Dark Wolf constructs and deploys data management and analytics solutions for the defense and intelligence communities. We’re proud to boast a world-class engineering team that thrives on rolling up their sleeves to solve your mission’s biggest challenges.

Dark Wolf is seeking a highly motivated and self-directed professional to fill the role of Software Developer/Data Engineer to support our team in Northern Virginia. The candidate will be a member of a software development team supporting cloud based application development.

Required Skills:

• Minimum 15 years of experience in software development
• Experience in Extract, Transform, and Load (ETL) data engineering
• Experience with REST APIs
• Experience with Java
• Experience with full lifecycle agile software development projects
• Desired skills:
• Experience with Python.
• Experience building data products in Apache Avro and/or Parquet
• On-the-job experience with Java software development.
• Experience deploying the complete DevOps Lifecycle including integration of build pipelines, automated deployments, and compliance scanning using test driven development.

 Responsibilities:

• Create APIs to package and disseminate data to mission partners
• Create access control mechanism to access collection data
• Implement standard interfaces, formats and application processes
• Build data models and analytics to support mission needs
• Implement and document RESTful API structures that communicate across data management components to include user interface, data flow, data ingestion, monitoring and dissemination

Position Clearance Requirement:

TS/SCI with Full-Scope Polygraph

Dark Wolf constructs and deploys data management and analytics solutions for the defense and intelligence communities. We’re proud to boast a world-class engineering team that thrives on rolling up their sleeves to solve your mission’s biggest challenges.

Dark Wolf is seeking a highly motivated and self-directed professional to fill the role of DevSecOps Engineer to support our team in Northern Virginia. Infrastructure The DevSecOps Engineer will be responsible for new and existing cloud production and development environments.  Deployment of new tools, infrastructure security, monitoring, auto-scaling, auto-recovery, performance tuning and installation/configuration of open-source applications.

Required Qualifications:

• A degree in Computer Science, Information Systems, Engineering or related or an additional 4 years of experience in lieu of degree
• Minimum 4 years of experience performing systems engineering related work in a multi-disciplinary, fast-paced, matrixed and cross-functional program in a resource intensive environment
• Demonstrated experience engineering and maintaining Continuous Integration deployment solutions using DevOps tools, such as Jenkins, CloudFormation, Nexus, Ansible, etc
• Experience using AWS technologies such as EC2, EBS, AMI, AWSCLI, CloudWatch, etc
• Excellent understanding of software development programming languages (Java, Python, Shell, etc.)
• In-depth knowledge of Linux operation systems

Desired Qualifications:

• AWS certifications
• Understanding of software development programming languages (Java, Python, etc.)
• Experience with Kubernetes and Docker

Position Clearance Requirement:

TS/SCI with Full-Scope Polygraph

Dark Wolf constructs and deploys data management and analytics solutions for the defense and intelligence communities. We’re proud to boast a world-class engineering team that thrives on rolling up their sleeves to solve your mission’s biggest challenges.

Dark Wolf is seeking a highly motivated and self-directed professional to fill the role of Machine Learning (ML) Engineer to support our team in Northern Virginia.

Responsibilities:

• Design, develop, and implement machine learning models and algorithms to solve specific business problems.
• Build and maintain scalable and robust machine learning pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
• Transform machine learning models into deployable APIs and integrate them with existing applications and infrastructure.
• Collaborate closely with data scientists, software engineers, and product managers to understand requirements and translate them into practical ML solutions.
• Experiment with different machine learning techniques and algorithms to identify the most effective approaches for given problems.
• Evaluate model performance using appropriate metrics and iterate on models to improve accuracy, efficiency, and scalability.
• Monitor and maintain deployed models, ensuring their reliability and performance in production environments.
• Troubleshoot and resolve issues related to machine learning models and pipelines.
• Stay up-to-date with the latest advancements in machine learning, deep learning, and related fields.
• Contribute to the development of best practices and standards for machine learning development and deployment within the team.
• Document machine learning models, experiments, and deployment processes.
• Potentially work with large datasets and big data technologies.
• Optimize machine learning models for performance and efficiency.

Qualifications:

• Master’s in computer science, Machine Learning, or higher level degree is preferred with of 3+ years of related industry experience in Machine Learning, Computer Science, Data Science or related fields.
• Demonstrated hands-on experience in developing and deploying machine learning models in a production environment.
• Strong programming skills in Python and experience with relevant machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, scikit-learn, etc.
• Solid understanding of machine learning algorithms (e.g., regression, classification, clusting, dimensionality reduction, deep learning architectures).
• Experience with data preprocessing, feature engineering, and data visualization techniques.
• Familiarity with data storage and processing technologies (e.g., SQL, NoSQL databases, Spark, Hadoop).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and their machine learning services.
• Understanding of software development principles, version control (e.g., Git), and CI/CD pipelines.
• Strong analytical and problem-solving skills with the ability to interpret data and draw meaningful conclusions.
• Excellent communication and collaboration skills to effectively communicate technical concepts to both technical and non-technical audiences. 

Preferred Skills:

• Experience with specific areas of machine learning such as Natural Language Processing (NLP), Computer Vision, or Recommender Systems.
• Experience with MLOps practices and tools for automating and monitoring machine learning workflows.
• Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes.
• Experience with building and deploying RESTful APIs.
• Familiarity with big data technologies and distributed computing.
• Experience with statistical modeling and inference. 

Position Clearance Requirement:

TS/SCI with Full-Scope Polygraph