Data Engineer/Machine Learning Developer

Data Engineer/Machine Learning Developer

CACI is currently looking for a motivated, career and customer-oriented Mid-level of Data Engineer and Machine Learning (ML) Developer with Agile methodology experience to join our Customs and Border Protection (CBP) Land Border Integration (LBI) Integrated Traveler Initiative 2.1 (ITI2.1) team in Northern Virginia! Join this passionate team of industry-leading individuals supporting the best practices in Agile Software Development and hardware integration for the Department of Homeland Security (DHS).

As a member of the ITI2.1 Team, you will support the men and women charged with safeguarding the American people and enhancing the Nation's safety, security, and prosperity. CBP Officers and Border Patrol agents are on the front lines, every day, protecting our national security by combining customs, immigration, border security, and agricultural protection into one coordinated and supportive activity.

CACI agile programs thrive in a culture of innovation and are constantly seeking individuals who can bring creative ideas to solve complex problems, both technical and procedural at the team and portfolio levels. The ability to be adaptable and to work constructively with a technically diverse and geographically separated team is crucial.

What you'll get to do:

The Data Engineer will work with interdisciplinary data teams to design, develop, and deploy machine learning algorithms in ITI2.1 program. The individual will import daily O&M operational and performance outcomes, develop predictive maintenance model to infer and recommend business decision, and/or conduct root cause analysis, support IoT device signal analytics, and trend analysis for ITI2.1 requirement. We are looking for experienced data engineers who know how to solve complex big data problems, work with algorithms, analyze big data and can run end-to-end data analytics.

• Develop an understanding of the customer's data environment through data profiling, data pipeline, and machine learning/statistical analyses

• Deliver ML software models and components that solve real-world business problems, while working in collaboration with our Product and Data Science teams

• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment

• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art, next generation big data and machine learning applications

• Leverage cloud-based architectures and technologies to deliver optimized ML models at scale

• Construct optimized data pipelines to feed ML models

• Use programming languages like Python, Scala, or Java

• Leverage Continuous Integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployments of ML models and application code

• Advocate for software and machine learning engineering best practices

• Function as the engineering tech lead for large-scale initiatives

• Perform statistical analysis and tune using test results

• Study appropriate datasets and transform data science prototypes

• Train data-driven learning model.

• Maintain and work with data pipeline that transfers and processes large scale of heterogenous structural/non-structural data using Spark, Scala, Python, Apache Kafka, TensorFlow, PyTorch, and/or other data analytic tools

• Design, build and support pipelines of data transformation, conversion, validation

• Build data manipulation, processing, and data visualization tools and share these tools across the team.

• Apply data analysis, data mining and data engineering to present data clearly and develop experiments

• Ensure high-quality data and understand how data is generated out experimental design and how these experiments can produce actionable, trustworthy conclusions.

• Work with development teams to build tools for data logging and repeatable data tasks that will accelerate and automate process.

You have:

• Must be a U.S. Citizen with the ability to pass CBP background investigation, criteria includes, but not limited to:

  • 3-year check for felony convictions

  • 1-year check for illegal drug use

  • 1-year check for misconduct such as theft or fraud

• Applicable combination of education and experience:

  • Data Engineer/Machine Learning Developer T3 - Bachelor's Degree in computer science, electrical engineering, mathematics, or a similar field and 5+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow, and applications related to data gathering and preparation for ML models and building production-ready data pipelines that feed ML models

  • Data Engineer/Machine Learning Developer T4 - Bachelor's Degree in computer science, electrical engineering, mathematics, or a similar field and 7+ years of on-the-job experience with 5+ years data gathering and preparation for ML models

• Proven previous experience as a Machine Learning Engineer or similar role

• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform

• Familiarity with machine learning frameworks (like Keras or PyTorch, or TensorFlow) and libraries (like Pandas or scikit-learn) and ability to write robust code in Python, Java and R

• Proven ML industry impact through conference presentations, papers, blog posts, open-source contributions, or patents

• Essential knowledge of neural networks, Deep Learning and Computer vision algorithms for object detection, feature engineering, and hyperparameter tuning

• Understanding of data structures, data modeling and software architecture

• Deep knowledge of math, probability, statistics and algorithms

• Outstanding analytical and problem-solving skills

• Experience with developing predictive models for using large data sets for high transactional volume environment

• Experience with evaluating and measuring performance of models

• Strong algorithmic problem-solving skills. Experience with statistics, modeling and machine learning techniques Statistics including but limited to hypothesis testing, regression, clustering, classification, and optimization.

• Ability to understand and analyze data models how the data is stored in relational databases

• Ability to understand system integration aspects of integrating model input and output in transactional systems to help real time decision making

• Good understanding software application architecture and develop integration approaches for predictive models

• Possess the ability to perform with little direct supervision as a self-starter. Be a self-motivated, creative, and inquisitive problem solver with a strong work ethic and data integrity.

• Strong organization and time management skills prior experience in leading a small team is preferred

• Have effective oral and verbal, visual and written communication skills.

• Ability to work effectively in a high energy and a very rapid dynamic environment and interact effectively with team members, senior managers, and clients.

• Working knowledge of the CBP Port of Entry systems and/or their operational requirements.

• Experience automating business processes using RPA technologies

This position is contingent on funding and may not be filled immediately. However, this position is representative of positions within CACI that are consistently available. Individuals who apply may also be considered for other positions at CACI.

What You Can Expect:

A culture of integrity.

At CACI, we place character and innovation at the center of everything we do. As a valued team member, you'll be part of a high-performing group dedicated to our customer's missions and driven by a higher purpose to ensure the safety of our nation.

An environment of trust.

CACI values the unique contributions that every employee brings to our