AI Software Engineer

OneOncology•Nashville, TN

About The Position

OneOncology is positioning community oncologists to drive the future of cancer care through a patient-centric, physician-driven, and technology-powered model to help improve the lives of everyone living with cancer. Our team is bringing together leaders to the market place to help drive OneOncology’s mission and vision. Why join us? This is an exciting time to join OneOncology. Our values-driven culture reflects our startup enthusiasm supported by industry leaders in oncology, technology, and finance. We are looking for talented and highly-motivated individuals who demonstrate a natural desire to improve and build new processes that support the meaningful work of community oncologists and the patients they serve. Job Description: We are seeking a highly motivated and skilled AI Software Engineer to join our dynamic team. You will be instrumental in designing, developing, and deploying cutting-edge AI solutions, with a focus on building agentic AI systems, implementing Retrieval Augmented Generation (RAG) architectures, and training sophisticated models. This role requires a strong understanding of machine learning principles, practical experience with cloud platforms (Azure and Databricks), and a passion for pushing the boundaries of AI technology.

Requirements

Bachelor's or Master's degree in Computer Science , Artificial Intelligence, or a related field.
3+ years professional software development experience
Proven experience in developing and deploying machine learning models.
Experience with large language models (LLMs) and transformer architectures.
Proficiency in Python and other relevant programming languages .
Experience with cloud platforms, specifically Azure and Databricks.
Excellent problem-solving and analytical skills.
Strong communication and collaboration skills .
Experience with Vector Databases is a strong plus.
Experience with orchestration tools like Langchain or similar is a strong plus.

Nice To Haves

Experience with : A gentic AI development.
RAG implementation.
P roductionizing machine learning models.
MLOps practices .

Responsibilities

Design and implement intelligent agents capable of autonomous decision-making and task execution.
Develop and integrate planning, reasoning, and memory modules within agentic systems.
Evaluate and optimize agent performance in complex, dynamic environments.
Architect and implement RAG pipelines to enhance large language model (LLM) performance by incorporating external knowledge.
Develop efficient indexing and retrieval mechanisms for diverse data sources.
Fine- tune LLMs for optimal performance within RAG frameworks.
Train and fine-tune large language models and other deep learning models using Azure Machine Learning and Databricks.
Develop and implement data preprocessing pipelines for model training.
Optimize model performance through hyperparameter tuning and architecture adjustments.
Evaluate and deploy models into production environments.
Utilize Azure services (e.g., Azure Machine Learning, Azure Cognitive Services, Azure Databricks) for model development, training, and deployment.
Develop and maintain scalable and efficient data pipelines within Databricks.
Manage and optimize cloud resources for cost-effectiveness.
Collaborate with data team, software engineers, and product managers to deliver end-to-end AI solutions.
Communicate technical concepts and results effectively to both technical and non-technical audiences.
Contribute to the development of best practices and standards for AI development.
Continuously research and evaluate new AI techniques and technologies.
Participate in industry conferences and workshops to stay abreast of the latest developments.
Other duties as assigned to help drive our mission of improving the lives of everyone living with cancer.