Machine Learning Engineer II

Indeed•Remote,

4d•$138,000 - $289,000

About The Position

As a Senior Machine Learning Engineer, you will work on developing, deploying predictive models and genAI capabilities that support various business functions. Your daily activities include exploring data to define problem statements, building and optimizing machine learning models, and monitoring their performance in production environments. You will collaborate with cross-functional teams to integrate machine learning solutions into products and stay informed about the latest advancements in the field to continuously improve model effectiveness and innovation.

Requirements

Requires a Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 5 years of related experience; or a Master’s degree with a minimum of 3 years of experience; or a PhD without experience
Prior success in deploying impactful Machine Learning solutions to large-scale production systems
Solid knowledge of data structures and algorithms
Exceptional sense of ownership
Excellent written and verbal communication in English, effective with technical audiences
Knowledge and practical experience working on Deep Learning Libraries (like Torch, Tensorflow, etc.)

Responsibilities

Build highly scalable and performant recommendation systems and technologies that can identify optimum matches between millions of jobs and millions of job seekers in real-time.
Experiment with Proof-Of-Concept Machine Learning (POC ML) model improvements, scale them to production, and run iterative A/B experiments to improve our matching technology.
Mentor other software engineers, data scientists, and Machine Learning Engineers in the team.
Break down larger Machine Learning initiatives into pieces that deliver incremental business value and implement them.
Represent Indeed at major Machine Learning conferences like Neural Information Processing Systems (NeurIPS), International Conference on Machine Learning (ICML), and International Conference on Learning Representations (ICLR).