Description

The Experience Center is transforming Humana into a human-centered, tech-driven company. We are accomplishing this by developing experience-first healthcare software rapidly, flexibly and iteratively. We are a technology incubator for the company and are expanding our capabilities by integrating Data Engineering and Data Science into the balanced team model. The Senior AI/ML Engineer will work alongside data scientists, software developers, designers, and product managers to identify, validate, and adopt new technologies, tools, and practices, and turn these into human-centered experiences for Humana members.

AI/Machine Learning Engineer will contribute to the development of our data preprocessing and modeling capabilities to drive intelligent applications and products in the healthcare industry as part of Humana’s Boston Experience Center. They will work collaboratively within a product team to automate the machine learning process in a big data cloud environment (e.g. GCP, Azure, etc.). They will be an integral part of a team that will design and build ML models and integrate them with other applications and services.

Responsibilities

The AI/Machine Learning Engineer at the Experience Center has a strong intuitive grasp of Artificial Intelligence (AI) and Machine Learning (ML) as well as core engineering skills (e.g. OOP, database schema design, understanding of S.O.L.I.D. principles, etc.). The AI/Machine Learning Engineer pushes forward the strategic development of applications for machine learning and do what it takes to make them successful. In addition the AI/ML Engineer will:

• Work collaboratively within a cross-functional balanced team to deliver solutions that meets our business needs.
• Work to continuously improve our service delivery and capabilities to deliver impactful experiences in the products we deliver to market.
• Act as an external facing business translator whose combined expertise in AI/ML and analytics will enable the incorporation of these practices to drive data driven decision in practice.
• Work on products that are developed in an extreme programming environment. Which means:
  • Code and pipelines should adhere to Test-Driven Development (TDD)
  • Engineers typically work in a paired programming environment.
  • Work fixed office hours from 8am – 5pm in order to optimize our
• Have the ability to travel as-needed to meet with team members (typically less than 5% travel).

Required Qualifications:

• Bachelor's Degree in Computer Science or related field
• 5 or more years of experience designing, developing, and testing of software applications and/or infrastructure

• 3 or more years of machine learning engineering experience
• Experience writing maintainable, testable, production-grade Python code
• Experience working with big data platforms (e.g. Hadoop, Hive, Impala, Spark)
• Experience working with big data file formats (e.g. Parquet, Avro)
• Proficient in SQL and creating ETL processes (any of MSSQL, MySQL, PostgreSQL)
• Understanding of different machine learning algorithm families and their tradeoffs (linear, tree-based, kernel-based, neural networks, unsupervised algorithms, etc.)
• Experience working in Azure cloud learning environment, including deployment of models to production.
• Experience with Agile, Continuous Integration, Continuous Deployment, TDD, Git
• Good command of scientific Python toolkit (numpy, scipy, pandas, scikit-learn)
• Understanding of time, RAM, and I/O scalability aspects of data science applications (e.g. CPU and GPU acceleration, operations on sparse arrays, model serialization and caching)
• Comfortable with Linux-based operating systems Desired Skills
• Ability to work in a collaborative environment:
  • AI/ML Engineers will be members of and work on a Balanced Team (including Product Managers, Designers, Software Engineers, and Data Scientists).
  • Products are developed in an extreme programming environment.
  • Code and pipelines should adhere to Test-Driven Development (TDD)
  • Engineers typically work in a paired programming environment.
  • Ability to travel as-needed to meet with team members (typically less than 5% travel).

Preferred Qualifications:

• Knowledgeable with deployments to Azure infrastructure using terraform
• Experience with large-scale machine learning (100GB+ datasets)
• Experience with deep learning libraries and frameworks (TensorFlow, Keras, PyTorch etc.)
• Master's Degree

Additional Information:

• This role will be located at Humana's Studio H office working Monday - Friday 8am-5pm.