Sr Machine Learning Engineer( Austin only)

Autonomize Inc
Austin, TX, United States
about 2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Computer Vision Big Data Cloud Computing Apache Hadoop Python (Programming Language) Machine Learning Natural Language Processing OpenCV Tensorflow Azure Machine Learning Software Engineering
+13 more
Graphics Processing Unit (GPU) Pytorch Large Language Models Snowflake Apache Spark Deep Learning Scikit Learn Kubernetes Information Technology Apache Kafka Machine Learning Operations GPT Programming Languages

Job description

  • 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.

Requirements

Do you have experience in Software engineering?, 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., * 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 Large/Complex organization experience in deploying NLP/ML in production Experience in efficiently scaling ML model training and inferencing

  • Experience with Big Data technologies using Kafka, Spark, Hadoop, Snowflake

Benefits & conditions

Pulled from the full job description

  • 401(k)
  • Vision insurance
  • Dental insurance
  • Employee assistance program
  • Disability insurance, * Competitive compensation and benefits

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

About the company

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.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on indeed.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:08 min

Essential engineering roles in the generative AI space

Mary Grygleski Mary Grygleski · LIVE

2:35 min

Preventing remote code execution in PyTorch models

Balázs Kiss · World Congress 2023

4:53 min

Achieving real-time tracking performance with OpenCV and segmentation

Thomas Endres Thomas Endres +2 · World Congress 2021

40 sec

Generative pre-trained transformer models powering code completions

lgonta lgonta +1 · World Congress 2024

5:01 min

Leveraging large language models for code optimization and development

Stephan Gillich Stephan Gillich +3 · World Congress 2024

1:06 min

Compiling PyTorch environments for advanced time forecasting

Christoph Lohrmann Christoph Lohrmann +1 · World Congress 2026 Europe

Videos

See all

Related articles

See all