aion

Machine Learning Engineer

• Design and implement end-to-end LLMOps pipelines for model training, fine-tuning, and evaluation
• Fine-tune and customize LLMs (Llama, Mistral, Gemma, etc.) using full fine-tuning and PEFT techniques (LoRA, QLoRA) with tools like Unsloth, Axolotl, and HuggingFace Transformers
• Implement RLHF (Reinforcement Learning from Human Feedback) pipelines for model alignment and preference optimization
• Design experiments for automated hyperparameter tuning, training strategies, and model selection
• Prepare and validate training datasets—ensuring data quality, preprocessing, and format correctness
• Build comprehensive model evaluation systems with custom metrics (BLEU, ROUGE, perplexity, accuracy) and develop synthetic data generation pipelines
• Optimize model accuracy, token efficiency, and training performance through systematic experimentation
• Design and maintain prompt engineering workflows with version control systems
• Deploy models using vLLM with multi-adapter LoRA serving, hot-swapping, and basic optimizations (speculative decoding, continuous batching, KV cache management)
• Set up ML-specific monitoring for model quality, drift detection, and performance tracking with automated retraining triggers
• Manage model versioning, artifact storage, lineage tracking, and reproducibility using experiment tracking tools
• Debug production model issues and optimize cost-performance trade-offs for training and inference
• Partner with infrastructure engineers on ML-specific compute requirements and deployment pipelines
• Document model development processes and share knowledge through internal tech talks

Machine Learning Engineer, Platform

Full-stack Engineer

• Design AION as a composable platform with independently deployable components that run seamlessly on AWS, GCP, Azure, and private data centers
• Work with senior engineering leads to define private deployment strategies and build automation for customer VPC and on-premises installations
• Build abstraction layers that unify diverse cloud providers while maintaining flexibility for customer-specific requirements
• Design globally distributed deployment patterns with built-in data sovereignty, compliance, and regulatory requirements
• Own end-to-end platform deployment automation using Terraform, Ansible, Helm, and infrastructure-as-code across hybrid cloud environments
• Design and implement disaster recovery, failover, high-availability architectures, and cloud migration strategies for customer deployments
• Build comprehensive CI/CD pipelines for infrastructure provisioning, configuration management, and deployment orchestration
• Implement monitoring, observability (Prometheus, Grafana, Loki), and alerting systems tailored for customer-managed AION instances
• Implement Kubernetes-based and custom orchestrator-based managed services with strict workload isolation and multi-tenancy
• Design container security, runtime protection, network policies, and secrets management for production workloads
• Own compliance implementation (SOC2, GDPR, HIPAA, ISO 27001, PCI-DSS) and security best practices for customer environments
• Create deployment blueprints, reference architectures, self-service portals, and comprehensive documentation for customer success

Senior Software Engineer, Infrastructure – Deployments

• Design and architect AION's multi-cloud compute platform, building abstraction layers that unify diverse cloud providers (AWS, GCP, Azure, bare-metal data centers)
• Work directly with cloud providers to expand AION's compute pool—understanding pricing, availability zones, GPU types, and capacity planning
• Build and maintain the AION managed services
• Understand and abstract cloud provider differences in storage (block, object, file systems), networking (VPCs, subnets, security groups), and compute resources
• Design composable platform components that enable forward deployments and promote reusability across AION's infrastructure stack
• Own end-to-end development of managed services on the compute platform—from design and architecture through execution and production monitoring
• Build scalable orchestration systems for GPU workloads, container scheduling, and resource allocation
• Develop robust APIs and control planes for compute lifecycle management (provisioning, scaling, termination)
• Lead technical discussions on platform reliability, performance optimization, and cost efficiency
• Execute on peripheral platform services including billing systems, usage accounting, observability infrastructure, and compliance tooling
• Build monitoring and telemetry systems for compute utilization, cost tracking, and performance metrics
• Establish engineering standards for platform development including code reviews, quality gates, and testing practices
• Mentor engineers on infrastructure best practices and distributed systems design

Senior Software Engineer, Compute Platform

Product Marketing

• aion is building the next generation of AI cloud platform by transforming the future of high-performance computing (HPC) through its decentralized AI cloud.
• Purpose-built for bare-metal performance, aion democratizes access to compute power for AI training, fine-tuning, inference, data labeling, and beyond.
• By leveraging underutilized resources such as idle GPUs and data centers, AION provides a scalable, cost-effective, and sustainable solution tailored for developers, researchers, and enterprises.
• Headquartered in the US, the company has a global presence with core teams in London, Seattle and India.
• Define and execute AION’s go-to-market strategy to drive adoption and growth.
• Build and manage lead funnels through targeted inbound/outbound campaigns.
• Partner with product and engineering to align platform development with customer needs.
• Lead marketing initiatives, including messaging, content, and events to grow awareness and demand.
• Develop strategic partnerships with cloud providers, GPU operators, and AI ecosystem players.
• Build and nurture AION’s community of developers and researchers to strengthen brand presence.
• Own the sales playbook, CRM systems, and pipeline to scale customer acquisition and revenue.
• Build and maintain executive-level relationships with key customers and partners.

Machine Learning Engineer, Platform

Senior Software Engineer, Infrastructure – Deployments

Senior Software Engineer, Compute Platform

Founding Go-to-Market Lead