Senior Manufacturing AI/Data Science Engineer (AI)

Location: Northridge, California, or St. Louis Park, Minnesota, United States. Hybrid schedule with 3 onsite days and 2 remote days per week; occasional visits to manufacturing floor environments may be required.

Salary: $112,000–$190,000 USD annually for U.S. locations excluding Puerto Rico.

Company

hirify.global is a full-stack insulin delivery company developing intelligent dosing systems and predictive support for people living with diabetes.

What you will do

• Develop and mature manufacturing data pipelines by identifying critical data elements and partnering with data engineering teams through requirements, development, validation, and production deployment.
• Convert complex operational data into governed insights, authoritative source-of-truth metrics, and measurable improvements in operational excellence and cost efficiency.
• Support root cause investigations using advanced analytics, statistical rigor, and computational methods to isolate variation and resolve quality and process challenges.
• Identify and implement AI and machine learning solutions across manufacturing, supply chain, operations, and new product introduction, considering data readiness, regulatory requirements, and business value.
• Partner with operational functions, build cross-functional relationships, and improve Data Science team maturity through reusable tooling, documentation standards, and technical mentorship.

Requirements

• Required: Bachelor’s degree in Data Science, Statistics, Computer Science, Industrial Engineering, or a related quantitative field. A master’s degree is preferred.
• Required: At least 5 years of applied data science or machine learning engineering experience, including meaningful experience in manufacturing, supply chain, or industrial operations.
• Familiarity with manufacturing execution system (MES) and ERP data structures.
• Proficiency in Python for data science and machine learning development, including pandas, scikit-learn, PyTorch, and TensorFlow.
• Strong SQL skills and experience with cloud data platforms such as Databricks, Snowflake, Azure, and AWS.
• Experience developing and deploying production machine learning models and analytical pipelines.
• Exposure to computer vision, NLP, or generative AI applications in industrial or operational contexts.
• Experience with BI and data visualization tools such as Power BI or Tableau.
• Ability to communicate complex analytical concepts clearly to non-technical business and operations stakeholders and work effectively in cross-functional, matrixed environments with competing priorities and ambiguous problem definitions.

Nice to have

• Master’s or Ph.D. in a quantitative discipline.
• Foundation in hypothesis testing, regression analysis, statistical process control, design of experiments, and process capability analysis.
• Experience in a regulated industry such as medical devices, pharmaceuticals, or aerospace, with familiarity with FDA data integrity requirements or GxP standards.
• Familiarity with MLOps platforms such as MLflow, Azure Machine Learning, or AWS SageMaker.
• Experience with AI-assisted coding environments such as Windsurf or GitHub Copilot.
• Experience with IoT or IoT sensor data and time-series data pipelines.
• Knowledge of Lean Manufacturing or Six Sigma; Green Belt or Black Belt certification is a plus.

Culture & Benefits

• Hybrid office environment with flexible work arrangements and occasional manufacturing floor visits.
• Health, dental, and vision insurance, plus Health Savings Account and Healthcare Flexible Spending Account access.
• Life insurance, disability coverage, paid time off, and paid holidays.
• 401(k) plan with company match, Employee Stock Purchase Plan, and Employee Assistance Program.
• Short-term incentive plan and additional retirement and capital accumulation plans for eligible employees.