Core AI Engineer

As a Core AI 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, work with our econometricians, scientists, and engineering teams to scope solutions, develop and train ML models, deploy them into production environments, and set up monitors, alerts and diagnostic tools to support model operations.

We are a tech focused 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.

Role and Responsibilities:

In your role as a Core AI Engineer, you will be instrumental in developing and deploying cutting-edge machine learning models and software applications to deliver these models. Your primary responsibilities will include:

• 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 datasets
• Conducting thorough data analysis and pre-processing to ensure high-quality input for the models
• Integrating machine learning solutions into existing systems and processes and scaling them for real-world applications
• Contributing to the development of proprietary machine learning models/tools and frameworks
• Continuously improving CI/CD and testing frameworks and methodologies
• Continuously researching and staying updated on the latest advancements in machine learning and AI technologies

The ideal candidate:

• Possesses expert knowledge in machine learning, software engineering, and system architecture
• Is proficient in programming languages such as Python, R, or Java, and has experience with machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn)
• Has a minimum of 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 automation
• Is familiar with cloud computing platforms and distributed computing frameworks
• Is familiar with the implementation of econometrics methods including double machine learning, time series analysis, and optimization techniques
• Is experienced with virtualization and cluster management tools, including Docker & Kubernetes
• Demonstrates performance of delivering end-to-end ML solutions that have meaningful value to stakeholders
• Is an excellent communicator and has strong teamwork skills to collaborate effectively with diverse stakeholders
• Bachelor’s degree in computer science, Engineering, or a related scientific field
• Strong academic background in Economics/Econometrics
• 2+ years of experience as a Software Engineer with a focus on production systems at scale
• Proficiency in programming languages such as Python, R, or Java, C# and experience with machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn, Jax)
• 2+ years of experience developing and deploying machine learning models into production environments
• Familiarity with cloud computing platforms and distributed computing frameworks
• Strong problem-solving skills and the ability to work independently in a dynamic environment

US Salary Range: $101,000 - $235,000, plus an annual discretionary bonus, 401k contribution, and competitive benefits package. Actual compensation within the range will depend upon the level the individual is hired into based on their skills, experience, qualifications.

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. If you are interested in growing your career with colleagues from varied backgrounds and cultures, consider Keystone Strategy.