughput loading, labeling/active-learning pipelines, storage architectures, privacy controls, and observability. Collaborate with ML researchers to optimize model training efficiency and document operational procedures.

Design, build, and maintain Coupa integrations using Coupa Integration Cloud and iPaaS (MuleSoft/Boomi/Workato). Sync supplier, PO, invoice, payment, chart-of-accounts, and identity data; implement security, error handling, performance tuning, release planning, documentation, and production support.

Design and govern enterprise Salesforce solutions across clouds; lead architecture, integrations, security, DevOps, and org strategy; mentor engineers; produce architecture artifacts; partner with stakeholders to deliver scalable, maintainable Salesforce implementations.