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Build and optimize large language models for insurance workflows, focusing on post-training, evaluation, and inference performance to improve underwriting and claims processing.
Build and deploy AI agents for fintech workflows (risk, fraud, payments) and the platform that powers them, including orchestration, tooling, and safety guardrails.
Builds and maintains the AI platform infrastructure, including model gateways, vector databases, and LLM evaluation tools, to integrate GenAI insights into agent workflows and downstream applications.
Principal AI/ML Architect designs and advises on production ML systems, MLOps/LLMOps pipelines, and GenAI architectures on AWS for enterprise clients, translating technical depth into business value.
Build and operate the ML infrastructure powering an AI assistant, focusing on model training, deployment, inference, and observability to enable reliable, scalable, and cost-efficient production systems.
Build and run the cloud infrastructure that serves SambaNova’s AI inferencing endpoints, ensuring high availability, low latency, and cost-efficient scaling across AWS, GCP, Azure, and on-prem.
Build and scale data pipelines that auto-tag petabytes of autonomous-truck logs, turning raw sensor data into curated driving scenarios for ML and simulation teams using Python, Databricks, and AWS.
Senior SRE builds and operates the platform that runs AI models reliably, implementing SLOs, observability, and incident response for a sovereign AI stack.
About the Role Sanas is looking for a Member of Technical Staff to lead the post-training and deployment of large language models across a new generation of self-hosted, sovereign-deployed products. This is a rare…
Build and deploy production-grade agentic AI and LLM applications for APAC enterprises, including RAG pipelines, multi-agent systems, and ML services across cloud and air-gapped environments.
Build and deploy LLM-powered agents and RAG systems using Python, FastAPI, and vector databases; optimize token costs and model performance for scalable AI applications.
Build and run a full-stack AI platform: React/TypeScript web app, Postgres telemetry, LLM fine-tuning and vLLM serving, plus MQTT/BMS integrations for heat-network decarbonisation.
Optimize AI training and inference workloads for speed, cost, and efficiency across the full stack, from GPU kernels to distributed systems, using Python, C++, and profiling tools.
Design and operate high-performance AI inference platforms, focusing on systems engineering for model serving, routing, caching, and autoscaling in production.
Build and maintain Python-based backend systems for cybersecurity data capture, compliance workflows, and AI-powered threat classification in a high-reliability environment.
Build and lead backend systems in Python for a cybersecurity platform that captures communications data, processes events, and integrates AI classification and agentic workflows across enterprise tools like Microsoft and Slack.
Build and deploy agentic AI systems for financial data, focusing on LLM orchestration, retrieval, and scalable workflows to power research and insights.
Architect and optimize LLM inference performance on NVIDIA GPUs, profiling vLLM, SGLang, TRT-LLM, and collaborating with teams to publish benchmark results and drive software advancements.
Build and deploy agentic AI systems for financial data, focusing on LLM orchestration, retrieval, and scalable workflows to power generative AI applications in finance.
Dive deeper. Aim higher. At Abysalto, that’s not just a motto — it’s how we work. We build serious tech for a variety of clients, but we keep things simple, fast, and focused. We’re a team driven by determination,…
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