Machine Learning Engineer - Seattle, WA, United States - Keystone

Description

Keystone is a premier consulting firm that combines economics, technology, and strategy to solve complex challenges facing global brands.

We impact society on a global scale by working at the forefront of influential technology cases changing consumer behavior and regulation laws.

Keystone brings an interdisciplinary approach, leveraging the intersection of economics, software and technology, and business strategy to deliver transformative ideas.

As Staff ML Engineer, you will leverage your deep understanding of machine learning, software engineering, and problem solving to build scalable, robust solutions for clients.

You'll spearhead the entire development process, working with our econometricians and engineering teams to scope solutions, train models, deploy into production environments, and set up monitors, alerts and diagnosis tools to support the ML model operations.

We are a consultancy where traditional reporting lines are not clearly demarcated.

Because we operate like a startup the most successful candidates will have a broad range of production software development skills, flexibility to wear many hats, and an enthusiasm to learn and teach along the way.

In your role as a Machine Learning Engineer, you will be instrumental in developing and deploying cutting-edge machine learning models and software applications to deliver these models.

Collaborating with cross-functional teams to identify business challenges and opportunities for applying machine learning techniques.

Designing, implementing, and testing machine learning models to extract valuable insights from large and complex datasetsConducting thorough data analysis and pre-processing to ensure high-quality input for the modelsIntegrating machine learning solutions into existing systems and processes and scaling them for real-world applicationsContributing to the development of proprietary machine learning models/tools and frameworksContinuously improve CI/CD and testing frameworksContinuously researching and staying updated on the latest advancements in machine learning and AI technologiesRequirements:

Possess expert knowledge in system architecture and engineering best practicesProficiency in programming languages such as Python, R, or Java, and experience with machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn)Minimum 4 years of experience as a Machine Learning Engineer, Software Engineer, Data Scientist, or a similar role, with a focus on developing and deploying ML models, as well as building the corresponding infrastructure for model scaling and pipeline automationFamiliarity with cloud computing platforms and distributed computing frameworksFamiliarity with the implementation of econometrics methods including double machine learning, time series analysis, and optimization techniquesExperience with virtualization and cluster management tools, including Docker & KubernetesDemonstrated performance of delivering of end-to-end ML solutions that realized meaningful value to stakeholdersStrong problem-solving skills and the ability to work independently in a dynamic environmentExcellent communication and teamwork skills to collaborate effectively with diverse stakeholdersA strong academic background with a degree in Computer Science, Engineering, or a related field.

At Keystone we believe diversity matters.

At every level of our firm, we seek to advance and promote diversity, foster an inclusive culture, and ensure our colleagues have a deep sense of respect and belonging.