Velocity-X is seeking a Machine Learning (ML) Engineer to design, develop, and implement machine learning models and algorithms to solve specific business problems for the defense and intelligence communities.
Requirements
- 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.
- Experience with MLOps practices and tools for automating and monitoring machine learning workflows.
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.
- 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.
Other
- Highly motivated and self-directed professional
- Collaborate closely with data scientists, software engineers, and product managers to understand requirements and translate them into practical ML solutions.
- 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.
- TS/SCI with Full-Scope Polygraph
