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.

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.

Key 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.
● 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.

Preferred Qualifications:
● 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.