Machine Learning Engineer

Vartana is the revenue acceleration platform for top-tier enterprise technology companies. We empower sales and finance to accelerate the deal cycle without compromising cash flow through our flexible payment options and collaborative sales closing platform. Our platform is trusted by leading enterprise companies, including Motive, Domo, Samsara, and many others, as the platform of choice to make products affordable and easy to purchase for their customers. We have raised over $40M to deliver on our vision and are backed by top-tier investors, including Activant Capital, Mayfield, and Audacious Ventures. About Role: At Vartana, we're dedicated to leveraging data-driven insights to fuel our growth and drive meaningful impact. As a Machine Learning Engineer, you'll play a pivotal role in designing and maintaining our data infrastructure, ensuring the integrity and accessibility of our data for informed decision-making. Qualifications

• Minimum: Bachelor's degree in Computer Science, Computer Engineering
• The ideal candidate will have industry experience working on a range of recommendation, classification, and optimization problems
• 3+ years of experience in software engineering or a relevant field
• 2+ years of experience in one or more of the following areas: machine learning, recommendation or classification or optimization systems, pattern recognition, artificial intelligence, or a related technical field
• Experience with developing machine learning models at scale from inception to business impact
• Knowledge developing and debugging in C/C++, Go, Java, or experience with scripting languages such as Ruby on Rails, Python
• Machine Learning Framework(s): PyTorch, or Tensorflow
• Software development tools: Code editors (VIM or Emacs), and GIT- revision control systems

• Track record of setting technical direction for a team, driving consensus and successful cross-functional partnerships

• You will bring the ability to own the whole ML life cycle, define projects and drive excellence across teams
• Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules based models
• Suggest, collect and synthesize requirements and create effective feature roadmapsCode deliverables in tandem with the engineering team
• Suggest, collect, analyze and synthesize requirements and bottleneck in technology, systems, and tools