About Autonomize AI

The Opportunity

Key Responsibilities

• Fine-tune or prompt engineer large language models for various healthcare applications across customer engagements.
• Develop and refine approaches for processing vision-based data using state-of-the-art VLMs for medical documents and healthcare forms.
• Create and enhance classic NLP models to support clinical documentation and patient interaction.
• Collaborate with multidisciplinary teams (data scientists, ML engineers, healthcare clients, product managers) to deliver robust solutions.
• Deploy and integrate models into healthcare systems ensuring performance and scalability.
• Mentor junior engineers and data scientists and document methodologies and outcomes.
• Conduct testing, validation, and tuning of models for accuracy, reliability, and compliance with healthcare standards.
• Apply distributed training techniques on GPUs/TPUs and stay current with relevant research and tools.

Qualifications

• Bachelor's or Master's in Computer Science, Engineering, Data Science, or related field.
• 5-7 years of machine learning engineering experience, with production-grade models and pipelines in regulated industries such as healthcare.
• Hands-on expertise with LLMs (e.g., GPT, BERT), computer vision models, and classic NLP technologies.
• Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, OpenCV.
• Strong understanding of deep learning, fine-tuning, hyperparameter optimization, and model optimization.
• Experience deploying and managing ML models in production; working knowledge of MLOps/LLMOps tools (mlflow, kubeflow).
• Strong analytical and communication skills; familiarity with software engineering best practices.

Who you are as a person/leader

Nice to have competencies

• Deploying NLP/ML at large/complex organizations.
• Scaling ML training and inference efficiently.
• Experience with Big Data technologies such as Kafka, Spark, Hadoop, Snowflake.

What We Offer