Applied Researcher I (AI Foundations)
$218,700–$249,600 year
On-siteMcLean, Virginia, United States
EXPIREDMcLean, Virginia, United StatesOn-siteFull Time$218,700–$249,600 yearEnterprise
Full TimeEnterprise
Job Summary
Partner with cross-functional teams to deliver AI-powered products that reshape customer interactions with financial services. Leverage Pytorch, AWS Ultraclusters, and VectorDBs to extract insights from massive numeric and textual datasets. Build AI foundation models through design, training, evaluation, and implementation, translating complex research into tangible business goals. Engage in high-impact applied research to push emerging AI developments into next-generation customer experiences.
Required Qualifications
- Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date
- M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research
- Has a deep understanding of the foundations of AI methodologies
- Experience building large deep learning models, whether on language, images, events, or graphs
- Expertise in training optimization
- Expertise in self-supervised learning
- Expertise in robustness
- Expertise in explainability
- Expertise in RLHF
- An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes
- Experience in delivering libraries, platform level code or solution level code to existing products
- A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects
- Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects
Desired Qualifications
- PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields
- LLM
- PhD focus on NLP or Masters with 5 years of industrial NLP research experience
- Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization)
- Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens)
- Publications in deep learning theory
- Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR
- Optimization (Training & Inference)
- PhD focused on topics related to optimizing training of very large deep learning models
- Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression
- Experience optimizing training for a 10B+ model
- Deep knowledge of deep learning algorithmic and/or optimizer design
- Experience with compiler design
- Finetuning
- PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning)
- Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance
- Experience deploying a fine-tuned large language model
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