Autonomize AI is seeking a highly motivated Senior ML Engineer to join our team on a journey to help healthcare organizations unlock dark data.

Autonomize is on a mission to help organizations make sense of the world's data. We help healthcare organizations harness the full potential of data to impact human health outcomes. Unstructured dark data contains nuggets of information that when paired with human context will unlock some of the most impactful insights for most organizations, and it’s our goal to make that process effortless and accessible.

We are an ambitious team committed to human-machine collaboration. Our founders are serial entrepreneurs passionate about data and AI and have started and scaled several companies to successful exits. We are a global, remote company with expertise in building amazing data products, captivating human experiences, disrupting industries, being ridiculously funny, and of course scaling AI.

About the role:

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

1. Help fine-tune or prompt engineer large language models (LLMs) for various healthcare applications across various customer engagements.
2. 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.
3. Create and enhance classic NLP models to understand and generate human language in healthcare settings, supporting clinical documentation, and patient interaction.
4. Collaborate with multi-disciplinary teams including data scientists,ml engineers, healthcare clients, and product managers to deliver robust solutions.
5. Ensure models are efficiently deployed and integrated into healthcare systems, maintaining high performance and scalability.
6. Mentor and provide guidance to junior engineers and data scientists, fostering a culture of continuous learning and innovation.
7. Conduct rigorous testing, validation, and tuning of models to ensure accuracy, reliability, and compliance with healthcare standards.
8. Deep understanding of various training techniques including distributed training on GPUs and TPUs.
9. Stay informed on the latest research, tools, and technologies in machine learning, particularly those applicable to language and vision processing in healthcare.
10. Document methodologies, model architectures, and project outcomes effectively for both technical and non-technical audiences.

Qualifications:

1. Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
2. 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.
3. Hands-on expertise in working with large language models (e.g., GPT, BERT), computer vision models, and classic NLP technologies.
4. Proficient in programming languages such as Python, with extensive experience in ML libraries/frameworks like TensorFlow, PyTorch, OpenCV, etc.
5. Strong understanding of deep learning techniques, model fine-tuning, hyper parameter optimization, and model optimization
6. Proven experience in deploying and managing ML models in production environments.
7. Excellent analytical skills, with a problem-solving mindset and the ability to think strategically.
8. Strong communication skills for articulating complex concepts to diverse audiences.
9. Working knowledge or experience in MLOps and LLMOps using tools like mlflow, kubeflow
10. Working knowledge of basic software engineering principles and best practices
11. Demonstrated working knowledge and experience on classic ML techniques and frameworks.
12. Nice to have : Knowledge of Cloud vendor based ML Platforms such as Azure ML, Sagemaker

Who you are as a person/leader:

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

Nice to have competencies

1. Large/Complex organization experience in deploying NLP/ML in production
2. Experience in efficiently scaling ML model training and inferencing
3. Experience with Big Data technologies using Kafka, Spark, Hadoop, Snowflake

Some perks of working with us:

*Outsized Bet: We are a young company, funded by early customer traction, and leading VCs, and provides you an opportunity to start at the ground floor. A few years may turn into a plush retirement fund.

1. Learning - Constantly learn from founders, community and customers
2. Startup Perks - Ownership, Autonomy &Mastery
3. Standard Benefits - insurance, commute etc.
4. You get to change the way the world, and leave a lasting impact.

We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability, or other legally protected statuses.