BenchSci is a company focused on expediting drug discovery through machine learning and artificial intelligence solutions.

BenchSci is at the forefront of accelerating drug discovery through advanced machine learning and AI technologies. We're seeking a Senior Machine Learning Engineer to join our Knowledge Enrichment team, where you'll work with complex biomedical data and knowledge graphs to drive innovation in drug discovery.

In this role, you'll be instrumental in designing and implementing ML-based approaches to analyze, extract, and generate knowledge from various biomedical data sources. You'll work with both public and proprietary data, leveraging state-of-the-art machine learning techniques to enrich BenchSci's knowledge graph through classification, relationship discovery, and novel insight prediction.

The position offers a unique opportunity to work alongside leading experts in tech while tackling meaningful challenges in the biotech industry. You'll be part of a team that pushes the boundaries of what's possible with cutting-edge ML/AI, operating in a fail-fast environment focused on delivering value.

Your work will directly impact the company's mission by ensuring we maintain an extensive, accurate, and high-quality representation of biomedical data. You'll collaborate with cross-functional teams, including product managers, scientists, and engineers, while providing technical leadership on knowledge enrichment projects.

The ideal candidate brings a strong background in machine learning, particularly in graph ML and NLP, combined with experience in biological data. You'll need to be comfortable with the full ML development lifecycle, from architecture to deployment, and have a proven track record of delivering complex ML projects in production environments.

This remote position offers the flexibility to work from anywhere while being part of a mission-driven company that's making a real impact in drug discovery. If you're passionate about applying cutting-edge ML techniques to solve complex biological problems and want to work in an environment that values innovation and technical excellence, this role presents an exciting opportunity to advance your career while contributing to meaningful scientific advancement.

Senior Machine Learning Engineer position at BenchSci, focusing on knowledge graph enrichment and biomedical data analysis using cutting-edge ML techniques to accelerate drug discovery.

Senior Machine Learning Engineer - Knowledge Graph

BenchSci develops AI-powered solutions for biomedical research and scientific discovery.

BenchSci is seeking a Lead Machine Learning Engineer to join their Knowledge Enrichment team, focusing on advancing biomedical research through sophisticated ML applications. This role combines cutting-edge machine learning with biological data analysis, working with complex knowledge graphs and heterogeneous data sources. The position offers an opportunity to lead technical initiatives in applying state-of-the-art ML and graph ML algorithms to biomedical data.

The role involves analyzing and enriching a large biological knowledge graph, developing sophisticated ML solutions for data classification and relationship discovery, and implementing production-ready models. You'll work with various data types, from unstructured text to complex knowledge graphs, and apply advanced techniques including Large Language Models and Retrieval Augmented Generation.

As a technical leader, you'll guide a team of 5-10 engineers, collaborate with cross-functional teams, and shape ML best practices. The ideal candidate brings 8+ years of ML engineering experience, deep expertise in graph machine learning, and a strong background in implementing complex ML systems. This position offers the unique opportunity to impact healthcare and biomedical research while working with cutting-edge AI technologies.

The role is fully remote, allowing for flexible work arrangements while contributing to meaningful scientific advancement. You'll be part of a team that values innovation, embraces failure as a learning opportunity, and focuses on delivering high-impact solutions in the biomedical field.

Lead Machine Learning Engineer position at BenchSci, focusing on graph ML and knowledge enrichment for biomedical data analysis, requiring 8+ years of ML experience and technical leadership skills.

Lead Machine Learning Engineer Graph ML

BenchSci develops advanced biomedical artificial intelligence software platform to accelerate life-saving research and development for pharmaceutical companies and academic centers.

BenchSci is revolutionizing life-saving research and development through their advanced biomedical AI platform. As a Senior Software Engineer, Data on the Knowledge Enrichment Team, you'll play a crucial role in evolving BenchSci's Knowledge Graph and integrating vital life science data into their biological ontology.

The position offers an exciting opportunity to work with cutting-edge technology in the intersection of data engineering and life sciences. You'll be responsible for scaling data pipelines, managing complex biological data structures, and improving internal tooling for data self-service. The role requires expertise in Python, SQL, and cloud development, with a focus on both batch and streaming ETL pipelines.

Working in a remote-first environment, you'll collaborate with a world-class team of engineers, scientists, and product managers. The company offers comprehensive benefits including equity options, health coverage, and professional development opportunities. BenchSci's culture emphasizes transparency, continuous learning, and diversity, making it a certified Great Place to Work®.

The ideal candidate brings 5+ years of software engineering experience, strong technical skills in data modeling and cloud architecture, and the ability to communicate complex technical concepts clearly. You'll have the opportunity to shape the future of scientific discovery while working with leading pharmaceutical companies and academic centers.

This role is perfect for someone who thrives in a fast-paced, mission-driven environment and wants to make a meaningful impact in the biotech industry. With backing from major investors like Google's AI fund and a strong focus on employee growth, BenchSci offers an unmatched opportunity for professional development and contribution to life-saving research.

Senior Software Engineer, Data position at BenchSci, focusing on evolving Knowledge Graph, integrating life science data, and building scalable data pipelines in a remote environment.

Senior Software Engineer, Data

BenchSci develops advanced biomedical artificial intelligence software platform to help scientists accelerate life-saving research and development.

BenchSci is revolutionizing life-saving research through their advanced biomedical AI platform. They're seeking a Senior Machine Learning Engineer to join their Knowledge Enrichment team, focusing on analyzing and extracting insights from complex biomedical data. The role combines cutting-edge ML/AI technology with practical applications in drug discovery, working with knowledge graphs and biological data. Backed by major investors including Google's AI fund, BenchSci serves 16 top pharmaceutical companies and 4,300+ academic centers. The position offers the opportunity to work with bright minds in tech, using state-of-the-art approaches in a remote environment. The company emphasizes a strong culture of transparency, continuous learning, and diversity, making it a certified Great Place to Work®. This role is perfect for someone passionate about applying ML to meaningful scientific challenges, comfortable with both technical leadership and hands-on development, and excited about working in a fast-paced, innovative environment that directly impacts scientific research.

Senior Machine Learning Engineer position at BenchSci, focusing on graph ML and biomedical data analysis to accelerate drug discovery research.

BenchSci Engineering Jobs

BenchSci is a company focused on expediting drug discovery through machine learning and artificial intelligence solutions.