Machine Learning Engineer II

 

Voted Best Places to Work in Austin, Best Paying Companies, 
and Top Startup Companies by Forbes

SparkCognition looks to bring in the best talent in the world. To accommodate the hiring of our wildly talented teams, SparkCognition sponsors visa opportunities when appropriate.

Who are we and why this opportunity? 
Drive change and create a footprint. SparkCognition invests in our employees and fosters 
collaboration throughout the organization. Our employees have the ability to work globally 
with award-winning artificial intelligence (AI) technology within multiple industries. 

What are the benefits and perks at SparkCognition? 
You and your loved ones will be supported with a competitive and comprehensive benefits package.

Below are some highlights - we’d love to connect and share more! 

• Fast-paced evolving culture with the opportunity to drive new ideas and technology.
• Dynamic Work Environment - Remote and In-Office Options  
• Stock Option Grants
• Generous Time Off Programs
• Medical Coverage, and Parental Leave Plans 
• 401k with Employer Match
• Monthly Technology Allowance 
• Large 2022 renovated office space centrally located near the Arboretum in Austin, TX- including fully stocked beverage and snack areas!

Join Us In:

• Collaborating with data scientists and engineers to transform state-of-the-art ML models into production-ready solutions 
• Using best practices to validate, optimize and deploy ML models in customers’ production environments 
• Improving workflows by distilling complex ML pipelines into their underlying components with an eye towards efficiency, reusability, and repeatability 
• Independently and effectively engaging with external technical stakeholders and subject matter experts to understand and solve critical business problems through the application of cutting-edge artificial intelligence 

You'll Have: 

• Degree in Computer Science, Statistics, Physics, Mathematics, Engineering, or a related quantitative discipline 
• A thorough understanding of the data science process, including data processing and analysis; feature extraction and engineering; and model training and evaluation 
• Knowledge of standard ML approaches and algorithms, including but not limited to Linear Models, Decision Trees, Clustering, and Neural Networks 
• A strong command of Python and at least one production OOP language (C#, Java, Scala) 
• A working understanding of database fundamentals and technologies 
• Hands-on experience with common ML toolkits such as sci-kit learn and at least one deep learning framework (preferably PyTorch or Tensorflow) 
• 2+ years of experience in building and deploying machine learning models into production environments 
• Strong written and verbal communications, ability to translate complex technical topics to internal and external stakeholders
• Ability to form strong working relationships with team members, cross departmentally, customers' technical teams, and executive leadership

It would be great if you had: 

• Experience and knowledge of renewable energy technologies especially applying data analytics techniques in the domain 
• Experience with workflow management and orchestration technologies such as Kubeflow or Airflow 
• Experience with the MLOps life cycle, especially as it pertains to practical implementation within a cloud (Azure, AWS, GCP) or cloud-agnostic environment 
• Ability to be responsive with a willingness to take ownership of issues and drive solutions. 

Explore SparkCognition: 

https://www.sparkcognition.com/company/ 

BuiltIn Austin 

SparkCognition is an equal opportunity employer, dedicated to diversity, equality, and inclusion, and provides equal employment opportunities to all employees and applicants for employment.  SparkCognition prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

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