Machine Learning Engineer

• *In person required.*
• Requirements: Employer will accept a Master's degree, or foreign equivalent, in Computer
• Science or a related field.
• Machine learning and deep learning model development;
• Natural language processing and large language model applications;
• Machine learning model development and applied AI/ML engineering;
• Job Location: New York, NY.
• Email resume to [email protected] and Reference Job Code #FMLE.

About Solstice

Solstice builds AI software that helps life sciences teams create, refine, and review pharmaceutical marketing content. We have worked with leading life sciences manufacturers and more than 50 pharma brands. Our backers include Transformation Capital, Twelve Below, Virtue, and the founders of Datavant, Commure, and Paradigm.

Our customers need useful, polished content whose claims trace to approved evidence and whose output can withstand medical, legal, and regulatory review. You will work with real customer workflows and proprietary data, and see the features you build reach the people using them.

Responsibilities

• Design, develop, and optimize machine learning and generative AI systems used to evaluate pharmaceutical marketing and promotional content for scientific accuracy, evidentiary support, and regulatory compliance.
• Develop large language model applications using prompt engineering, retrieval-augmented generation (RAG), multi-agent orchestration, model experimentation, fine-tuning, and performance benchmarking to analyze clinical literature, prescribing information, regulatory guidance, and other life sciences source materials.
• Build machine learning pipelines for content classification, claim extraction, source attribution, evidence verification, and contextual compliance analysis.
• Design and deploy scalable production infrastructure supporting AI applications, including model serving, retrieval systems, data processing, evaluation frameworks, testing, monitoring, and system integrations.
• Develop and maintain evaluation systems to measure model factuality, groundedness, accuracy, reliability, and compliance-related performance. Monitor, debug, and optimize production machine learning systems for accuracy, reliability, scalability, latency, and performance.
• Collaborate with engineering, product, regulatory, and business teams to translate scientific, regulatory, and commercial requirements into production-ready AI solutions.
• Machine learning data pipeline development and processing;
• Model evaluation, experimentation, and performance benchmarking, including evaluation of factuality, groundedness, or accuracy;
• Deployment of machine learning models and systems in production environments; and

Requirements

• Any amount of experience in the additional requirements below will be acceptable unless a specific amount is noted. Prior academic background or work experience to include the following skills:
• Python and machine learning frameworks, including PyTorch or TensorFlow;
• Software debugging, testing, monitoring, and performance optimization.

Pay

Salary: $140,000 to $250,000 per year.