Data & Artificial Intelligence Research Engineer, L4

Citrine Informatics

. Write and maintain Python ML code .

Posted 10/3/2026full-timeRemote • United StatesSeniorLead💰 $182,000 - $210,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Python programming and machine learning model development, with a focus on materials science applications. Proven ability to mentor teams, communicate complex concepts, and deliver high-performance, scalable ML systems.

Highest-signal resume keywords

Python ProgrammingMachine Learning Model DevelopmentAI Solutions ImplementationStatistical AnalysisMaterials Science Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning AlgorithmsProduction-Quality CodeQuantitative AnalysisComputational TechniquesModel InterpretabilityUncertainty QuantificationInverse Design CapabilitiesTesting and Analysis

Soft Skills

MentoringCollaborationCommunication

Tools & Technologies

AWS ServicesSQLRelational DatabasesLLMsFoundation Models

Industry Keywords

Materials ScienceAI/MLNLPComputer Vision

Tech Stack

Tools & technologies

AWSPythonScalaSQL

About the role

Key responsibilities & impact

Write and maintain Python ML code
Research, prototype, and develop new materials-aware ML models and features
Collaborate closely with other engineers, frequently reviewing code and best practices
Mentor other developers
Design high-performance, scalable ML systems
Test and analyze the impact and performance of models
Work in a multifunctional team on features from concept to delivery
Improve and maintain core Python libraries enabling machine learning for materials science problems at industrial scale
Collaborate with the Product team to shape AI capabilities and support customer use cases
Improve machine learning model interpretability and develop user communication tools
Improve inverse design capabilities for complex materials synthesis parameter spaces
Collaborate with the External Research and Development team to write and publish papers
Develop new methods to quantify uncertainty in machine learning predictions

Requirements

What you’ll need

8+ years of professional experience or 3+ years with MS/PhD in a quantitative discipline
Proficient in a programming language such as Python or Scala
Proven history of implementing AI solutions for customers, with quantifiable results
Experience solving scientific problems with computational techniques
Ability to communicate complex technical concepts and design choices to any audience
In depth knowledge of how core ML algorithms work and their design (random forest, neural networks, etc.)
Ability to write tested, production-quality code
Legally eligible to work in the United States
Preferred: Experience with or a degree in Materials Science
Preferred: Extensive knowledge of statistics
Preferred: Experience with LLMs
Bonus: pre-trained or fine-tuned foundation models
Preferred: SQL and relational databases
Preferred: Close integration with various AWS services (S3, RDS, SQS, etc)
Preferred: Published papers establishing domain expertise in AI/ML, NLP, or CV

Benefits

Comp & perks

401k with matching up to 4%
Medical, vision, dental insurance (we pay 100% of your premium and 75% of your dependents)
Company-paid Life and Disability insurance
FSA and HSA plans
Equity options within the company
12 weeks of paid parental leave
Flexible PTO
15 paid company holidays (includes your birthday!)
Free financial counseling
$600 tech allowance
Monthly $75 phone reimbursement
$5,000 annual continuing educational allowance