Sr Machine Learning Engineer( Austin only)

Autonomize, Inc

Austin (TX)

On-site

USD 120,000 - 150,000

Full time

14 days+

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Benefits offered by this job

100% employer-paid health, vision, and dental insurance

Retirement plans (401k)

Competitive compensation and benefits

Job summary

Autonomize, Inc, located in Austin, is seeking a Senior Machine Learning Engineer who will lead the development and deployment of machine learning solutions aimed at revolutionizing healthcare. You will fine-tune large language models, develop vision-based data approaches, and enhance classic NLP models.

The ideal candidate has 5-7 years of experience in machine learning engineering and is well-versed in technologies like TensorFlow and PyTorch. The position offers competitive compensation, 100% employer-paid health insurance, and a chance to make an impact in the future of healthcare.

Qualifications

5-7 years in machine learning engineering in healthcare.
Experience with large language models and NLP technologies.
Proven model deployment in production environments.

Responsibilities

Lead development of machine learning solutions focusing on healthcare.
Mentor junior engineers and conduct rigorous testing of models.
Ensure efficient model deployment and integration in healthcare systems.

Skills

Large language models (LLMs)

Computer Vision

Natural Language Processing (NLP)

Python

ML libraries/frameworks (TensorFlow, PyTorch)

MLOps and LLMOps

Education

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field

Tools

TensorFlow

PyTorch

OpenCV

mlflow

kubeflow

Job description

Sr Machine Learning Engineer( Austin only)

5-10

Austin

Full-Time

About Autonomize AI

Autonomize AI is revolutionizing healthcare by streamlining knowledge workflows with AI. We reduce administrative burdens and elevate outcomes, empowering professionals to focus on what truly matters — improving lives. We're growing fast and looking for bold, driven teammates to join us.

The Opportunity

As a Senior Machine Learning Engineer at Autonomize, you will lead the development and deployment of machine learning solutions with an emphasis on large language models (LLMs), vision models, and classic NLP (Natural Language Processing) models. The ideal candidate will have a proven track record in these areas, particularly within healthcare contexts, and will play a significant role in advancing our AI‑driven healthcare optimized AI Copilots and Agents.

Key Responsibilities

Help fine‑tune or prompt engineer large language models (LLMs) for various healthcare applications across various customer engagements.
Develop and refine our approach to handling vision‑based data using state‑of‑the‑art VLM based models capable of processing and analyzing medical documents, healthcare forms in various formats and other visual data accurately.
Create and enhance classic NLP models to understand and generate human language in healthcare settings, supporting clinical documentation, and patient interaction.
Collaborate with multi‑disciplinary teams including data scientists, ml engineers, healthcare clients, and product managers to deliver robust solutions.
Ensure models are efficiently deployed and integrated into healthcare systems, maintaining high performance and scalability.
Mentor and provide guidance to junior engineers and data scientists, fostering a culture of continuous learning and innovation.
Conduct rigorous testing, validation, and tuning of models to ensure accuracy, reliability, and compliance with healthcare standards.
Deep understanding of various training techniques including distributed training on GPUs and TPUs.
Stay informed on the latest research, tools, and technologies in machine learning, particularly those applicable to language and vision processing in healthcare.
Document methodologies, model architectures, and project outcomes effectively for both technical and non‑technical audiences.

Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
5-7 years of experience in machine learning engineering, with a significant track record in the developing production grade models and model pipelines in a regulated industry such as healthcare.
Hands‑on expertise in working with large language models (e.g., GPT, BERT), computer vision models, and classic NLP technologies.
Proficient in programming languages such as Python, with extensive experience in ML libraries/frameworks like TensorFlow, PyTorch, OpenCV, etc.
Strong understanding of deep learning techniques, model fine‑tuning, hyper parameter optimization, and model optimization.
Proven experience in deploying and managing ML models in production environments.
Excellent analytical skills, with a problem‑solving mindset and the ability to think strategically.
Strong communication skills for articulating complex concepts to diverse audiences.
Working knowledge or experience in MLOps and LLMOps using tools like mlflow, kubeflow.
Working knowledge of basic software engineering principles and best practices.
Demonstrated working knowledge and experience on classic ML techniques and frameworks.
Nice to have: Knowledge of Cloud vendor based ML Platforms such as Azure ML, Sagemaker.

Who you are as a person/leader

Owner mentality – For you, the buck stops at you, you own it, you will learn it, and you will get it done.
You are naturally curious. Always experimenting than hypothesizing – You like to push boundaries, you figure things out and experiment your way through any problem.
You are passionate, unafraid & loyal to the team & mission.
You love to learn & win together.
You communicate well through voice, writing, chat or video, and work well with a remote/global team.

Nice to have competencies