Machine Learning Engineer

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