Machine Learning Engineer
MANTECH · United States
- Hybrid
- Full-time
- $120,000 / year
- United States
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Job highlights
- Build and deploy scalable ML applications and pipelines.
- Implement full MLOps lifecycle for model management.
- Develop and test ML applications with Python, Java, or R.
- Utilize cloud platforms like AWS, Azure, or GCP.
- Collaborate with cross-functional teams on ML solutions.
About the role
Machine Learning Engineer
MANTECH seeks a motivated, career and customer-oriented Machine Learning Engineer to join our team.
The Machine Learning Engineer will leverage their strong technical background and knowledge to support highly scalable machine learning-based applications, including both pipelines and services, processing large volumes of data. This role involves collaborating with Data Scientists to design tools and train models using data from across the enterprise to support mission and business functions.
Responsibilities Include But Are Not Limited To
- Collaborate with cross-functional teams—including data scientists, engineers, and architects—to build machine learning models, training tools, and simulation environments that support business functions.
- Implement the full MLOps lifecycle to deploy, operationalize, scale, and manage automated machine learning models and analytical solutions.
- Develop and test ML applications according to requirements, running targeted experiments to optimize overall system performance.
- Train and embed machine learning models into applications using programming languages (Python, Java, R) and core libraries (TensorFlow, Keras, Scikit-learn).
- Explore and visualize data to uncover key insights and identify specific factors that impact model accuracy and performance.
- Manage and deploy cloud-based ML services across major cloud computing environments, including AWS, Azure, or Google Cloud Platform (GCP).
- Follow Agile methodologies to deliver production-ready, highly testable code in small, efficient, and continuous iterations.
Minimum Qualifications
- Master’s degree in Applied Mathematics, Statistics, Computer Science, or related fields.
- Verifiable work experience defining and implementing data pipelines and machine learning algorithms.
- Proficiency in Agile Development and Git Operations.
- Experience creating, maintaining, and communicating complex technical documentation for machine learning systems.
Preferred Qualifications
- Experience with the Sponsor’s primary cyber risk and compliance automation tools.
Clearance Requirements
An active Secret clearance is required.
Physical Requirements
- Must be able to remain in a stationary position 50%.
- Needs to occasionally move about inside the office to access file cabinets, office machinery, etc.
- Frequently communicates with co-workers, management, and customers, which may involve delivering presentations.
- Must be able to exchange accurate information in these situations.
Key skills/competency
- Machine Learning Engineer
- MLOps
- Python
- TensorFlow
- Keras
- Scikit-learn
- AWS
- Azure
- GCP
- Agile Methodologies
Skills & topics
- Machine Learning Engineer
- Machine Learning
- MLOps
- Data Pipelines
- Python
- TensorFlow
- Keras
- Scikit-learn
- AWS
- Azure
- GCP
- Agile
- Statistics
- Applied Mathematics
- Computer Science
How to get hired
- Tailor your resume: Highlight your Master's degree and experience with data pipelines, ML algorithms, Agile, and Git.
- Showcase MLOps skills: Emphasize your experience in deploying, operationalizing, and managing ML models in production.
- Quantify achievements: Provide examples of how your ML applications improved system performance or supported business functions.
- Prepare for technical questions: Be ready to discuss your experience with Python, TensorFlow, Keras, Scikit-learn, and cloud platforms (AWS, Azure, GCP).
- Demonstrate collaboration: Highlight your ability to work with data scientists, engineers, and architects on complex projects.
Technical preparation
Master data structures and algorithms.,Practice Python and ML libraries.,Build MLOps pipelines.,Familiarize with cloud ML services.
Behavioral questions
Describe a complex ML project you led.,How do you handle conflicting team priorities?,Explain a time you improved system performance.,How do you communicate technical concepts clearly?
Frequently asked questions
- What are the primary responsibilities of a Machine Learning Engineer at MANTECH?
- The Machine Learning Engineer at MANTECH will primarily be responsible for supporting scalable machine learning applications, including pipelines and services. This involves collaborating with data scientists to design tools, train models, implement the full MLOps lifecycle, develop and test ML applications, explore data for insights, and deploy cloud-based ML services.
- What educational background is required for the Machine Learning Engineer role at MANTECH?
- A Master’s degree in Applied Mathematics, Statistics, Computer Science, or a related field is the minimum educational requirement for this Machine Learning Engineer position at MANTECH.
- What programming languages and libraries are essential for this Machine Learning Engineer position?
- Proficiency in programming languages such as Python, Java, or R is essential. Core libraries like TensorFlow, Keras, and Scikit-learn are also critical for training and embedding machine learning models into applications.
- Does MANTECH require specific cloud platform experience for Machine Learning Engineers?
- Yes, experience managing and deploying cloud-based ML services across major cloud computing environments like AWS, Azure, or Google Cloud Platform (GCP) is required for this Machine Learning Engineer role at MANTECH.
- What is the clearance requirement for this Machine Learning Engineer job?
- An active Secret clearance is a mandatory requirement for this Machine Learning Engineer position at MANTECH.
- What type of development methodology does MANTECH follow for Machine Learning Engineers?
- MANTECH follows Agile methodologies to ensure the delivery of production-ready, highly testable code in small, efficient, and continuous iterations for its Machine Learning Engineer roles.
- What kind of documentation experience is needed for the Machine Learning Engineer role?
- Experience in creating, maintaining, and communicating complex technical documentation for machine learning systems is a minimum qualification for the Machine Learning Engineer position at MANTECH.
- How important is data exploration and visualization for this Machine Learning Engineer role?
- Exploring and visualizing data is crucial for the Machine Learning Engineer role at MANTECH. It helps in uncovering key insights and identifying specific factors that impact model accuracy and performance.