Machine Learning Data Architect

If you're seeking a sense of community and the ability for growth, look no further. Since 1982, we have been 100% dedicated to our people. Our approach permits greater ownership for individuals and welcomes input into decisions for a thriving workplace and happy employees. Our people are the core reason for AIS' success. As an employee owned company, we are looking for individuals that are passionate about finding innovative solutions, and excited about emerging technologies and capabilities.

We are seeking a highly skilled Machine Learning Data Architect to lead the design and implementation of scalable data architectures that support advanced AI and machine learning initiatives for a major utility client. This role is critical to ensuring the success of AI-driven solutions by enabling robust data pipelines, governance, and model deployment frameworks.

• Architect Scalable Data Solutions: Design and implement data architectures optimized for machine learning workflows, including data ingestion, transformation, storage, and retrieval.

• ML Infrastructure Design: Collaborate with data scientists and engineers to build infrastructure for training, testing, and deploying ML models at scale.

• Data Governance & Quality: Establish data governance frameworks, ensure data integrity, and implement best practices for data security and compliance.

• Cloud & On-Prem Integration: Develop hybrid data solutions that integrate cloud platforms (e.g., Azure, AWS, GCP) with on-premise systems.

• Model Lifecycle Management: Support MLOps practices including versioning, monitoring, and retraining of models.

• Stakeholder Collaboration: Work closely with business analysts, data scientists, and IT teams to align data architecture with business goals.

• Performance Optimization: Tune data systems for performance, scalability, and cost-efficiency.

• This is a remote position with occasional travel (if needed)

• Strong expertise in data modeling, ETL/ELT pipelines, and big data technologies (e.g., Spark, Hadoop).

• Proficiency in cloud platforms (Azure) and containerization tools (Docker, Kubernetes).

• Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn) and MLOps tools (MLflow, Kubeflow).

• Deep understanding of data privacy, security, and regulatory compliance (e.g., GDPR, CCPA).

• Excellent communication and stakeholder management skills.

• Experience in the utility or energy sector.

• Familiarity with time-series data and IoT data streams.

• Certifications in cloud architecture or data engineering.

• Oracle OCI

This position is contingent upon contract award. We are currently pursuing a proposal and are seeking qualified candidates to include in our submission and identify candidates for future hiring needs on the program once awarded.

Applied Information Sciences does not discriminate on the basis of race, national origin, religion, color, gender, sexual orientation, age, disability, protected veteran status, or any other basis. Employment decisions are based solely on qualifications, merit, and business needs.