Machine Learning Engineer II

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SparkCognition catalyzes sustainable growth for our clients throughout the world with proven artificial intelligence (AI) systems, award-winning machine learning technology, and a multinational team of AI thought leaders. Our clients are trusted with advancing lives, infrastructure, sustainability, and financial systems across the globe. They partner with SparkCognition to understand their industry's most pressing challenges, analyze complex data, empower decision-making, and transform human and industrial productivity with scalable AI solutions to solve the problems that matter most. With our leading-edge artificial intelligence products and solutions, our clients can adapt to a rapidly changing digital landscape, accelerate their business strategies, and reduce environmental impact creating a better, smarter, and more sustainable world.
Our Services team is looking for a Machine Learning Engineer to join us in ensuring that our customers derive value from their engagement with us. As a Machine Learning Engineer, you'll bring your knowledge and proven expertise to develop, scale, and deploy AI solutions that help our customers make well-informed decisions.
If you were already working for us, you would be:

  • 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 may be a good fit for our team if you 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
  • A strong work ethic, along with the ability to prioritize and complete all job responsibilities in a timely manner
  • Ability to be responsive with a willingness to take ownership of issues and drive solutions.
  • Excellent time management and organizational skills


Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information. 41 CFR 60-1.35(c)
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Location

Large 2022 renovated office space located near the Arboretum in Austin, TX- including fully stocked beverage and snack areas, along with community spaces that include games and activities.

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