Applied Research Engineer

Applied Research Engineer AI & Machine Learning

Location: San Francisco Bay Area (Hybrid)
Compensation: $250,000 - $350,000 + 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.