Machine Learning Engineer

Company: HackerRank

Website: Visit Website

Business Type: Startup

Company Type: Product

Business Model: B2B

Funding Stage: Series D+

Industry: HR Tech

Job Description

At HackerRank, we are on a mission to change the world to value skills over pedigree. We are a high-performing, mission-driven team that truly, madly, deeply cares about what we do. We don’t see velocity and quality as tradeoffs - both matter. If you take pride in high-impact work and thrive in a driven team, HackerRank is where you belong.

As a Senior ML Scientist at HackerRank, you will be working closely with Engineering & Product teams to design, implement, and deliver machine learning and AI solutions. You will be a key part of developing HackerRank's Machine Learning practice across our products, with a heavy emphasis on technical & thought leadership for machine learning and AI solutions.

We Are Looking For

• 5+ years of experience working on data science and machine learning applications, including 5+ years on model development
• A strong background in math & statistics for machine learning applications
• Prior experience in technical directing and mentoring junior team members to deliver large efforts
• Solid ability to understand business priorities and set a vision to realize them
• Being up to date on recent advances in machine learning, and identifying relevant papers and opportunities
• Ability to design
  
  

You Will Be Working On

• Design and Develop Advanced ML Solutions: Conceive research ideas, build end-to-end models, and refine algorithms for complex business challenges.
• Technical Leadership and Mentorship: Guide teams on best practices, review and optimize machine learning assets such as datasets, models, and code, and foster continuous learning.
• Cross-functional collaboration: Work with engineers, product managers, and stakeholders to align ML initiatives with broader organizational goals and ensure seamless deployment.
• Strategic Planning and Thought Leadership: Shape the ML roadmap, ensure model fairness and compliance, and represent the organization at industry events.