We are seeking a Senior Machine Learning Engineer with strong Data Engineering and Machine Learning experience to help build and scale a modern enterprise ML and Data Platform. This role requires hands-on expertise in Azure Databricks, Python Model Development, Medallion Architecture, MLflow, Delta Lake, and enterprise-scale data engineering. Candidates must possess strong business acumen and communication skills, as they will work directly with business stakeholders, architects, and executive leadership teams.
Required Skills 5 7+ years of hands-on Machine Learning Engineering experience with model development, feature engineering, model deployment, monitoring, and MLOps.
Strong experience with Azure Databricks, Delta Lake, Databricks Workflows, MLflow, and modern data engineering frameworks.
Extensive experience implementing and supporting Medallion Architecture (Bronze, Silver, Gold) and building ML-ready data platforms.
Strong Python development experience for machine learning, predictive modeling, feature engineering, data processing, and automation.
Advanced SQL skills with experience developing optimized ELT/ETL pipelines, data transformations, semantic layers, and curated data models.
Experience designing and building Enterprise Feature Stores and ML-ready Gold Layer datasets.
Experience integrating machine learning outputs into analytics platforms, dashboards, and business-facing applications.
Proven ability to translate business requirements into scalable machine learning and data engineering solutions.
Experience mentoring technical teams, establishing coding standards, engineering best practices, and scalable development frameworks.
Strong communication skills with experience interacting directly with business leaders, directors, and executive stakeholders.
Preferred Skills Azure Cloud Services and enterprise cloud architecture experience.
Experience with Power BI, DAX, semantic models, dashboards, and analytics reporting.
Familiarity with GIS technologies.
Experience with Generative AI, LLMs, AI Agents, Retrieval-Augmented Generation (RAG), and advanced machine learning techniques.
Experience with model monitoring, drift detection, ML observability, and governance frameworks.
Responsibilities Lead the development and evolution of the organization's Modern ML & Data Platform.
Design, develop, and support end-to-end machine learning pipelines including data ingestion, feature engineering, model training, deployment, and monitoring.
Architect and operationalize Bronze Silver Gold data flows supporting advanced analytics and machine learning workloads.
Build and maintain Enterprise Feature Stores and production-grade ML-ready datasets.
Develop scalable ETL/ELT frameworks, data acquisition pipelines, and automated workflows.
Collaborate with Data Engineering, Analytics, Product, and Business teams to deliver enterprise-scale machine learning solutions.
Mentor engineers and establish machine learning engineering standards, governance, and best practices.
Ensure data quality, lineage, governance, security, scalability, and performance optimization across ML and Data platforms.
Support semantic models, dashboards, and reporting solutions that surface machine learning insights and operational metrics.
Drive innovation through AI, advanced analytics, predictive modeling, and data-driven decision-making initiatives.
Ideal Candidate Self-starter with strong problem-solving and analytical abilities.
Comfortable working in a fast-paced, highly collaborative environment.
Strong tenure and stability in prior positions preferred.
Ability to bridge business strategy, analytics, and machine learning technologies.
Passionate about building enterprise-scale ML platforms that drive measurable business outcomes.
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