Staff Machine Learning Engineer (Ai Engineering)

TL;DR

Staff Machine Learning Engineer (AI Engineering): Designing, implementing, and improving machine learning systems to reconstruct customer engagement workflows and developing metrics to measure their success. Focus on developing and deploying GenAI based applications, building microservices, and navigating both AI engineering sides with little help from others.

Location: Remote

Company

hirify.global is the only complete AI Revenue Workflow Platform that helps sales leaders benefit from connected account visibility, performance insights, and higher forecasting accuracy across every GTM team.

What you will do

• Design, implement, and improve machine learning systems.
• Contribute to machine learning applications end to end, i.e. from research to prototype to production.
• Work with product managers, designers, and customers to define vision and strategy for a given product.

Requirements

• You have degree in Computer Science, Data Science, or a related field, and 7-10 years of industry or equivalent experience.
• You understand the typical lifecycle of machine learning product development, from inception to production.
• You have strong programming skills in at least one object-oriented programming language (Java, Scala, C++, Python, Golang, etc.)
• You have substantial experience with building and managing infrastructure for deploying and running ML models in production
• You have experience working with distributed data processing frameworks such as Spark.

Nice to have

• Experience with LangChain, LangGraph is a plus
• Experience building microservices. Experience with Golang is a plus
• Experience with Spark's MLlib, AWS, Databricks, MLFlow are a plus.

Culture & Benefits

• Our success is reliant on building teams that include people from different backgrounds and experiences who can elevate assumptions and ideas with fresh perspectives.
• We're dedicated to hiring the whole human, not just a resume.
• We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses.