AI Software Lead (consultant)

About PinkStar

PinkStar is an innovative health-tech startup developing AI-powered solutions for breast MRI. PinkStar

combines clinical expertise, advanced AI, and unique breast MRI data to support radiologists in

detecting breast cancer earlier, improving diagnostic accuracy, and reducing unnecessary procedures.

Our mission is to empower radiologists and advance personalized breast care through technology.

The Role

We are looking for a part-time AI Software Lead to own and drive our AI software development. This is a role for a builder and a leader - someone who codes, drives technical decisions, and collaborates across teams to ship AI products.

What you will own

• Define and drive the technical vision and roadmap for our AI software development.

• Design, build, and ship high-quality software that turns AI capabilities into scalable, production-

grade products.

• Own the end-to-end architecture: from data and pipelines to model deployment, serving, and

monitoring.

• Build in reproducibility and traceability: versioning of data, models, and pipeline runs, with logging

and monitoring for reliability and audit-readiness.

• Partner with data science, product, and engineering teams to integrate AI capabilities into

production, driving alignment.

• Lead collaboration with external partners and vendors-managing integrations and evaluating

third-party tools.

• Make the key architectural decisions, balancing simplicity, scalability, and reliability.

What we are looking for

• 7+ years in software engineering, with a track record of independently shipping production systems

• Demonstrated ability to lead a technical domain and drive it forward without close oversight

• Strong Python skills

• Deep experience building and operating cloud-based systems (AWS, GCP, or Azure)

• Experience deploying and operating AI/ML systems in production, including model serving and

lifecycle management.

• Experience with observability, reproducibility, and end-to-end versioning across data, models, and

pipelines.

• Experience working with external partners, vendors, or cross-company integrations

• Strong communication skills to align a small, cross-functional team

• Experience in healthcare (FDA/GxP exposure a plus).

Nice to have

• Experience working with medical imaging or other large unstructured datasets.

• Familiarity with deep learning frameworks such as PyTorch or TensorFlow.

• Experience in early-stage or high-ownership engineering teams.

• Familiarity with containerized/orchestrated systems (Docker, Kubernetes, Airflow, Dagster) and MLOps platforms (MLflow, Kubeflow, SageMaker, or Vertex AI).