Remote Senior Materials AI Research Engineer

Jobgether SRL; United States; Remote; USD 182,000 - 210,000; Full time

Benefits offered by this job

401(k) retirement plan

Medical, vision, dental insurance

Equity options

12 weeks paid parental leave

Flexible PTO + 15 holidays

Job summary

Jobgether SRL is seeking a Data & AI Research Engineer based in the United States. You will work at the intersection of materials science, machine learning, and software engineering to research, develop, and maintain materials-aware AI capabilities.

You will contribute to ML systems including interpretability, uncertainty quantification, and inverse design, collaborating with product and research teams to deliver customer-ready AI capabilities.

Qualifications

• 8+ years of relevant professional experience, or 3+ years with a master's/PhD.
• Proven experience delivering AI/ML solutions to customers.
• Experience applying computational techniques to solve scientific problems.
• Strong understanding of core ML algorithms and scalable system design.

Responsibilities

• Write, test, and maintain production-quality Python ML code and libraries.
• Prototype and develop new materials-aware ML models and features.
• Design scalable ML systems for industrial-scale scientific applications.
• Evaluate model performance and continuously improve effectiveness.
• Collaborate with product, engineering, and research teams to translate customer needs into AI capabilities.
• Mentor developers and contribute to knowledge sharing.

Skills

Python

Scala

Production-grade software

ML research

Model evaluation

Communication

Autonomy

Education

Master's or PhD in quantitative discipline

Tools

AWS (S3/RDS/SQS)

Job description

Jobgether SRL is seeking a Data & AI Research Engineer based in the United States. You will work at the intersection of materials science, machine learning, and software engineering to research, develop, and maintain materials-aware AI capabilities.

You will contribute to ML systems including interpretability, uncertainty quantification, and inverse design, collaborating with product and research teams to deliver customer-ready AI capabilities.