Firm overview:

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 behaviour and regulation laws. We also provide value by delivering insights and product that defines the future of the technological ecosystem. Keystone brings an interdisciplinary approach, leveraging the intersection of economics, software and technology, and business strategy to deliver transformative ideas.

At Keystone we believe everything is an opportunity for creativity. Transformative ideas can contradict common knowledge. Work hard and be nice to people. Trust can get through catastrophe. Impact takes work. It is never too far gone to salvage. We can deliver anything. Unprecedented outcomes come from unconstrained thinking.

Position overview:

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.

Role and Responsibilities:

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. 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 improve CI/CD and testing frameworks
Continuously researching and staying updated on the latest advancements in machine learning and AI technologies

Requirements:

Possess expert knowledge in system architecture and engineering best practices
Proficiency 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 automation
Familiarity with cloud computing platforms and distributed computing frameworks
Familiarity with the implementation of econometrics methods including double machine learning, time series analysis, and optimization techniques
Experience with virtualization and cluster management tools, including Docker & Kubernetes
Demonstrated performance of delivering of end-to-end ML solutions that realized meaningful value to stakeholders
Strong problem-solving skills and the ability to work independently in a dynamic environment
Excellent communication and teamwork skills to collaborate effectively with diverse stakeholders
A strong academic background with a degree in Computer Science, Engineering, or a related field. Additional study or degrees in Economics is preferred

US Salary Range: $175,000 - $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.

Keystone Strategy

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Machine Learning Engineer