Hybrid Senior Development Operations Engineer

at InDepth Engineering Solutions

• Job title: Senior Development Operations Engineer
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Tech skills: AWS, NoSQL, Numpy, Pandas, Python, Scikit-Learn, SQL, Go
• Location requirements: Hybrid, Normal, United States

About the role

• Staff AI/ML Engineer & Data Scientist at InDepth Engineering Solutions, focusing on ML pipelines and statistical analysis. Remote work with occasional travel to Normal, IL.

Responsibilities

• Lead the design, deployment, and maintenance of production-grade ML systems
• Architect robust ML pipelines and apply advanced statistical techniques
• Ensure models are accurate, explainable, and scalable
• Apply algorithms such as regression, tree-based models, SVMs, clustering, and forecasting to solve high-impact problems
• Lead the full lifecycle from data preprocessing and feature engineering to training, validation, deployment, and monitoring
• Apply hypothesis testing, Bayesian methods, and model interpretability techniques to ensure reliable insights
• Define ML architecture, best practices, and performance standards for enterprise-scale solutions
• Build scalable ML pipelines and APIs in Python (primary) and Golang (for backend services)
• Design and manage CI/CD pipelines for ML, including automated retraining, model versioning, monitoring, and rollback strategies
• Partner with engineering, analytics, and product teams to align technical solutions with business objectives

Requirements

• 8+ years of experience in applied ML or data science
• 3+ years in a senior or staff-level role and devops experience
• Expert proficiency in Python for ML development (Good to have: Golang for backend integration)
• Proven experience deploying traditional ML models to production with measurable business impact
• Strong knowledge of ML frameworks (Scikit-learn, XGBoost, LightGBM) and data libraries (Pandas, NumPy, Statsmodels)
• Hands-on MLOps experience with tools like MLflow (preferred), Databricks(preferred), Kubeflow, Vertex AI Pipelines, or AWS SageMaker Pipelines
• Experience with model monitoring, drift detection, and automated retraining strategies
• Strong database skills (SQL and NoSQL)
• Masters degree or PHD is mandatory

Benefits

• Mostly remote with a required trip to Normal, IL once a month for three days