Machine Learning Engineer

remotestar-team; Bengaluru; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

RemoteStar is hiring a Machine Learning Engineer (NLP) in Bengaluru to drive AI-powered coding and clinical data solutions. You will develop, deploy, and scale ML models and pipelines for NLP tasks, experiment with self-hosted models, and refine prompts for better results.

The role emphasizes research-minded programming, collaboration across teams, and translating the latest AI advances into practical solutions for real-world problems.

Qualifications

• Experience in ML or applied AI roles (2–4 years).
• Strong Python skills with hosting and maintaining ML models at scale.
• Proficiency with deep learning frameworks (PyTorch or TensorFlow).
• Ability to review research papers and identify applicable methods.

Responsibilities

• Develop, deploy, and maintain ML models and pipelines for NLP tasks.
• Design self-hosted models for scalable tasks.
• Set up workflows for fine-tuning, feedback loops, and online learning.
• Implement prompt refinement techniques to improve results.
• Research and evaluate state-of-the-art AI advancements to integrate into solutions.
• Collaborate with teams to apply AI/ML to complex problems.
• Build production-ready DL models and integrate with existing systems.

Skills

NLP

Python programming

ML fundamentals

Communication skills

Education

Bachelor’s degree in Computer Science or related field

Tools

PyTorch

TensorFlow

Docker

Kubernetes

Job description

Location: Bengaluru (Onsite)

Years of Experience - 2 to 4

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.

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.