Machine Learning Engineer, IgniteTech - Washington DC, United States - Crossover

Description

Crossover is the world's #1 source of full-time remote jobs.

Are you a C# and .NET whiz with an interest in using cutting-edge technology like generative AI tools? Do you thrive on the challenge of enhancing product performance and customer satisfaction? it's a hub of innovation and growth.

it's a unique blend of maintaining and upgrading Everest software, addressing customer issues with precision, implementing customer-driven features, and optimizing databases using SQL Server.

It's an opportunity to take the lead enhancing task efficiency and product quality.

If hired, you will be a key player in ensuring the efficiency and effectiveness of Everest, working independently to solve challenging software problems.

Your proficiency in C#, .NET, JSON, and SQL Server will be crucial in maintaining software excellence. Regularly updating and optimizing Everest software to ensure peak performance and user satisfaction
Employing GenAI tools to increase the efficiency and effectiveness of tasks, including maintenance, feature implementation, and customer issue resolution
Machine Learning Engineer Key Responsibilities
~ At least 3 years of professional experience working with C# in a software development or support role
NET framework and SQL Server database management
Through our portfolio of leading enterprise software solutions, we ignite business performance for thousands of customers globally.

We're doing it in an entirely remote workplace that is focused on building teams of top talent and operating in a model that provides challenging opportunities and personal flexibility.

IgniteTech is an Affirmative Action, Equal Opportunity Employer that values the strength that diversity brings to the workplace.
This is a full-time (40 hours per week), long-term position. The position is immediately available and requires entering into an independent contractor agreement with Crossover. You will receive an email with a link to start your self-paced, online job application.

Our hiring platform will guide you through a series of online "screening" assessments to check for basic job fit, job-related skills, and finally a few real-world job-specific assignments.

Third, we will send to whatever email account you indicated on the Apply form - by default, that is the email address you use as your LinkedIn username and it might be different than the one you have already checked.

If all else fails, just reset your password by visiting if you already applied using LinkedIn EasyApply.