Machine Learning Engineer

Extra Space Storage•Salt Lake, UT

3d•Hybrid

About The Position

Responsible to build and deploy advanced analytics systems into production. Responsible for maintaining the environments and software for ongoing maintenance of these systems. Familiar with database structures, statistical modelling, software engineering best practices, and the latest developments in generative AI.

Requirements

A Master’s Degree in computer science, data science, mathematics, statistics, finance, economics, or other engineering
Requires 3+ years' experience in deploying advanced analytics solutions to drive business outcomes.
Proven analytical skills with data driven decision-making skills.
Ability to manage large data sets, develop data pipelines.
SQL programming skills.
Python or R programming skills.
Knowledge of vector databases, embedding models, LLM endpoints.
Team player with excellent collaboration skills.
Highly motivated and high level of energy and enthusiasm.

Nice To Haves

Prior experience with cloud technologies will be a plus.

Responsibilities

Builds and deploys scalable analytical systems.
Develops data science proof-of-concept models into production-ready applications.
Follows industry standard principles on software development.
Builds data science applications related to text-based search, and audio & video recordings.
Uses statistical modeling or A/B testing approaches to evaluate algorithmic improvements to model.
Executes on technical roadmap for data science products.
Performs systems analysis, interprets the findings from it and explains the finding to business audience to improve products such as revenue management system, and paid search bidding system.
Documents assigned aspects of projects including business objectives, data gathering and processing, leading approaches, final algorithm, detailed set of results and analytical metrics.
Develop and optimize prompts for large language models (LLMs), evaluate and fine-tune AI models to achieve desired outcomes for specific business applications.
Collaborate with various teams to integrate and test data science and AI applications.