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Amazon Software Development Engineer, Eva Development Team
Software engineer on Amazon's AWS Data Center Gen AI team in Bellevue, building generative-AI platform features that orchestrate data center operations for a 30K+ user base — work spans LLM/agent systems, serverless AWS backends, React frontends, and search/ML data pipelines.
Amazon Senior Applied Scientist, LLM Code Agents, Kiro Science
Senior Applied Scientist on Amazon's Kiro LLM-training team at AWS, advancing reinforcement learning and post-training of large language models for code intelligence behind AI developer tools (Kiro IDE, Amazon Q Developer), shipping at Amazon scale and publishing at top ML/NLP conferences.
Senior Software Engineer - DevEx
Senior engineer on the developer-experience team of a fast-growing AI infrastructure company in Stockholm: improving and extending its SDK, CLI and platform interfaces, working directly with customers, and sharing on-call for owned systems. Office-based in Stockholm, with emphasis on API ergonomics and async/concurrent programming.
Software Engineer - Fullstack
Fullstack software engineer at Grasp, an agentic AI platform automating research for financial institutions. Builds and maintains scalable systems across the stack — data pipelines, APIs, and UI features — using TypeScript, React, and GCP. In-person role in Stockholm, working closely with the Head of Engineering and CPO.
Data Engineer
Data Engineer at Grasp, an agentic AI platform for finance, building and maintaining scalable data pipelines and tuned databases that feed LLM/RAG systems used by banks, PE firms, and consultancies. Onsite in Stockholm; focuses on data chunking/parsing, retrieval pipelines, and monitoring data process health.
Product Manager, AI Infrastructure
Product Manager on the Together Cloud team owning day-to-day feature work across AI infrastructure products — GPU clusters, managed storage, networking, and observability — with an early focus on observability and GPU clusters. Drives data-backed experimentation and cross-team delivery, with a path to owning a full product area within ~9 months.
Platform Engineer, Model Shaping
Platform engineer on Together AI's Model Shaping team, building and operating the backend services and infrastructure behind its model-customization and evaluation platform — production Linux/Kubernetes systems, multi-datacenter job orchestration over heterogeneous GPU hardware, plus CI/CD and observability tooling, using Python/Go, Terraform, and Prometheus/Grafana.
Specialiste Devops
DevOps Specialist at Coginov, a software company providing semantic text analytics for intelligent document and email management. The role oversees code releases and CI/CD deployments across production, test and QA environments using Git, GitLab and Jenkins, plus Windows/Linux administration, testing, troubleshooting and documentation.
Remote Python Backend Engineer (FastAPI) for AI Infra
Turing seeks a Software Engineering Evaluator to curate datasets that train and benchmark large language models — evaluating AI-generated code and writing precise solutions alongside researchers. Work centers on Python (FastAPI, backend services, data pipelines, ML infra) with exposure to JavaScript, C/C++, Java, Rust, and Go, on a flexible contractor basis.
AI Code Evaluator & Backend Engineer (Contract)
One-month contractor role (10-40 hrs/week) evaluating AI-generated code: curating training and benchmark datasets, building verification tools, and collaborating with researchers. Core focus is Python across backend services, data pipelines, and ML infrastructure. Note: posting lists Vancouver, Canada but description says candidates must be based in the United States.
JAVA Developer / Full Stack Developer
Contract role with Turing (posted via Randstad Canada) evaluating and refining AI-generated code: building agents that verify code quality, assessing model capabilities across the software engineering lifecycle, and designing automatic verification for coding tasks. Requires a full-stack engineering background; remote work at 10-40 hrs/week for a 1-month engagement.
Machine Learning Engineer - Inference
Machine Learning Engineer on Together AI's Inference Engine team, building and optimizing production systems that run large language model inference at scale. Day-to-day work centers on Python and PyTorch, high-performance runtime services, and low-level systems optimization (memory, threading, CUDA/Triton kernels).
Lead/Manager AI Infra Systems Engineering Team (Amsterdam)
Lead the SRE team in Amsterdam to manage production systems and infrastructure using Ansible, Terraform, and Kubernetes, ensuring reliability for an AI infrastructure company.
Hardware Security Engineer, New Grad (2027)
New-grad Hardware Security Engineer at Together AI, securing AI infrastructure end to end — hardware, firmware, BMCs, TPMs, secure boot, and cloud services — while building AI-assisted security tooling. Day-to-day involves implementing security controls, platform lifecycle automation in Python/Bash, and evaluating technologies like confidential computing and remote attestation.
Hardware Security Engineer Intern (Summer 2027)
A 12-week San Francisco internship on Together AI's security team, prototyping AI-assisted security tools and safeguarding AI infrastructure across hardware, firmware, OS, and cloud (BMCs, TPMs, secure boot, device identity). Work involves Python/Bash automation, platform lifecycle tasks, and researching areas like confidential computing and remote attestation.
Forward Deployed Engineer, Strategic Inference
A hands-on engineer acting as deep technical partner to strategic AI customers: optimizing LLM inference engines (vLLM, TensorRT-LLM, SGLang), tuning KV cache, parallelism, and quantization to hit performance targets, and guiding fine-tuning/post-training pipelines (LoRA, SFT, DPO, RLHF, GRPO) from POC to production, primarily in Python.
Forward Deployed Engineer, Post-Training
A hands-on ML specialist embedded with strategic customers, guiding LLM post-training efforts (fine-tuning and RL) from data strategy and algorithm selection through experiment design, evaluation, and compute sizing. Core tech: Python, LLM fine-tuning/RL methods like SFT, LoRA, DPO, GRPO, and PPO.
Forward Deployed Engineer (Inference & Post-Training) - Mandarin Speaking
Optimize and deploy large language models for enterprise customers, tuning inference engines and post-training pipelines to meet performance targets.
AI Infrastructure Systems Engineer (Amsterdam & London)
Build and maintain the AI infrastructure platform for a cutting-edge AI research company, using Kubernetes, Terraform, and Ansible to ensure high availability and scalability.
AI Infrastructure Systems Engineer
Build and automate GPU fleets for AI training and inference, designing systems that provision, monitor, and heal thousands of accelerators autonomously.