Data EngineerMachine Learning Developer

Virginia, VA - USA

Monthly Salary: Not Disclosed

Posted on: 9 hours ago

Vacancies: 1 Vacancy

Job Summary

We are seeking a motivated and experienced Mid-Level Data Engineer and Machine Learning (ML) Developer with Agile methodology experience to support advanced data analytics and machine learning initiatives. This role focuses on designing developing and deploying scalable ML models and data pipelines that solve complex real-world problems. The ideal candidate is a strong problem solver who thrives in a collaborative fast-paced environment and can work end-to-end across data engineering and machine learning workflows.

Responsibilities

Design develop and deploy machine learning models and data pipelines to support operational analytics and predictive insights.
Import process and analyze large-scale operational and performance datasets.
Develop predictive models perform root cause analysis trend analysis and IoT signal analytics.
Build and optimize end-to-end data analytics solutions from ingestion to model deployment.
Deliver ML software components in collaboration with Product and Data Science teams.
Write test and maintain application code and ML models including automated testing and deployment.
Collaborate within a cross-functional Agile team to develop next-generation big data and ML applications.
Leverage cloud-based architectures to deploy scalable and optimized ML models.
Construct and maintain optimized data pipelines to feed ML models.
Use programming languages such as Python Scala or Java.
Apply CI/CD best practices including test automation and monitoring.
Advocate for software and ML engineering best practices across the team.
Serve as a technical lead for large-scale initiatives when required.
Perform statistical analysis model tuning and performance evaluation.
Transform data science prototypes into production-ready solutions.
Build data visualization manipulation and processing tools for team use.
Ensure high-quality data reproducible experiments and actionable analytical outcomes.
Work with development teams to automate data logging and repeatable analytics tasks.

Qualifications

Required

U.S. Citizenship with the ability to pass a background investigation.
Applicable combination of education and experience:
- Mid-Level (T3): Bachelors degree in Computer Science Engineering Mathematics or related field plus 5 years of experience working with ML frameworks and production data pipelines.
- Senior-Level (T4): Bachelors degree in a related field plus 7 years of experience including 5 years in data preparation and ML model development.
Proven experience as a Machine Learning Engineer Data Engineer or similar role.
Experience developing and deploying ML solutions in public cloud environments.
Proficiency with ML frameworks and libraries such as TensorFlow PyTorch scikit-learn Pandas and similar tools.
Strong programming skills in Python with working knowledge of Java or R.
Solid understanding of data structures data modeling and software architecture.
Strong background in mathematics probability statistics and algorithms.
Experience developing and evaluating predictive models using large high-volume datasets.
Knowledge of statistical techniques such as regression classification clustering hypothesis testing and optimization.
Ability to analyze relational data models and integrate ML model inputs/outputs into transactional systems.
Self-starter with the ability to work independently and collaboratively.
Strong organizational time management and communication skills.
Ability to work effectively in a fast-paced dynamic environment.

Desired

Experience with Spark Kafka TensorFlow PyTorch or similar big data tools.
Experience building real-time or near real-time ML systems.
Prior experience leading or mentoring small technical teams.
Experience automating business processes using RPA technologies.
Familiarity with operational or enterprise-scale systems.

Job Summary We are seeking a motivated and experienced Mid-Level Data Engineer and Machine Learning (ML) Developer with Agile methodology experience to support advanced data analytics and machine learning initiatives. This role focuses on designing developing and deploying scalable ML models and dat...

Job Summary

Responsibilities

Design develop and deploy machine learning models and data pipelines to support operational analytics and predictive insights.
Import process and analyze large-scale operational and performance datasets.
Develop predictive models perform root cause analysis trend analysis and IoT signal analytics.
Build and optimize end-to-end data analytics solutions from ingestion to model deployment.
Deliver ML software components in collaboration with Product and Data Science teams.
Write test and maintain application code and ML models including automated testing and deployment.
Collaborate within a cross-functional Agile team to develop next-generation big data and ML applications.
Leverage cloud-based architectures to deploy scalable and optimized ML models.
Construct and maintain optimized data pipelines to feed ML models.
Use programming languages such as Python Scala or Java.
Apply CI/CD best practices including test automation and monitoring.
Advocate for software and ML engineering best practices across the team.
Serve as a technical lead for large-scale initiatives when required.
Perform statistical analysis model tuning and performance evaluation.
Transform data science prototypes into production-ready solutions.
Build data visualization manipulation and processing tools for team use.
Ensure high-quality data reproducible experiments and actionable analytical outcomes.
Work with development teams to automate data logging and repeatable analytics tasks.

Qualifications

Required

U.S. Citizenship with the ability to pass a background investigation.
Applicable combination of education and experience:
- Mid-Level (T3): Bachelors degree in Computer Science Engineering Mathematics or related field plus 5 years of experience working with ML frameworks and production data pipelines.
- Senior-Level (T4): Bachelors degree in a related field plus 7 years of experience including 5 years in data preparation and ML model development.
Proven experience as a Machine Learning Engineer Data Engineer or similar role.
Experience developing and deploying ML solutions in public cloud environments.
Proficiency with ML frameworks and libraries such as TensorFlow PyTorch scikit-learn Pandas and similar tools.
Strong programming skills in Python with working knowledge of Java or R.
Solid understanding of data structures data modeling and software architecture.
Strong background in mathematics probability statistics and algorithms.
Experience developing and evaluating predictive models using large high-volume datasets.
Knowledge of statistical techniques such as regression classification clustering hypothesis testing and optimization.
Ability to analyze relational data models and integrate ML model inputs/outputs into transactional systems.
Self-starter with the ability to work independently and collaboratively.
Strong organizational time management and communication skills.
Ability to work effectively in a fast-paced dynamic environment.

Desired

Experience with Spark Kafka TensorFlow PyTorch or similar big data tools.
Experience building real-time or near real-time ML systems.
Prior experience leading or mentoring small technical teams.
Experience automating business processes using RPA technologies.
Familiarity with operational or enterprise-scale systems.

Key Skills

Apache Hive
S3
Hadoop
Redshift
Spark
AWS
Apache Pig
NoSQL
Big Data
Data Warehouse
Kafka
Scala

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Data EngineerMachine Learning Developer

Virginia, VA - USA

Job Summary

Job Summary

Responsibilities

Qualifications

Required

Desired

Job Summary

Responsibilities

Qualifications

Required

Desired

Key Skills

About Company

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