About the Role

Data & AI Research Engineering (DARE) is a uniquely interdisciplinary team working at the intersection of materials science, machine learning, and software engineering. We are responsible for researching, developing, testing, implementing, and maintaining the core materials-aware machine learning functionality that powers the Citrine Platform. We collaborate extensively across the company - other teams rely on us throughout the product lifecycle to translate ideas to math to code and back again.

Example projects:

• Improve and maintain our core Python libraries that enable our users to apply machine learning to solve the world's most important materials science problems at an industrial scale
• Collaborate with our Product team to shape the future of our AI capabilities and support our customer's unique use cases
• Improve the interpretability of machine learning models and develop tools to communicate that information to users
• Improve our inverse design capabilities that efficiently explore complex parameter spaces that characterize real-world materials synthesis problems
• Collaborate with our External Research and Development (ERD) team to write and publish papers related to the work we're doing
• Develop new methods to quantify uncertainty in machine learning predictions

Responsibilities

• Writing and maintaining Python ML code
• Researching, prototyping, and developing new materials-aware ML models and features
• Collaborating closely with other engineers, frequently reviewing code and best practices
• Mentoring other developers
• Designing high-performance, scalable ML systems
• Testing & analyzing the impact and performance of models
• Working in a multi-functional team on features from concept to delivery

Skills and Experience

• 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 Skills and Experience

• Experience with or a degree in Materials Science
• Extensive knowledge of statistics
• Experience with LLMs
• • Bonus points if you've pre-trained or fine-tuned foundation models!
• SQL and relational databases
• Close integration with various AWS services (S3, RDS, SQS, etc)
• Published papers that establish you as a domain expert in AI/ML, NLP, or CV

Compensation and Pay Transparency

At Citrine, we want your path to career growth to be transparent, straightforward, fair, and easily accessible - starting with your application and interview process. The annual salary range listed below reflects the level we are considering for this position (please note that there may be unique situations where you may fall outside of this range). Where you fall within the range will depend on how your experience and skills align with our internal leveling system as we learn more about you throughout the interview process.

$182,000 USD - $210,000 USD

*Range(s) listed are for full-time employees based in the United States only.

Our Benefits(for exempt, full-time employees based within the United States)

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 on top of our 15 paid company holidays (includes your birthday!)

Free financial counseling

$600 tech allowance

Monthly $75 phone reimbursement

$5,000 annual continuing educational allowance