Top 979 Machine learning engineer Jobs in Gambrills, Md

Data Architect
WSSC Water —Laurel, MD
- $135,814 - $231,251 a year
- Full-time
- System design
- HIPAA
- Office
Signal and Image Processing Engineer
Johns Hopkins Applied Physics Laboratory (APL) —Laurel, MD
- $85,000 - $195,000 a year
- Full-time
- Computer science
- Computer Science
- Bachelor of Science
- Disability insurance
- Health insurance
Systems Engineer
Leidos —Odenton, MD
- $69,550 - $125,725 a year
- Full-time
- Computer Science
- Java
- Databases
3d
Systems Engineer
National Security Agency —Fort Meade, MD
- $105,262 - $197,200 a year
- 8 hour shift
- Doctoral degree
- Computer Science
- Engineering
11d
Strategic Artificial Intelligence (AI) Engineer
Computer World Services —Fort Meade, MD
- $130,000 - $150,000 a year
- Hybrid work
- Computer science
- Computer Science
- Engineering
Artificial Intelligence/Machine Learning Engineer
Everwatch —Annapolis Junction, MD
- $47.60 - $108.18 an hour
- Azure
- Mid-level
- 3 years
7d
Artificial Intelligence/Machine Learning Engineer, Junior
Everwatch —Annapolis Junction, MD
- $55.28 - $72.11 an hour
- Azure
- Computer Science
- Master's degree
7d
Machine Learning Operations (MLOps) Engineer
University of Maryland —College Park, MD
- $150,000 - $225,000 a year
- Full-time
- Background check
- Azure
- Computer Science
Senior Systems Applications Engineer
HII —Fort Meade, MD
- $129,285 - $210,000 a year
- Email
- System design
- 11+ years
- Office
- Paid holidays
- Health insurance
Machine Learning Engineer
Lynker Corporation —College Park, MD
- $95,000 - $195,000 a year
- Full-time
- Remote
- English
- Office
- Math
- Paid holidays
- Disability insurance
Data Scientist
CACI —Bethesda, MD
- $66,700 - $133,300 a year
- Full-time
- Hybrid work
- Computer science
- Computer Science
- SQL
- Health insurance
3d
Machine Learning Engineer
Johns Hopkins Applied Physics Laboratory (APL) —Laurel, MD
- $100,000 - $245,000 a year
- Full-time
- Computer Science
- Writing skills
- Mid-level
- Disability insurance
- Health insurance
2026 Graduate – Data Science – System Performance Evaluation
Johns Hopkins Applied Physics Laboratory (APL) —Laurel, MD
- $85,000 - $165,000 a year
- Full-time
- Computer science
- Computer Science
- Master's degree
- Disability insurance
- Health insurance
DevOps Engineer
Everwatch —Annapolis Junction, MD
- $72.12 - $110.58 an hour
- 5 years
- High school diploma or GED
- AWS
7d
Mid-Level Software Engineer (Remote)
RealmOne —Columbia, MD
- $145,000 - $160,000 a year
- Full-time
- Remote
- Computer Science
- Mid-level
- Java
- Paid training
- Paid parental leave
Machine Learning Application Engineer
University of Maryland —College Park, MD
- $49,072 - $252,288 a year
- Background check
- Computer science
- Computer Science
Senior Machine Learning Engineer, Public Sector
Scale AI —Washington, DC
- $225,750 - $282,450 a year
- Computer science
- Computer Science
- Research
Senior Data Scientist
Peraton —Fort Meade, MD
- $135,000 - $216,000 a year
- Bachelor of Science
- 11+ years
- Master's degree
- Health savings account
- Paid holidays
AI/ML Platform Engineer
Johns Hopkins Applied Physics Laboratory (APL) —Laurel, MD
- $85,000 - $195,000 a year
- Full-time
- Computer Science
- Engineering
- Mid-level
- Disability insurance
- Health insurance
Distinguished Engineer - Delivery (Remote)
CareFirst BlueCross BlueShield —Baltimore, MD
- $184,560 - $342,590 a year
- Full-time
- Remote
- Computer science
- Azure
- Computer Science
- 401(k)

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machine learning engineer jobs near gambrills, md

Data Architect

WSSC Water -
Laurel, MD

Apply Now

Job Details

Full-time
$135,814 - $231,251 a year

Qualifications

Data integrity assurance
Data model design
Commercial use (data warehousing systems)
Systems integration
Cloud analytics services
Data Integration (Data management)
Data modeling projects
System performance optimization
System design
Integration Architecture Design (Architecture design skills)
IoT systems
Scalable systems
Managing data teams
Object storage systems
Schema design
Database security management
Infrastructure architecture design
Information security compliance
Cloud database architecture
Data integrity process (data warehousing)
Enterprise Integration
Regulatory Frameworks (Architecture security)
Leading team collaboration initiatives
Scalability
Data-driven problem-solving
Agile
Cloud compliance
Managing projects
Technical troubleshooting support
Access control management

Full Job Description

This is a non-merit employment-at-will contract position.

The Data Architect plays a critical role in designing and implementing secure, scalable data architectures that integrate operational and enterprise data from sources such as SCADA systems, IoT devices, sensors, and business platforms. This position is responsible for developing a unified data ecosystem that enables real-time data processing, advanced analytics, and data-driven insights to support optimized operations, predictive maintenance, and informed decision-making.

The role ensures the integrity, security, and governance of data by establishing and enforcing industry-compliant standards, protecting sensitive water system information while promoting accessibility and reliability across the organization. Leveraging modern cloud technologies and data platforms, the Data Architect drives the transformation of data into a strategic asset, enhancing asset management, water quality monitoring, and overall operational performance supporting the delivery of safe, reliable, and high-quality water services.

Essential Functions

Lead the design, development, and implementation of scalable and secure data architectures that support WSSC Water’s operational systems and data needs
Develop and maintain data models, database schemas, and data warehouses tailored to the water and wastewater industry
Design, integrate and optimize real-time data pipelines to support the integration of operational data from various sources (e.g., SCADA, GIS, sensors, IoT devices, field data and enterprise systems)
Design ETL (Extract, Transform, Load) processes to ensure smooth, efficient data flow between operational systems and analytics platforms
Ensure data consistency, quality, and availability across different platforms, supporting both historical and real-time analytics
Develop hybrid cloud architectures to leverage cloud computing platforms (e.g., AWS, Azure, GCP, OCI) while maintaining necessary on-premises solutions
Ensure seamless integration between on-premises and cloud data environments for scalability, flexibility, and cost-effectiveness
Lead cloud migration initiatives, ensuring that legacy systems are efficiently transitioned to modern cloud-based infrastructure
Design robust security practices, including data encryption, access controls, and data masking protocols, to protect sensitive water and wastewater data, ensuring compliance with regulatory requirements
Collaborate with IT security teams to establish data governance frameworks, risk mitigation strategies, and incident response plans
Establish and enforce data governance policies and practices to ensure data accuracy, consistency, and reliability across all systems
Develop frameworks for data lineage, metadata management, and data cataloging to improve data traceability and transparency
Lead initiatives to improve data quality by identifying issues and implementing solutions for cleansing, standardization, and validation
Design data architecture to support advanced analytics, machine learning, and AI workloads for predictive modeling, asset management, and operational optimization
Ensure that data infrastructure supports real-time analytics for enhanced decision-making and monitoring of water quality, usage patterns, and infrastructure performance
Work closely with data science teams to provide the necessary data structures and processes to enable data-driven insights
Document data architecture designs, processes, and systems to ensure transparency, maintainability, data usage, integration procedures, and security protocols to enable team collaboration and compliance
Conduct training and knowledge-sharing sessions for internal teams to improve understanding of data systems and best practices

Other Functions

Partner with stakeholders across WSSC Water, including operations, engineering, regulatory compliance, and customer service, to align data architecture with business goals
Provide technical leadership and mentorship to a team of data engineers, analysts, and other data professionals
Lead the evaluation and selection of third-party tools, platforms, and vendors to support data architecture and integration efforts
Continuously monitor the performance of data architecture systems and implement optimizations for speed, reliability, and cost-effectiveness
Design systems that are highly available and resilient to ensure continuous operations in the event of system failures or disruptions
Scale data infrastructure to accommodate growing volumes of data, supporting increased usage and future technological advancements
Stay current with emerging technologies, industry trends, and best practices related to data architecture, cloud computing, big data, and data security
Proactively identify opportunities for innovation and process improvements in data systems, ensuring that WSSC Water maintains a competitive edge in the water and wastewater sector
Contribute to the long-term strategic vision for data architecture, helping to drive digital transformation across the organization
Perform other related duties as required

Work Environment And Physical Demands

Business casual office environment

Required Knowledge, Skills, And Abilities

Expertise in designing scalable data systems, including data modeling (conceptual, logical, and physical), data standardization, data lifecycle management, and building data lakes and warehouses to support large-scale integration and analytics
Proficiency managing data lakes, performing analytics, and optimizing data warehousing solutions (e.g. Azure Synapse Analytics)
Strong experience designing data pipelines, transforming large datasets, and supporting real-time analytics and machine learning or other ETL tools such as Azure Databricks, Azure Data Factory, Apache Nifi etc.
Proficiency in SQL, Python, Scala, or Java for managing and processing data across systems, particularly in Azure Databricks
Knowledgeable in big data technologies (e.g., Hadoop, Spark) and their integration with cloud platforms for handling large volumes of data securely and efficiently
Experience with scalable and secure storage of large datasets (such as Azure Data Lake Storage and Azure Blob Storage)
In-depth knowledge of data security practices, including encryption, access control, identity management, and secure data storage
Expertise in implementing data privacy and regulatory compliance frameworks, such as GDPR, CCPA, HIPAA, and industry-specific utility standards
Experience in managing and securing sensitive data using tools such as Azure Security Center and Azure Key Vault
Strong understanding of data governance frameworks, ensuring data quality, integrity, and traceability through tools such as Azure Purview and/or other metadata management tools
Knowledge of data lineage and metadata management practices to ensure data accuracy and compliance throughout the data lifecycle and knowledge of data cataloging with tools such as Alation, Collibra, Atlan or any similar product
Familiarity with water and wastewater management systems, including SCADA, GIS, IoT sensors, and how these integrate with data architecture
Understanding of operational challenges in water distribution, treatment, and wastewater management, and how data systems can optimize these processes
Strong analytical skills to troubleshoot complex data systems, identify bottlenecks, and propose data-driven solutions for improved performance and security
Ability to design and manage cloud-based data architecture
Expertise in integrating disparate data sources (e.g., IoT, SCADA, sensors) into centralized data repositories using modern cloud tools
Strong project management skills to oversee the design, development, and deployment of data architecture projects, ensuring deadlines and requirements are met
Familiarity with agile methodologies for managing data-related projects and collaborating with cross-functional teams
Proven ability to work with different application stakeholders across the organization in designing effective data flows at the onset of large enterprise initiatives

Minimum Education, Experience Requirements

Bachelor’s degree
8+ years experience as a Data Architect or in a similar data-related role, with a focus on designing and implementing large-scale data systems
3+ years experience working with cloud data management platforms such as Azure Synapse Analytics and Azure Databricks
Experience with big data technologies such as Apache Spark, Hadoop, or equivalent, and cloud data storage solutions (e.g., Azure Data Lake Storage)
Proficiency in SQL, Python, or Scala for data processing and transformation
Knowledge of data modeling and data warehousing concepts for designing scalable data architectures
Knowledge of data governance principles, such as metadata management, data lineage, data cataloging, and data quality standards
Strong analytical and troubleshooting skills, with the ability to optimize data systems and resolve technical challenges related to performance, security, and scalability
Ability to communicate complex technical concepts to non-technical stakeholders
Strong collaboration skills to work with cross-functional teams and lead data-related projects

High school diploma or equivalent
12+ years experience as a Data Architect or in a similar data-related role, with a focus on designing and implementing large-scale data systems
3+ years experience working with cloud data management platforms such as Azure Synapse Analytics and Azure Databricks
Experience with big data technologies such as Apache Spark, Hadoop, or equivalent, and cloud data storage solutions (e.g., Azure Data Lake Storage)
Proficiency in SQL, Python, or Scala for data processing and transformation
Knowledge of data modeling and data warehousing concepts for designing scalable data architectures
Knowledge of data governance principles, such as metadata management, data lineage, data cataloging, and data quality standards
Strong analytical and troubleshooting skills, with the ability to optimize data systems and resolve technical challenges related to performance, security, and scalability
Ability to communicate complex technical concepts to non-technical stakeholders
Strong collaboration skills to work with cross-functional teams and lead data-related projects

Apply Now

Refine Your Search

machine learning engineer jobs in gambrills, md

Data Architect

Signal and Image Processing Engineer

Systems Engineer

Systems Engineer

Strategic Artificial Intelligence (AI) Engineer

Artificial Intelligence/Machine Learning Engineer

Artificial Intelligence/Machine Learning Engineer, Junior

Machine Learning Operations (MLOps) Engineer

Senior Systems Applications Engineer

Machine Learning Engineer

Data Scientist

Machine Learning Engineer

2026 Graduate – Data Science – System Performance Evaluation

DevOps Engineer

Mid-Level Software Engineer (Remote)

Machine Learning Application Engineer

Senior Machine Learning Engineer, Public Sector

Senior Data Scientist

AI/ML Platform Engineer

Distinguished Engineer - Delivery (Remote)

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