About the job
At Scale, our mission is to craft dependable AI systems that influence the world's most vital decisions. We focus on:
- Building bespoke AI applications that benefit millions of citizens
- Producing high-quality training data for national Large Language Models (LLMs)
- Providing upskilling and advisory services to maximize the impact of AI
We are seeking talented Machine Learning Research Engineers to connect cutting-edge research with tangible real-world applications. In this role, you will not only implement solutions but also spearhead initiatives in Agent design, AI Safety, and Deep Research, creating innovative methodologies that enhance public sector applications and elevate standards throughout Scale.
Your mission encompasses three primary areas:
- Leading Research & Publication: Drive research into LLM/agent capabilities, reasoning, and safety, aiming for publication in top-tier venues such as NeurIPS, ICML, and ICLR.
- Cross-Organizational Impact: Develop generalized techniques in Agent design, AI Safety, and Deep Research agents to be applied across our commercial and governmental platforms.
- Mission-Critical Applications: Engineer high-stakes AI systems that have a profound impact on millions of citizens worldwide.
Your Responsibilities:
- Pioneer Innovative Architectures: Design and train state-of-the-art models and agents, moving beyond standard solutions to create customized architectures for complex public sector reasoning tasks.
- Lead AI Safety Initiatives: Research and implement robust safety frameworks, including red teaming, alignment (RLHF/DPO), and bias mitigation strategies crucial for sovereign AI.
- Drive Deep Research Capabilities: Develop agents capable of long-term reasoning and autonomous information synthesis to tackle intricate problems in national security and public policy.
- Publish and Contribute: Represent Scale within the broader research community by publishing influential papers and contributing to open-source advancements.
- Consult as a Subject Matter Expert: Serve as a technical authority for public sector leaders, providing insight into the theoretical limitations and safety considerations of emerging AI technologies.
- Establish Evaluation Standards: Create new benchmarks and evaluation protocols that define success for high-stakes, non-commercial AI applications.
