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Entalpic is an AI-driven deep tech company at the intersection of machine learning, computational chemistry, and materials science. The company is building tools to engineer materials and manufacturing processes at the atomic scale, with initial focus on the semiconductor industry (thin films, interfaces, ALD, ALE) and expanding into catalysis, batteries, and photovoltaics. Backed by $10M in funding, Entalpic works with leading industrial and research partners to connect materials discovery, process optimization, and device performance.
You will join the Experimental Data Team as a Scientific Software Engineer, reporting to the Experimental Data Team Lead. Your role bridges chemistry, scientific data, and AI, transforming scientific literature, patents, and experimental lab data into high-quality structured datasets that power Entalpic's materials and molecules discovery platform.
Key responsibilities include:
• Scientific Data Modeling: Leverage your chemistry and materials science expertise to understand scientific problems, define clear schemas, and create extraction specifications for chemical properties, materials, and experimental processes.
• Agentic Scientific Extraction: Design and build agentic workflows using LLMs and scientific tools to extract structured information from scientific literature and experimental data.
• Data Quality & Evaluation: Develop robust quality mechanisms for scientific datasets, including chemical identity resolution, automated evaluations, consistency checks, provenance tracking, and targeted human review of uncertain cases.
• Scientific Data Engineering: Build and maintain reliable, tested, and scalable Python pipelines that transform heterogeneous scientific sources into high-quality datasets. Contribute to the architecture of Entalpic's scientific data platform.
• Cross-team Collaboration: Work closely with domain experts, computational chemists, materials scientists, and AI engineers to translate scientific needs into data specifications, software, and datasets that support modeling and discovery.
Your initial focus will cover advanced materials and thin-film properties (from precursor chemistry to device-relevant characteristics like electronic and optical properties) and atomic layer manufacturing processes (ALD, ALE, CVD, ASD).
Entalpic values scientific rigor, clear communication, simplicity, and a constant drive to learn and iterate. The company fosters a sustainable culture promoting work-life balance and competitive compensation. While the preference is for in-person collaboration in the Paris office, occasional remote work arrangements are available.
REQUIREMENTS:
• M.S. or Ph.D. in Chemistry, Materials Science, Chemical Engineering, or related field
• 2+ years of professional experience in software engineering, data engineering, or scientific software development
• Strong understanding of chemistry and/or materials science, with ability to reason about chemical compounds, physical properties, and experimental data
• Strong Python software engineering skills, including testing, version control, and designing maintainable systems
• Experience working with complex scientific or experimental data
• Excellent English communication skills and ability to work effectively across scientific and engineering teams
• Ability to thrive in a fast-paced, evolving startup environment
NICE TO HAVE:
• Experience with thin-film deposition processes (ALD, ALE, ASD), inorganic molecules, or device qualification metrics
• Experience with LLMs, agentic systems, or scientific information extraction
• Familiarity with cheminformatics, chemical structures and identifiers, or tools such as RDKit
