Machine Learning Engineer

Company: SpineZone
Location: San Diego, California, United States
Type: Full-time
Posted: 29.MAY.2021
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Company Description Musculoskeletal (MSK) problems are the costliest medical category today, accounting for $432 billion cost alone in the ...


Company Description

Musculoskeletal (MSK) problems are the costliest medical category today, accounting for $432 billion cost alone in the US, four times the cost of diabetes and Heart disease. One key reason for this high cost has been the current "fee-for service" care model in the US where patients are treated in an uncoordinated manner throughout their care pathway. The mission of SpineZone is to reduce both the unnecessary suffering of these MSK patients and the total cost of care through an integrated holistic program that includes not only physical therapy but also education, diet and behavioral programs. The company was started by a group of spinal surgeons whose philosophy is to acknowledge the latent potentials of both mind and the body to heal and correct itself, and only intervening with costly injections and surgery when all other non-invasive interventions have not alleviated the suffering. The company has been operating several physical therapy clinics in California as well as an online, and has accumulated a trove of structured and unstructured data covering several years of patient features, interventions and outcomes. The company is also contributing to medical research through publications in leading journals and conferences in MSK.

We are now looking to expand the ML team whose mission is to develop, implement and deploy models and contribute to the ongoing scientific research efforts.

Job Description

You will be an early member of the ML team, with a unique opportunity to work on high dimensional data in the MSK domain. No other institution knows as many features about a MSK patient than SpineZone. You can shape and lead directions of the team and work closely with various teams, including:

  • Clinical team (spine surgeons, physical therapists, spine research professors): to understand nuances of the data and the domain, define new clinical questions and research directions as well as validate model development and predictions.
  • Product team: to understand customer (therapists, insurance clients, PCPs, ..) needs and opportunities
  • ML team: to support complementary efforts and help refine the end-to-end MLOps architecture and technologies, from labeling platforms, high dimensional ETLs to model serving and distribution shift detection and retraining pipelines.

We are looking for applied ML researchers in mid to senior stages of their career to join us in this exciting journey to reduce the unnecessary suffering of patients. The position can be remote or in San Diego, CA. In particular, we are looking for individuals who have the following characteristics:

  • Have at least a masters or preferably a doctoral degree in AI/ML, biostatistics, epidemiology, with publications in respectable venues (e.g. NeurIPs, ICML, ICRL, CVPR, ACL, etc.)
  • Has an understanding of basic statistical methodology and experimental design principles.
  • Has deep experience in at least one of:
    • CV
    • NLP
    • RL
    • Causal modeling (contextual bandits, batch off-policy evaluation, sequential decision making, TMLE, etc.)
  • Excellent data and programming skills including:
    • languages: python3, Julia, C++
    • Database: postgres, sql
    • Big Data: Spark, Big Table, Athena
    • Cloud: AWS / GCP
    • Versioning: git
    • ML: Pytorch / TF, Pandas/Dask, Scikit-learn,
    • MLOps (optional): Sagemaker, MLFlow
Soft Skills
  • Can interact with non-ML experts (clinical researchers, therapists, surgeons, etc.) and explain complex concepts in a clear and concise manner.
  • Prefers to work in a collaborative rather than isolated mode
  • Evidence based approach for modeling and evaluation. Be able to nimbly adjust to study findings and change direction.
  • (optional) Able to grow the team.
SpineZone is an Equal Opportunity Employer: we value diversity. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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