Machine Learning Engineer

At RemoteStar, we are hiring for one of our clients - A leader in AI-driven revenue cycle management, transforming medical coding and revenue operations with cutting-edge technology. The company has raised $11 million in total funding from top investors, including Accel and Together Fund. Join us as we scale a cloud-native platform that runs transformer-based Large Language Models rigorously fine-tuned on millions of clinical notes and claims every month. You’ll engineer autonomous coding pipelines that parse ICD-10-CM, CPT® and HCPCS at lightning speed, deliver reimbursement insights with sub-second latency and >99 % accuracy, and tackle the deep-domain challenges that make clinical AI one of the hardest—and most rewarding—problems in tech. Machine Learning Engineer - Job Overview We are seeking a skilled and innovative Machine Learning Engineer with expertise in Natural Language Processing (NLP) and an interest in the latest AI models. This role focuses on driving innovation by introducing non-traditional approaches, deploying scalable models, and implementing advanced AI techniques to solve real-world challenges. The ideal candidate is a strong programmer with a research mindset and the ability to translate the latest advancements in AI into impactful solutions.

Responsibilities

Develop, deploy, and maintain ML models and pipelines for NLP tasks; Design and set up self-hosted models for specific tasks, ensuring efficiency and scalability; Establish workflows for fine-tuning, feedback loops, and online learning to enhance model performance; Implement and optimise prompt refinement techniques to improve results; Continuously research and evaluate state-of-the-art AI advancements to integrate into the organisation's solutions; Contribute to existing and new projects by streamlining processes for better estimation and scaling solutions and enhancing testing tools and pipelines for AI development; Collaborate with teams to identify opportunities for applying AI and ML to solve complex problems efficiently; Build and productionize deep learning models, ensuring seamless integration into existing systems.

Requirements

Bachelor’s degree in Computer Science, Machine Learning, or a related field; 2-4 years of experience in machine learning or applied AI roles; Strong Python skills with experience in hosting and maintaining ML models at scale; Proficiency in a deep learning framework (e.g., PyTorch or TensorFlow); Ability to explore and evaluate research papers, identifying key methods and techniques for application; Capable of combining existing tools and frameworks to create efficient and effective solutions; Solid foundation in machine learning principles and statistical techniques; Strong communication skills to convey complex ideas to technical and non-technical stakeholders.

Nice to have

Familiarity with cloud platforms, containerization tools (e.g., Docker, Kubernetes), and production-level AI workflows; Experience working with domain-specific data, such as clinical or biomedical datasets; Interest in cutting-edge AI techniques, with aspirations to co-author research or contribute to industry advancements; Knowledge of advanced NLP techniques, including prompt engineering and refinement frameworks; Exposure to signal processing applications in various domains.