Role: Machine Learning Engineer (Azure Databricks / Python)
Location: Plano, TX (Hybrid 3 Days Onsite)
Duration: 24+ Months
Minimum 10 years of experience required...
Education Requirement - Bachelor's Degree in: Computer Science, Information Technology, Or related field
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.
Thanks & Regards, OpenKyber
For applications and inquiries, contact: [email protected]
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