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AI Engineer (m/w/d)
Build and deploy machine learning models, RAG chatbots, and scalable data and model pipelines while working with large language models.
(Senior) AI Engineer (all genders)
The Senior AI Engineer will experiment with new model architectures, integrate LLMs into software products, and optimize model performance and latency. The role involves deploying, versioning, and serving machine learning models within an agile team environment.
Senior Backend Engineer
Senior Backend Engineer at HackerRank architecting and scaling core backend services using Python/Ruby/Go/Java/Node.js, PostgreSQL/MySQL, Redis, Kafka, and Docker/Kubernetes, with strong emphasis on AI-augmented development practices.
Senior Technical Program Manager, Core ML
Lead complex, multi-disciplinary technical programs for Google's Core ML team, driving standard software stacks, reducing fragmentation, and accelerating AI research-to-production transitions across Cloud, Search, Ads, and YouTube.
Senior Data Analytics Consultant
Senior consultant designs and delivers data analytics solutions for financial services clients, building predictive models and dashboards with tools like Python, Power BI, and AI-enabled techniques to drive business decisions.
Аналитик-разработчик в международное направление Финтеха
Design analytical and data infrastructure, evaluate recommendation algorithms and AI-agent performance for international BNPL fintech services using SQL and Python.
Algorithm - AI Research Engineer
AI Research Engineer developing proprietary LLMs for agentic tasks, RL post-training pipelines, and frontier AI research at a Korean AI chip company, primarily using PyTorch and deep learning frameworks.
Hardware - AI Chip Architect
Designs AI-native hardware architectures and RTL implementations for high-performance, energy-efficient AI chips, focusing on chip modules, simulation, and optimization for power, timing, and area.
Software Engineer, Agent System Developer
Builds and optimizes an agent system framework for AI-driven automation, integrating LLM-based reasoning, tool execution, and orchestration in a production environment.
Software Engineer, Compiler (AX Engineer)
Build and refine AI-assisted engineering workflows for FuriosaAI’s compiler team, optimizing development, debugging, and CI using LLM tools and automation to boost team productivity.
Software Engineer, Technical Writer & Document Specialist
This role involves creating and maintaining developer-facing documentation for FuriosaAI's SDK and LLM software stack using a docs-as-code approach. The engineer will build automated validation pipelines to ensure documentation accuracy against live hardware and code releases.
Software Engineer, Machine Learning Engineer (Agentic AI)
Develops autonomous agent systems that solve complex engineering problems via AI-driven exploration, optimization, and self-improvement, integrating LLM post-training and multi-agent workflows for production-grade solutions.
Solutions Architect - US
Design and deploy AI/LLM models on FuriosaAI’s RNGD NPU using the Furiosa SDK, running POCs, benchmarks, and debugging for US customers while translating technical capabilities into business value.
DevOps Intern
The DevOps Intern will assist in managing cloud-native infrastructure, including Kubernetes clusters, CI/CD pipelines, and observability stacks. The role focuses on automating operational tasks and ensuring the reliability of production systems using tools like Kubernetes, GitOps, and various cloud services.
Product Manager
Experienced Product Manager (10+ years) defining product vision/roadmap, driving cross-functional execution, and delivering scalable products. Works with Agile methodologies, customer research, and data analysis to align with business objectives.
Data Scientist
Data scientist leading client projects, analyzing diverse data, building ML models, and deploying scalable solutions using Python, cloud platforms, and CI/CD pipelines.
Data Engineer
Builds and maintains data pipelines for UK government clients in cybersecurity, telecoms, and data, focusing on ETL/ELT, cloud infrastructure (AWS/Azure/GCP), and data warehousing (Postgres, Spark, Kafka) to support analytics, ML, and mission-critical intelligence.