Sr. Applied AI/ML Engineer

Vi; United States; Hybrid; USD 130,000 - 190,000; Full time

Job summary

Vi is seeking an engineer with deep expertise in building and scaling big-data and ML pipelines. The role will be a hybrid between an integration engineer owning customer data integrations with Vi’s data lakehouse and a platform engineer packaging Vi’s products into repeatable, scalable, automated pipelines.

You will work with Apache Spark, PySpark, Python and AWS technologies to design and implement data and ML workflows and to prototype predictive insight products.

Qualifications

• Experience building large-scale data analytics pipelines with Spark.
• Strong Python and AWS data/ML tooling experience.
• Excellent communication across customer accounts and technical counterparts.

Responsibilities

• Own the design and implementation of data and ML pipelines based on first-party customer data and Vi’s data lakehouse.
• Prototype predictive insight products and run rapid feasibility studies for new commercial opportunities.
• Identify commonalities between customer engagements to synthesize reusable data capabilities.

Skills

Big-data pipelines

Python & AWS for data/ML

Communication across accounts

Tools

Apache Spark

Apache Iceberg

AWS EMR

Glue

S3

Python

PyTorch

sklearn

xgboost

catboost

mlflow

SageMaker

Airflow

Job description

Vi manages a petabyte scale data lakehouse that drives data and ML pipelines across all our products. Vi is looking for an engineer with deep expertise building and scaling big-data and ML pipelines. The role will be a hybrid between an FDE that owns integrations of customer data with Vi’s data lakehouse and a platform engineer responsible for packaging Vi’s products into repeatable, scalable, automated pipelines.

Tech Stack

• Apache PySpark, Apache Iceberg, AWS EMR, Glue, S3
• Python, PyTorch, sklearn, xgboost, catboost, mlflow
• AWS SageMaker, Airflow

Key Responsibilities

• Own the design and implementation of data and ML pipelines based on a combination of customer first party data and Vi’s internal data lakehouse.
• Prototype predictive insight products and run rapid feasibility studies to assess new commercial opportunities for Vi’s capabilities built on petabyte scale data lakehouse.
• Identify commonalities between customer engagements to synthesize reusable data capabilities.

What We’re Looking For

• Deep expertise building large-scale data analytics pipelines with Apache Spark.
• Comfortable using Python and AWS technologies for data engineering and ML.
• Strong communication skills to interact with technical counterparts across customer accounts to coordinate data integrations.

Nice to Have

• Experience in the healthcare and life sciences domain.
• Familiarity with ML and statistical modeling methodologies and experimental design.