CACI
Overview
CACI is currently looking for a motivated, career and customer-oriented Senior level of 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 supporting 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 protect national security by combining customs, immigration, border security, and agricultural protection into one coordinated activity. CACI agile programs thrive in a culture of innovation and seek individuals who can bring creative ideas to solve complex problems, both technical and procedural at the team and portfolio levels. Adaptability and the ability to work constructively with a technically diverse and geographically separated team are crucial. What you’ll get to do
The ML Developer will work on the development and deployment of machine learning models for the ITI2.1 border applications. The role includes managing and using data to train predictive models, inferring and recommending business intelligence decisions, conducting root cause analysis, supporting IoT device signal analytics, and performing trend analysis. The candidate should be able to solve complex big data problems, work with algorithms, analyze big data, and run end-to-end data analytics processes. Develop an understanding of the customer’s data environment through data profiling, data pipelines, and machine learning/statistical analyses Deliver ML software models and components that solve real-world business problems, collaborating with Product and Data Science teams Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployments Collaborate as part of a cross-functional Agile team to create and enhance software for state-of-the-art, next generation big data and ML applications Leverage cloud-based architectures to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Use programming languages like Python, Scala, or Java Leverage CI/CD best practices, including test automation and monitoring, to ensure successful deployments of ML models and application code Advocate for software and ML engineering best practices Function as the engineering tech lead for large-scale initiatives Perform statistical analysis and tune models using test results Study appropriate datasets and transform data science prototypes Research and implement ML algorithms and tools and develop ML applications according to requirements Train data-driven learning models Maintain and work with data pipelines that process large-scale heterogeneous data using Spark, Scala, Python, Apache Kafka, TensorFlow, PyTorch, and other data analytics tools Design, build and support pipelines of data transformation, conversion, and validation Build data manipulation, processing, and data visualization tools for 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 from experimental design to actionable conclusions Assist senior management in making key business decisions Mentor junior ML engineering talent Work with development teams to build tools for data logging and repeatable data tasks to accelerate and automate data science duties You have
Must be a U.S. Citizen with the ability to pass CBP background investigation (3-year felony check, 1-year checks for illegal drug use and misconduct such as theft or fraud) Bachelor’s degree in computer science, electrical engineering, mathematics, or a similar field and 7 years of related experience Experience developing performant, resilient, and maintainable code Experience with data gathering and preparation for ML models Experience with industry ML frameworks (e.g., Pandas, scikit-learn, PyTorch, Dask, Spark, TensorFlow Keras) and ability to write robust code in Python and Java Strong understanding of neural networks and deep learning algorithms (e.g., MLP, CNN, SGD, GANs, LSTMs, RNNs) Understanding of statistical learning and Bayesian methods Experience deploying ML solutions in public clouds (AWS, Azure, or Google Cloud Platform) Experience building production-ready data pipelines that feed ML models Proven experience as a Machine Learning Engineer or similar role Experience with neural networks, deep learning and computer vision for object detection, feature engineering, and hyperparameter tuning Understanding of data structures, data modeling and software architecture Strong math, probability, statistics, and algorithm knowledge Analytical and problem-solving skills Experience developing predictive models for large data sets in high-transaction environments Knowledge of Bayesian Inference, probabilistic learning, kernel methods, and time series analysis Experience evaluating and measuring model performance Strong algorithmic problem-solving skills and knowledge of statistics, modeling, and ML techniques (hypothesis testing, regression, clustering, classification, optimization) Ability to understand data models and how data is stored in relational databases Ability to understand system integration aspects of integrating model input/output in transactional systems for real-time decision making Good understanding of software architecture and integration approaches for predictive models Strong organizational and time management skills; prior experience leading a small team is preferred Bonus would be having
Practical experience applying state-of-the-art ML techniques to signal/image processing, computer vision, object recognition, biometrics, and sensing applications Knowledge of MLOps concepts Knowledge of OpenCV Proven ML industry impact through conference presentations, papers, blog posts, open-source contributions, or patents Strong fundamentals in problem solving and algorithm design Strong problem-solving and research capabilities Working knowledge of CBP Port of Entry systems and/or their operational requirements Experience automating business processes using RPA technologies What You Can Expect: A culture of integrity and an environment of trust. At CACI, we place character and innovation at the center of everything we do and offer autonomy with flexible time off and learning resources. Pay Range : The proposed salary range for this position is $103,800 - $218,100. EEO statement: CACI is an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, pregnancy, sexual orientation, age, national origin, disability, veteran status, or any other protected characteristic.
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CACI is currently looking for a motivated, career and customer-oriented Senior level of 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 supporting 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 protect national security by combining customs, immigration, border security, and agricultural protection into one coordinated activity. CACI agile programs thrive in a culture of innovation and seek individuals who can bring creative ideas to solve complex problems, both technical and procedural at the team and portfolio levels. Adaptability and the ability to work constructively with a technically diverse and geographically separated team are crucial. What you’ll get to do
The ML Developer will work on the development and deployment of machine learning models for the ITI2.1 border applications. The role includes managing and using data to train predictive models, inferring and recommending business intelligence decisions, conducting root cause analysis, supporting IoT device signal analytics, and performing trend analysis. The candidate should be able to solve complex big data problems, work with algorithms, analyze big data, and run end-to-end data analytics processes. Develop an understanding of the customer’s data environment through data profiling, data pipelines, and machine learning/statistical analyses Deliver ML software models and components that solve real-world business problems, collaborating with Product and Data Science teams Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployments Collaborate as part of a cross-functional Agile team to create and enhance software for state-of-the-art, next generation big data and ML applications Leverage cloud-based architectures to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Use programming languages like Python, Scala, or Java Leverage CI/CD best practices, including test automation and monitoring, to ensure successful deployments of ML models and application code Advocate for software and ML engineering best practices Function as the engineering tech lead for large-scale initiatives Perform statistical analysis and tune models using test results Study appropriate datasets and transform data science prototypes Research and implement ML algorithms and tools and develop ML applications according to requirements Train data-driven learning models Maintain and work with data pipelines that process large-scale heterogeneous data using Spark, Scala, Python, Apache Kafka, TensorFlow, PyTorch, and other data analytics tools Design, build and support pipelines of data transformation, conversion, and validation Build data manipulation, processing, and data visualization tools for 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 from experimental design to actionable conclusions Assist senior management in making key business decisions Mentor junior ML engineering talent Work with development teams to build tools for data logging and repeatable data tasks to accelerate and automate data science duties You have
Must be a U.S. Citizen with the ability to pass CBP background investigation (3-year felony check, 1-year checks for illegal drug use and misconduct such as theft or fraud) Bachelor’s degree in computer science, electrical engineering, mathematics, or a similar field and 7 years of related experience Experience developing performant, resilient, and maintainable code Experience with data gathering and preparation for ML models Experience with industry ML frameworks (e.g., Pandas, scikit-learn, PyTorch, Dask, Spark, TensorFlow Keras) and ability to write robust code in Python and Java Strong understanding of neural networks and deep learning algorithms (e.g., MLP, CNN, SGD, GANs, LSTMs, RNNs) Understanding of statistical learning and Bayesian methods Experience deploying ML solutions in public clouds (AWS, Azure, or Google Cloud Platform) Experience building production-ready data pipelines that feed ML models Proven experience as a Machine Learning Engineer or similar role Experience with neural networks, deep learning and computer vision for object detection, feature engineering, and hyperparameter tuning Understanding of data structures, data modeling and software architecture Strong math, probability, statistics, and algorithm knowledge Analytical and problem-solving skills Experience developing predictive models for large data sets in high-transaction environments Knowledge of Bayesian Inference, probabilistic learning, kernel methods, and time series analysis Experience evaluating and measuring model performance Strong algorithmic problem-solving skills and knowledge of statistics, modeling, and ML techniques (hypothesis testing, regression, clustering, classification, optimization) Ability to understand data models and how data is stored in relational databases Ability to understand system integration aspects of integrating model input/output in transactional systems for real-time decision making Good understanding of software architecture and integration approaches for predictive models Strong organizational and time management skills; prior experience leading a small team is preferred Bonus would be having
Practical experience applying state-of-the-art ML techniques to signal/image processing, computer vision, object recognition, biometrics, and sensing applications Knowledge of MLOps concepts Knowledge of OpenCV Proven ML industry impact through conference presentations, papers, blog posts, open-source contributions, or patents Strong fundamentals in problem solving and algorithm design Strong problem-solving and research capabilities Working knowledge of CBP Port of Entry systems and/or their operational requirements Experience automating business processes using RPA technologies What You Can Expect: A culture of integrity and an environment of trust. At CACI, we place character and innovation at the center of everything we do and offer autonomy with flexible time off and learning resources. Pay Range : The proposed salary range for this position is $103,800 - $218,100. EEO statement: CACI is an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, pregnancy, sexual orientation, age, national origin, disability, veteran status, or any other protected characteristic.
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