Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Developing and implementing cutting-edge machine learning algorithms and training sophisticated models for hirify.global products and services with an accent on designing system and model architectures and conducting rigorous experimentation. Focus on building AI functionalities, model evaluations, and guiding junior ML engineers.

Location: Remote within the United States, with office options in Seattle, San Francisco, or Mountain View. Salary ranges are specific to US geographic pay zones.

Salary: USD 119,700–USD 188,000

Company

hirify.global is a product company focused on unleashing the potential of every team through its software products for collaboration.

What you will do

• Develop and implement cutting-edge machine learning algorithms.
• Train sophisticated models for hirify.global products and services.
• Collaborate with product, engineering, and analytics teams to build AI functionalities.
• Design system and model architectures.
• Conduct rigorous experimentation and model evaluations.
• Provide guidance to junior ML engineers.

Requirements

• Bachelor's or Master's degree (preferably Computer Science or equivalent experience).
• Related industry experience in the data science domain.
• Expertise in Python or Java with the ability to write performant production-quality code.
• Familiarity with SQL, Spark, and cloud data environments (e.g. AWS, Databricks).
• Experience building and scaling machine learning models in business applications using large amounts of data.
• Ability to communicate and explain data science concepts to diverse audiences.

Nice to have

• Experience working in a consumer or B2C SaaS product provider, or the enterprise/B2B space.
• Experience in developing deep learning-based models and working on LLM-related applications.
• Excelling in solving ambiguous and complex problems.

Culture & Benefits

• Flexible work arrangements (office, home, or hybrid).
• Equitable, explainable, and competitive compensation programs.
• Eligible for benefits, bonuses, commissions, and equity.
• Health and wellbeing resources.
• Paid volunteer days.
• Commitment to diversity and inclusion.