ML/AI Software Engineer

Youngsoft, Inc. ( is a global software solutions IT company, delivering digital enterprise business betterment since 1996. Through collaborative engagement and discovery with our clients and vendors, we co-create industry specialized digital products, applications software, process, programs, and project outcomes. Headquartered in metro-Detroit, we leverage "pods" of Subject Matter Experts, Business Analysts, Solutions Architects, Software Engineers, and Project Managers, fused with HyperCare through our Global Support Centers. Through inclusivity, we share a singular vision to deliver world-class measurable upside results to our customers. It takes a village – come join ours!

• The ML/AI Software Engineer (MASE) is an applied solutions expert who combines working knowledge of machine learning and software engineering best practices.
• As part of a small team of dedicated AI problem solvers, an MASE draws upon their practical skills to conceive, specify, and implement tailored solutions to real-world problems facing VWGoA business users. This work entails problem solving in a variety of domains, including: regression and classification problems; natural language processing tasks; business process optimization; and conducting research and analysis on new technologies and business methodologies.
• An MASE helps to guide projects through their lifecycle from conception to production. As such, an MASE contributes to multiple layers of the solution, which may include: interpretation of problem statements and requirements gathering; the analysis of data and model design; and production implementations, such as dashboards, web APIs, or simple web applications, as appropriate.

• Fluency in Python. Fluent candidates can comfortably: read and write object-oriented Python code; write method and class docstrings; write and verify type signatures; manage package dependencies in a principled way.
• Solid grasp of ML theory. Candidates should be comfortable explaining concepts such as the mathematical intuition behind an SVM, or the role of cross validation in an ML project.
• Experienced with standard ML libraries. For example, pandas, scikit-learn, tensorflow/pytorch/jax, etc.
• Proficiency in SQL. Knowledge of basic SQL syntax is occasionally required for data ingestion and analysis.
• Excited to build production grade software. To help everyone sleep soundly at night, we seek teammates who write code with an eye for maintainability and testability. Candidates should be comfortable writing unit tests and running linters.
• Working knowledge of containers. For example, experience with Docker or podman, and an appreciation for twelve-factor design.
• Comfortable with git. Candidates should be comfortable: making commits; creating and merging branches; navigating GitHub and GitLab; collaborating with colleagues via merge requests.
• Strong command lines skills in nix environments. Our code is typically created and deployed into Unix-like environments.
• Proven engineering background. A technical degree in a field such as Computer Science or Data Analytics, and/or equivalent work experience.

• Graduate degree in a related field, such as Computer Science or Data Analytics
• Prior experience in the Hadoop ecosystem
• Familiarity with Test-Driven Development (TDD)
• Experience with Kubeflow or similar machine learning pipeline solutions
• Experience with Operations Research (OR)
• JavaScript and frontend development experience
• Java knowledge and courage in the face of legacy code
• Experience with Kubernetes, AWS, and cloud-native technologies generally
• A high tolerance for OpenShift, Cloudera, Tableau, Confluence, Jira, and other enterprise tools

• Agency over design process
• Small team - opinions and input valued and actively solicited
• Mission statement for innovation
• Opportunities to choose projects and responsibilities
• Direct access to tech leaders, e.g. nvidia, google, aws, docker