Artificial Intelligence Researcher

Job Title : Applied Researcher

Location : District of Columbia

Type : Full Time

Job Summary

Our client is seeking a world-class AI Research Scientist to join a cross-functional team of data scientists, software engineers, and product managers focused on developing next-generation AI systems that transform how customers interact with their finances. This is an opportunity to work at the forefront of large-scale AI model development, research, and deployment—turning cutting-edge ideas into real-world impact.

What You’ll Do

• Collaborate with diverse technical teams to design, train, and deploy AI foundation models that power innovative customer experiences.
• Work with advanced technologies such as PyTorch, AWS UltraClusters, Hugging Face, Lightning, and vector databases to extract insights from massive structured and unstructured datasets.
• Drive the full lifecycle of model development — from conceptual design and experimentation to training, evaluation, validation, and scalable implementation.
• Conduct high-impact applied research, adapting the latest advancements in deep learning and generative AI to practical business solutions.
• Translate complex AI research into clear business strategies and measurable outcomes, engaging with senior stakeholders and product teams.
• Push the boundaries of AI by contributing to new methodologies in self-supervised learning, optimization, explainability, and reinforcement learning with human feedback (RLHF).

The Ideal Candidate

• Passionate about building transformative AI systems that balance innovation, scalability, and responsible development.
• Technically strong, with hands-on experience developing and deploying large-scale deep learning models for language, vision, or multi-modal applications.
• Brings an engineering mindset, with proven experience building production-ready ML pipelines, optimizing training and inference performance, and contributing to platform-level codebases.
• Innovative thinker, driven by curiosity and creativity — comfortable defining open-ended research problems and pushing for novel solutions.
• Demonstrated thought leadership in AI research, evidenced by first-author publications, open-source contributions, or impactful projects in the ML community.
• Deep understanding of core AI principles, such as training optimization, transfer learning, robustness, and model interpretability.

Basic Qualifications

• PhD (or in process) in Computer Science, Electrical/Computer Engineering, Artificial Intelligence, Applied Mathematics, or a related discipline — or
• Master’s degree with 4+ years of experience in applied AI or machine learning research.

Preferred Qualifications

• PhD in Computer Science, Machine Learning, or Applied Mathematics with a focus on Natural Language Processing (NLP) or Deep Learning.
• Hands-on experience training or fine-tuning large language models (10B+ parameters, 500B+ tokens).
• Published research at top-tier conferences such as NeurIPS, ICML, ICLR, ACL, NAACL, or EMNLP.
• Expertise in one or more of the following domains:
• Pre-training and self-supervised learning for large models
• Training and inference optimization, including quantization, sparsification, parallelism, and model compression
• Finetuning and instruction tuning for LLMs, including transfer learning and dialogue adaptation
• Compiler or optimizer design for large-scale deep learning
• Proven experience deploying and optimizing AI systems in cloud environments (AWS, Azure, or GCP).