Ideal Candidate Profile
You combine academic rigor with practical engineering skills and exceptional client communication abilities. You will work end-to-end from project initiation through client delivery, comfortable both building sophisticated algorithms and presenting findings directly to clients. You excel at automating repetitive tasks and developing reusable frameworks that scale across multiple engagements. You should be comfortable implementing cutting-edge research while translating complex technical concepts into actionable business strategies. Strong presentation skills and the ability to build trust with senior executives are essential.
Equal Opportunities
In order to comply with equal pay and salary transparency laws in various locations, we believe the target range of base compensation in all locations within the United States for this role is $155k-$240k. Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, and location.
In addition to medical, dental and vision coverage, we offer a generous unlimited PTO plan, 401k program and comprehensive benefits plan. Additional perks and benefits include a month-long sabbatical, active employee advocacy groups, globally driven inclusivity initiatives, wellness days, summer Fridays and learning and development programs for our employees.
Required Qualification
- PhD in Computer Science, Computational Linguistics, Statistics, Mathematics, Economics, Econometrics, or related quantitative field
- Minimum 5 years of professional experience in data science, machine learning, or related roles
- Advanced NLP expertise: Deep understanding of transformer architectures, attention mechanisms, and modern NLP techniques
- Large Language Model proficiency: Hands-on experience with LLM fine-tuning, prompt engineering, RLHF, and deployment at scale
- Programming mastery: Expert-level Python, with strong knowledge of PyTorch/TensorFlow, Hugging Face ecosystem
- MLOps & Infrastructure: Experience with model deployment, monitoring, and scaling in production environments
- Experience writing production code and ensuring well-managed software delivery
- Experience with foundation models (GPT, BERT, T5, LLaMA, etc.)
- Knowledge of retrieval-augmented generation (RAG) systems
- Understanding of model compression techniques (quantization, distillation, pruning)
- Experience with evaluation metrics and benchmarking for language models