Job Description
Job Description
Applied Research Engineer AI & Machine Learning
Location : San Francisco Bay Area (Hybrid)
Compensation : $250,000 - $300,000 Equity
Who Are We?
We are pioneering AI infrastructure , empowering leading research labs and enterprises to develop next-generation AI models .
Why Join Us?
- High-Impact Research Develop cutting-edge AI alignment methods , advancing how AI systems learn from human feedback .
- Fast-Paced Innovation Take ownership, move fast , and deliver groundbreaking solutions .
- Technical Excellence Work at the forefront of AI , collaborating with industry leaders.
- Clear Ownership Work autonomously with well-defined responsibilities and directly influence the future of AI .
What's In It for You?
Advance AI Alignment Design innovative human-in-the-loop data strategies such as RLHF, Direct Preference Optimization (DPO), and novel AI alignment approaches .Enhance Human Data Quality Develop measurement and refinement systems to optimize AI training data .Optimize AI-Assisted Data Labeling Build AI-powered active learning and adaptive sampling tools to reduce manual effort and improve annotation accuracy .Bridge Research and Real-World Application Integrate research breakthroughs into AI product development , making alignment scalable and impactful .Shape Next-Gen AI Models Investigate how different types of human feedback (demonstrations, preferences, critiques) impact AI performance .Influence Industry Innovation Engage with the AI research community, publish in top-tier conferences, and contribute to the evolution of AI ethics .Collaborate with Leading AI Teams Work closely with AI engineers, product teams, and industry researchers to drive human-AI alignment at scale .What Will You Need? Required Experience :
Ph.D. or Masters degree in AI, Machine Learning, or Computer Science (or equivalent research experience).3 years of hands-on experience in machine learning research and engineering , solving complex ML alignment challenges .Expertise in AI model alignment Experience with RLHF, active learning, reinforcement learning, or human preference-based optimization .Strong research background Track record of publishing in top-tier AI / ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL ).Deep understanding of large-scale AI models Experience working with LLMs, multimodal models, and frontier AI architectures .Proficiency in Python Experience with deep learning frameworks such as PyTorch, JAX, or TensorFlow .Strong analytical and problem-solving skills , with a structured, data-driven approach to tackling ambiguous AI challenges .Excellent communication and collaboration skills , enabling you to work effectively across research, engineering, and product teams .Ability to bridge research and application , rapidly translating new findings into functional AI prototypes .Preferred Experience (Nice to Have) :
Experience designing scalable AI-assisted data labeling systems .Familiarity with AI service APIs (e.g., OpenAI, Anthropic, Google AI) to develop product-driven AI applications .Understanding of memory management and optimization in data-intensive AI systems .Experience working on human-AI interaction frameworks .Why Join Us?
This is an opportunity to own and shape the future of AI alignment , working at the intersection of AI research, human feedback, and real-world AI applications . If you are passionate about advancing human-AI collaboration , thrive in high-growth AI environments , and want to drive AI innovation at the frontier , we want to hear from you.
Salary : $250,000 - $300,000
