Job Description
About the position
- Responsibilities
- Collaborate with the Data Science and Machine Learning team to create AI solutions for constituents.
- Translate stakeholder needs into user-facing applications leveraging NLP techniques and LLMs.
- Work on products like conversational search interfaces, chatbots, and text summarizers.
- Partner with Product Managers and Engineers to develop production-grade algorithms.
- Architect the framework and infrastructure for GenAI products.
- Develop techniques to optimize model performance for product goals.
- Align technical roadmap with product management and engineering leads.
- Establish protocols for fair and transparent LLM applications.
- Lead efforts to assess and mitigate risks due to model biases.
- Implement feedback pipelines and monitoring for model safety.
- Design and curate high-quality datasets for LLM training.
- Build data science pipelines and provide documentation for re-usability.
- Communicate effectively to technical and non-technical audiences.
- Contribute research to academic conferences and journals.
- Requirements
- Minimum of seven years' post-secondary education or relevant work experience.
- Bachelors/Advanced Degree in Mathematics, Physics, Computer Science, Engineering, Statistics, or 8+ years equivalent work experience.
- 3-5 Years Experience in developing machine learning models in a commercial environment.
- Experience with production RAG pipelines and information retrieval systems.
- Strong Python skills required.
- Minimum of three years' experience building production NLP and deep learning models using PyTorch/Tensorflow.
- Experience with large language model architectures (BERT, GPT-3 etc.).
- Experience building advanced workflows using Langchain and similar tools.
- Proficiency with various prompting techniques and understanding of tradeoffs between prompting and finetuning.
- Experience with finetuning embedding models and tuning vector databases.
- Experience with cloud computing platforms - AWS.
- Prior experience in leading data science and machine learning.
- Nice-to-haves
- Proficiency in at least one open-source programming language (R, Java, C++ or another) and SQL.
- Experience establishing model guardrails and developing bias detection techniques.
- Ability to mentor and lead others; provide hands-on technical guidance.
- Ability to coordinate and track multiple deliverables across stakeholders.
- Experience working in agile methodology.
- Benefits
- Paid Time Off: 3-4 weeks of accrued vacation time per year, 12 accrued sick days, 12.5 holidays plus a Winter Recess, 3 personal days, and up to 12 weeks of paid leave for new parents.
- Comprehensive medical, dental, and vision benefits, disability and life insurance programs.
- Child and elder/adult care resources including on-campus childcare centers and wellness programs.
- University-funded retirement plan with contributions from 5% to 15% of eligible compensation.
- Tuition Assistance Program including $40 per class at the Harvard Extension School.
- Tuition Reimbursement Program providing 75% to 90% reimbursement for eligible courses.
- Professional Development programs and classes at little or no cost.
- Various commuter options including discounted parking and public transportation passes.
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