Senior Machine Learning Engineer (NLP)

About the Role:
We are seeking an experienced Senior Machine Learning Engineer with expertise in Natural Language Processing (NLP) and healthcare data to join our AI/Data Science team. This role is crucial in advancing our efforts to enhance Clinical Decision Support (CDS) and optimize lab testing through innovative Machine Learning (ML) and Artificial Intelligence (AI) technologies.

The ideal candidate will have a robust background in ML, NLP, and AI, with extensive experience in handling complex medical datasets, including electronic health records (EHRs) and medical ontologies. The selected candidate will drive the development of NLP technology and the associated tech stack, ensuring alignment with our healthcare objectives. Additionally, the candidate should have strong experience with MLOps/DevOps practices, as they will serve as the primary contact for these topics within the team, supporting the infrastructure team to ensure seamless deployment and operationalization of ML models. The selected candidate will establish and manage collaborations with external service providers, such as LLM inference endpoints, to enhance our capabilities. They will also collaborate with colleagues on topics related to medical knowledge graphs and patient data.

This is a hands-on, developer-facing role, requiring extensive software engineering skills in Python to develop and deploy production-quality code in a collaborative environment.

Key Responsibilities:

• Lead the development and enhancement of NLP technologies and the tech stack, ensuring alignment with healthcare and AI/ML objectives.
• Analyze and interpret complex medical datasets, including structured and unstructured data from scientific publications, EHRs, and medical ontologies, to extract meaningful insights.
• Establish and manage collaborations with external service providers, such as LLM inference endpoints, to enhance our technological capabilities and service offerings.
• Collaborate with team colleagues on topics related to medical knowledge graphs and patient data, ensuring a cohesive approach to integrating various data sources and technologies.
• Develop high-quality, maintainable Python code, adhering to software engineering best practices.
• Act as the primary liaison for MLOps/DevOps, collaborating with the infrastructure team to ensure smooth deployment, scaling, and monitoring of ML models.
• Collaborate with cross-functional teams, including product managers, data engineers, and healthcare professionals, to apply advanced data science techniques in clinical settings.
• Implement robust monitoring, logging, and alerting solutions to ensure the reliability, scalability, and availability of data processing and ML services.
• Stay updated with the latest advancements in NLP, Large Language Models (LLMs), medical data science, and ML, and integrate these into the company’s technology stack and practices.

Required Qualifications:

• Advanced degree (Master's or Ph.D.) in Data Science, Computer Science, Statistics, or a related field.
• Minimum of 5 years of experience in Data Science, Machine Learning, or Artificial Intelligence, with a significant focus on NLP and text analytics.
• Proven experience in driving the development of NLP technologies and managing the associated tech stack in a professional setting.
• Extensive software engineering skills, particularly in Python, with a track record of developing and deploying production-quality code.
• Proficiency in Python, SQL, and NoSQL databases, with hands-on experience in cloud platforms such as AWS, GCP, or Azure.
• Demonstrated expertise in developing ML models for predictive analytics, particularly in the healthcare domain.
• Experience with MLOps/DevOps practices, including the deployment and operationalization of ML models, CI/CD pipelines, and infrastructure collaboration.
• Experience with Large Language Models (LLMs), including prompting and quantization techniques.
• Strong collaborative skills with a proven ability to work effectively in cross-functional teams, including product managers, infrastructure teams, and stakeholders.
• Experience in implementing monitoring, logging, and alerting solutions to ensure the reliability and availability of data processing and ML services.
• Excellent problem-solving abilities and a proactive approach to addressing complex challenges.
• English fluency required (B1 or above).
• Willingness to work within Central European Time (CET) business hours.

Preferred Qualifications:

• Experience in the healthcare industry, particularly within the U.S. market.
• Familiarity with healthcare standards and protocols (e.g., HL7, FHIR).
• Strong background in ML, NLP, and text analytics, with a focus on medical datasets, ontologies, and EHRs.
• Experience with big data technologies and cloud computing platforms.
• Experience with data curation and annotation processes, particularly in the context of healthcare datasets.