Description:

BenchSci is seeking a Senior Machine Learning Engineer to join their Knowledge Enrichment team.
The role involves designing and implementing ML-based approaches to analyze, extract, and generate knowledge from complex biomedical data.
The data sources include both publicly available and proprietary internal data, represented in unstructured text and knowledge graphs.
The engineer will work to enrich BenchSci’s knowledge graph through classification, discovery of high-value implicit relationships, and predicting novel insights using various ML techniques.
Responsibilities include analyzing a large biological knowledge graph, collaborating with data and knowledge engineering experts, and delivering robust, scalable ML models.
The engineer will architect and design ML solutions, from data collection to deployment and monitoring.
Collaboration with product management, project management, and science teams is essential, as well as providing technical leadership on Knowledge Enrichment projects.
Participation in agile rituals and practices is expected.

Requirements:

A minimum of 3 years of experience as an ML engineer, ideally 5+ years.
Experience in providing technical leadership on complex projects is preferred.
A degree, preferably a PhD, in Software Engineering, Computer Science, or a related field is required.
Proven track record of delivering complex ML projects in agile environments, with proficiency in state-of-the-art NLP and ML techniques.
Mastery of several ML frameworks and libraries, with extensive experience in Python and PyTorch.
Experience with the full ML development lifecycle, including architecture, data collection, model training, and deployment.
Familiarity with Large Language Models and Retrieval Augmented Generation (RAG) architecture is necessary.
Experience with graph machine learning and knowledge graphs, particularly in the biological domain, is preferred.
Strong problem-solving skills and attention to detail regarding scalability and performance.
Comprehensive knowledge of software engineering principles and programming fundamentals, particularly in Python.
Experience with data manipulation and processing tools such as SQL, Cypher, or Pandas is required.
A proactive and assertive attitude is essential, along with experience in cross-functional teams.
Outstanding verbal and written communication skills are necessary to explain complex concepts to both technical and non-technical stakeholders.
A growth mindset and engagement with the ML/AI community are important.

The position offers the opportunity to work remotely, providing flexibility in work location.
Employees will collaborate with some of the brightest minds in tech, contributing to the mission of expediting drug discovery.
The role allows for the application of cutting-edge ML/AI techniques in a fail-fast environment focused on value delivery.
There is an emphasis on professional growth and staying up-to-date with advances in ML/AI.
The company fosters a culture of freedom and responsibility, allowing employees to take ownership of their work.