AI Scientist - Open budget Project / Full remote Okay

We are looking for an experienced AI scientist to design and deploy machine learning systems across predictive diagnostics, enterprise collaboration, and generative agents. You'll be advancing the core ML architecture for high-impact platforms used by major industrial clients.

Client Details

This remote-first, venture-backed startup is developing AI-native platforms for enterprise and industrial applications. With a focus on solving complex real-world problems, the team blends deep technical talent with a pragmatic product mindset to deliver scalable, high-performance AI solutions.

Description

• Develop and optimize ML models for predictive maintenance using time-series data (RUL prediction, anomaly detection, root cause analysis)
• Fine-tune LLMs and transformer-based models for technical document understanding and automation
• Build and refine RAG pipelines that integrate vector search with LLMs for high-precision enterprise retrieval
• Define robust evaluation frameworks to ensure reliability and accuracy in industrial and collaboration contexts
• Collaborate cross-functionally to deploy ML systems across on-prem and cloud environments for various platforms

Job Offer

• Long-term renewable contract
• Potential path to permanent employment
• Competitive compensation
• Attractive benefits package
• International and remote-first work culture
• Strong opportunities for career growth and technical leadership

To apply online please click the 'Apply' button below. For a confidential discussion about this role please contact Hikari Takamura on +813 6832 8903.

• Proven working experience in applied AI/ML, with a strong background in predictive modeling and diagnostics
• Expertise in LLM fine-tuning, transformer architectures, and AI agent frameworks (e.g., LangChain)
• Proficient with tools including Python, PyTorch/TensorFlow, HuggingFace, MLflow, Airflow, vector databases, and big data frameworks
• Deep understanding of full ML pipelines from data ingestion to production deployment
• Comfortable working closely with engineers and stakeholders in complex enterprise environments