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ML Research Engineer at Callosum designing experiments to understand why agentic AI systems fail, building evaluation infrastructure, and publishing findings to improve heterogeneous model/hardware orchestration.
Build and improve an LLM-guided evolutionary search system that iteratively generates, evaluates, and optimises programs across kernels, inference runtimes, and scheduling policies, working with optimisation and search algorithms at an AI infrastructure startup in London.
Build and own a unified benchmarking system for evaluating agentic and algorithmic LLM solutions at Callosum's London office, using Python, sandboxed execution, and distributed systems to produce reproducible, contamination-controlled evaluation results.
Build the networking and interconnect systems that let heterogeneous AI accelerators communicate efficiently, spanning RDMA, programmable NICs, memory movement, and cluster fabric strategy at Callosum's London office.
Build and maintain production-grade AI agents for India’s largest banks, insurers, and government departments, treating agents as engineered artifacts with versioning, evals, and regression suites.
Leads end-to-end client engagements and a small engineering pod, focusing on multi-cloud platform engineering, AI solutions, and digital transformation for enterprises. Owns scope, delivery standards, and team growth while refining company-wide playbooks.
Builds and optimizes Web3 big-data pipelines (on-chain transactions, smart-contract events) and integrates AI/LLM features like Text2SQL and anomaly detection to power analytics, risk models, and AI-driven data products.
On-site Field Solution Engineer responsible for physically installing, configuring, and troubleshooting AI infrastructure (DGX/HGX/MGX nodes, switches, storage) in Australian/New Zealand data centers. Focuses on Layer 1 execution, fault diagnosis, and hardware/software integration for AI factories, bridging offshore engineering teams with on-premise operations.
Leads AI-powered product strategy from discovery to launch, aligning technical feasibility with user needs and business goals.
The Senior Solutions Engineer manages the full lifecycle of customer engagements, from pre-sales discovery and solution design to post-signature implementation and delivery. This role requires deep expertise in cold chain logistics and supply chain processes to bridge the gap between commercial commitments and technical execution.
The Senior DevSecOps Manager will lead a team of engineers to secure Gong's multi-cloud infrastructure, focusing on automation, identity governance, and CI/CD pipeline security. This hands-on role involves defining security roadmaps and implementing security-as-code to support a large-scale AI-driven revenue platform.
The Engineering Manager will lead a team of ML and platform engineers to build and maintain production-grade AI infrastructure for Xero's financial products. The role focuses on team development, MLOps maturity, and balancing technical delivery with system health.
The Senior Data Scientist will lead complex data science engagements, combining traditional statistical modeling with Generative AI and LLM techniques. The role involves hands-on development, client communication with C-level stakeholders, and technical leadership of junior team members.
An internship to design, test, and integrate AI-driven threat-simulation features into a cybersecurity platform using Python, prompt engineering, and workflow automation tools.
The AI Data Engineer will design technical data pipeline architectures and implement change management frameworks to help client organizations integrate AI. The role requires expertise in SQL, Python, and Spark, alongside strong skills in process optimization and stakeholder management.
Build and secure cloud-native platforms at the intersection of software, IoT, and edge computing. Day-to-day: design AWS security guardrails, embed DevSecOps, and automate security controls across multi-account environments.
The Senior Forward Deployed Solution Engineer will work directly with customers to design, deploy, and troubleshoot complex infrastructure architectures involving Kubernetes, AI/GPU systems, and cloud-native environments. This hands-on role requires deep technical expertise in automation and systems engineering to ensure successful customer outcomes and production readiness.
Design and build memory architectures for AI models to store, retrieve, and exploit long-horizon experience across modalities using Python and PyTorch.
Design ML architectures for long-horizon memory in game engines and AI systems, building scalable models to store, retrieve, and reason over experience.
Design memory architectures for AI models to store, retrieve, and exploit experience across modalities, improving long-horizon decision-making in production systems.
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