Job Title: Applied Researcher I
Job Responsibilities:
- Collaborate with a cross-functional team comprising data scientists, software engineers, machine learning engineers, and product managers to create AI-driven products that transform customer interactions with their finances.
- Utilize a diverse array of technologies such as Pytorch, AWS Ultraclusters, Huggingface, Lightning, and VectorDBs to uncover insights from extensive volumes of numeric and textual data.
- Develop AI foundation models through all stages, including design, training, evaluation, validation, and implementation.
- Engage in impactful applied research to integrate the latest AI advancements into the next generation of customer experiences.
- Translate complex work into tangible business objectives using interpersonal skills.
Education and Experience Information:
Basic Qualifications:
- Currently pursuing or having obtained a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with the degree required to be obtained before the scheduled start date, or
- . in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields with 2 years of experience in Applied Research.
Preferred Qualifications:
- PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering, or related fields.
- LLM with 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.
- Experience as a member of a team that has trained a large language model from scratch.
- Publications in deep learning theory and at conferences such as ACL, NAACL, EMNLP, Neurips, ICML, or ICLR.
- Expertise in optimization, including model sparsification, quantization, training parallelism/partitioning design, gradient checkpointing, and model compression.
- Experience in optimizing training for large models and deep knowledge of deep learning algorithmic or optimizer design.
- Experience with compiler design.
- Expertise in finetuning, including supervised finetuning, instruction-tuning, dialogue-finetuning, and parameter tuning.
- Demonstrated knowledge of transfer learning, model adaptation, and model guidance.
- Experience deploying a fine-tuned large language model.
Salary Information:
The full-time annual salary range for this role varies by location:
- Cambridge, MA: $214,500 - $244,800
- McLean, VA: $214,500 - $244,800
- New York, NY: $234,000 - $267,000
- San Francisco, CA: $234,000 - $267,000
- San Jose, CA: $234,000 - $267,000
Candidates hired to work in other locations will have a pay range associated with that location. The actual annualized salary offered to any candidate will be reflected in the candidate’s offer letter. This role is eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives, discretionary or non-discretionary depending on the plan.
Company offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits to support total well-being. Eligibility varies based on employment status and management level.
