Senior/Staff Machine Learning Engineer (Search & Recs)

About

The Search & Recommendation Team’s mission is to accelerate our ability to return billions of hours to scientists by empowering them with the most relevant content in the most highly trafficked part of our application: the core illustrator.

As the first Machine Learning Engineer/Applied Scientist, you will partner with product, design, and engineering to build the ML and AI system that enables scientists to effortlessly create beautiful and effective figures. We are looking for individuals at senior and staff levels who are product driven, and are passionate about making ML innovations in areas such as; Ranking, Natural Language Processing, Information Retrieval, Graph Learning, Reinforcement Learning to help improve the BioRender user experience! Excitement for applied research is a must as you combine rigorous thinking with practical tooling to meet these modeling challenges efficiently.

Responsibilities

• Design and execute multi-quarter ML initiatives that deliver measurable technical, organizational, or business impacts in our Search & Recommendations domain.
• Oversee the performance and continued optimization of our search engine and recommendation systems: build machine learning models to improve query understanding, and extract user intent and context to deliver accurate, relevant, and personalized results for users.
• Prototype, optimize, and productionize ML models that help deliver key results.
• Evaluate performance of search and recommendation systems and models end to end.
• Influence the company’s ML system and data infrastructure to power personalization, recommendations to make it faster for our users to create communication materials.
• Collaborate closely with product managers, scientists, full-stack engineers, and designers on product teams.
• Communicate with business, data, and engineering counterparts to clarify requirements, provide feedback, and share discovered data stories with stats, charts, and formal presentations. Propose recommendations to maximize business impact.

Requirements

Must Haves

• Extensive industry experience as an ML engineer with expert level knowledge in one or more areas: Information Retrieval, Recommender Systems, Learning-to-Rank, Large Language Models, NLP, Deep Learning, Transfer Learning, Multi-task Learning, Graph Neural Network, Human-in-the-loop or similar
• Hands-on experience with with both traditional keyword-based search technologies as well as modern search paradigm utilizing vector-based retrieval algorithms and search systems such as Elasticsearch
• Experience with deep learning frameworks such as PyTorch and TensorFlow
• Experience with data exploration, analysis, and feature engineering
• Excellent programming skills with one or more of the following languages python, scala, java
• Expertise with operationalizing, monitoring, and scaling machine learning models and pipelines in cloud ecosystems
• Previous experience working cross-functionally with product and engineers to deliver solutions with complex requirements in an agile environment

Nice to have

• Familiar with the state-of-the-art ML/AI research with publication track record
• Experience with Generative AI, Langchain, Transformer models or related
• You have experience building a variety of ML applications end to end
• Scientific and research background