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The MLOps Lead Engineer will design and automate end-to-end machine learning production lifecycles on the Databricks Lakehouse platform. This role involves leading technical implementations, managing CI/CD/CT pipelines, and providing governance and upskilling for client-side engineering teams.
The Staff Software Engineer will lead the architecture and development of a production-critical platform for manufacturing, utilizing Python, FastAPI, React, TypeScript, and Java. The role involves building scalable, event-driven systems, integrating cloud infrastructure, and applying AI/ML to optimize manufacturing operations.
This role involves developing and optimizing low-level GPU kernels and math primitives for the oneDNN library to accelerate AI frameworks on Intel hardware. The engineer will focus on performance modeling, hardware co-design, and kernel architecture using C++.
Leads customers in designing and implementing secure, scalable big data solutions on Databricks, focusing on cloud infrastructure, security, and performance optimization for production workloads.
Build production-grade AI solutions and LLM applications in Python, integrating APIs and optimizing performance on AWS for a global investment fund.
The Solution Architect will design and deploy AI environments, manage MLOps/LLMOps pipelines, and implement RAG systems across various infrastructure types. The role involves hands-on engineering, AI governance, and mentoring teams while collaborating with global stakeholders.
Business Analyst driving AI adoption in Singapore’s public sector by identifying automation opportunities, prototyping solutions, and translating technical concepts for non-technical stakeholders.
The AI Solutions Engineer designs, develops, and deploys AI and LLM solutions to solve business challenges. The role involves optimizing models, managing deployment pipelines, and collaborating with cross-functional teams using tools like Python, PyTorch, TensorFlow, and cloud AI services.
The GPU Digital Frontend Design Engineer will define microarchitecture, design RTL for high-performance GPU/AI accelerator chips, and optimize for power, performance, and area. The role involves collaborating with verification, software, and physical design teams using Verilog/SystemVerilog and standard EDA tools.
The Technical Business Analyst will identify operational inefficiencies to solve with AI, design AI prototypes, and drive AI adoption across the organization. The role involves collaborating with stakeholders to build AI literacy, monitoring project performance, and developing standards for responsible AI implementation.
The SoC Digital Design Engineer will design and implement hardware accelerators for video codecs and SoC subsystems using Verilog/SystemVerilog. The role involves architecture definition, RTL implementation, and cross-functional collaboration to optimize power, performance, and area for large-scale video platforms.
The AI Engineer will develop Python-based agentic AI workflows and AIOps solutions to automate infrastructure diagnostics, incident response, and predictive alerting. The role focuses on integrating these AI capabilities into CI/CD pipelines to enhance system reliability and observability.
The Senior Specialist Solutions Architect for GenAI at AWS works with startups to drive the adoption of AWS AI services, providing technical leadership and strategic guidance to founders and developers. The role involves building go-to-market plans, creating reference architectures, and acting as a trusted advisor to help startups scale their inferencing and agentic workloads on AWS.
The Solution Architect will design and implement scalable multi-cloud and Generative AI solutions for clients, bridging business requirements with technical execution. The role focuses on AWS, Azure, and GCP environments, utilizing LLMOps, RAG, and agentic AI frameworks to deliver production-grade platforms.
Drive AI adoption in government by identifying automation opportunities, prototyping solutions, and training teams to use LLMs responsibly in daily workflows.
Designs and delivers multi-cloud, AI-driven enterprise solutions (GenAI/Agentic AI, RAG, LLMOps) for clients, leading architecture, POCs, and technical delivery across AWS/Azure/GCP.
The Business Analyst (AI) identifies AI opportunities, bridges business needs with tech solutions, and drives AI adoption across processes, focusing on Generative AI and LLMs.
Designs, configures, and maintains ICT infrastructure for platform operations, ensuring compliance with security and regulatory policies while leveraging AI to automate testing and improve efficiency.
A Technical Business Analyst focused on identifying AI automation opportunities in public sector operations, designing AI prototypes, and driving adoption across government divisions while ensuring responsible AI use and tracking efficiency gains.
Hands-on QA Engineer/SDET focused on backend API testing and automation, integrating tests into CI/CD pipelines while leveraging AI tools to enhance testing workflows. Core stack includes TypeScript/Python, Jest, Playwright, Pytest, SQL, Redis, and ELK.
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