Sr. Director of Data Science Engineering

Location: Chicago, Illinois, United States; hybrid schedule with three days per week in the office

Base pay: $161,500–$299,700 annually, plus eligibility for an annual incentive bonus.

Company

hirify.global is a purpose-driven healthcare organization supporting its members through health insurance and related services.

What you will do

• Develop the strategy and operating plans for the Data Science Engineering function.
• Lead machine learning engineers in building and operationalizing scalable AI/ML solutions with data scientists, product managers, IT, and business stakeholders.
• Establish MLOps practices covering CI/CD, model deployment, monitoring, lifecycle management, and reliability for traditional ML and generative AI systems.
• Architect secure and scalable cloud infrastructure for model training, inference, and serving.
• Drive engineering standards for code quality, automated testing, observability, reproducibility, and responsible AI.
• Recruit, develop, and evaluate personnel while overseeing budgets, operations, and resource allocation.

Requirements

• Bachelor’s degree with 7 years of relevant experience, Master’s degree with 6 years, or Ph.D. with 4 years in computer science, engineering, or a related field.
• At least 4 years of management or leadership experience.
• Proficiency in at least five and mastery of one of six areas: software engineering and version control, machine learning development and evaluation, MLOps and model deployment, high-level programming such as Python, generative and agentic AI, or healthcare.
• Experience independently delivering or leading multiple complex machine learning engineering solutions and products.
• Experience with agile development, business cases, cost-benefit analysis, ROI justification, annual budgeting, and resource allocation.

Nice to have

• Master’s degree in a computational field or significant healthcare experience with a Bachelor’s degree.
• Experience with AWS, Azure, GCP, cloud-native ML services, Docker, Kubernetes, and infrastructure-as-code.
• Experience with MLflow, Kubeflow, SageMaker, Azure ML, Databricks, model monitoring, drift detection, and responsible AI tooling.
• Experience deploying generative AI and LLM-based solutions, including LLMOps, RAG architectures, and vector databases.

Culture & Benefits

• Curated development plans and professional growth opportunities.
• Health and wellness benefits, 401(k) savings plan, pension plan, and paid time off.
• Paid parental leave, disability and supplemental life insurance, and an employee assistance program.
• Paid holidays, tuition reimbursement, and additional incentives.