Machine Learning Engineer

Machine Learning Engineer
Take the opportunity to work with highly professional people with remarkable ideas on their minds!
Newfire Global Partners is a rapidly growing, privately-held, American company that provides advisory and technology services to some of the world’s most innovative companies. In 2022, Inc. Magazine recognized Newfire as one of the fastest-growing companies in America. Headquartered in Boston with operations spanning four continents (including teams in Argentina, Brazil, Canada, Costa Rica, Columbia, Croatia, Malaysia, Mexico, Ukraine, United States, and others), our global staff of nearly 1,000 professionals represents top talent worldwide in the areas of software development, product management, data science & data engineering, and CEO & board advisory services.
Our core values are demonstrated by a commitment to continuous improvement, open communication & trust, and respect for the individual.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• Proven experience in machine learning, specifically with RAG and LLMs
• Strong programming skills in Python
• Experience in API development and integration
• Proficiency in SQL and cloud-based data management solutions
• Knowledge of tools such as Guardrails, Lakera, and other relevant libraries
• Excellent problem-solving skills and the ability to work in a fast-paced environment
• Strong communication and teamwork abilities

Nice-to-Have:

• Programming skills in JavaScript
• Experience with AWS Healthlake

• Machine Learning & Model Development:

• Implement large language models with a focus on Retrieval Augmented Generation (RAG).
• Fine-tune and optimize models to enhance performance and accuracy
• Conduct prompt engineering to improve model outputs and user interaction
• Deploy and maintain vector database infrastructure for hosting large document chunks

• Software Development & API Integration:

• Design, develop, and maintain APIs for seamless integration of machine learning models into applications
• Collaborate with frontend and backend developers to ensure smooth implementation of features
• UClize JavaScript and other programming languages to build robust and scalable applications

• Database and Data Engineering:

• Deploy scalable, secure infrastructure for our RAG pipeline on AWS
• Manage and preprocess large documents for model fine-tuning and evaluation
• Use SQL for data manipulation, extraction, and analysis
• Work with AWS Healthlake and other cloud-based data storage solutions to efficiently manage healthcare data

• Tool Utilization & Collaboration:
  • Utilize a variety of tools such as Guardrails, Lakera, and other Python-based libraries to enhance model development and deployment
  • Collaborate with cross-functional teams to identify and address technical challenges
  • Stay updated with the latest advancements in machine learning and healthcare technology