SR. MACHINE LEARNING ENGINEER - WFHMD - 1530 WITH SECURITY CLEARANCE

Global Infotek - Herndon, VA

Full-time - Mid Level

Remote - Herndon, VA

Professional, Scientific, and Technical Services

About the position

Global InfoTek Inc. (GITI) is seeking a highly skilled and motivated Senior Machine Learning (ML) Engineer to join our dynamic team. This exciting remote telework opportunity involves researching, developing, implementing, and deploying machine learning models and algorithms to tackle a variety of cyber analytical challenges. As a key member of our team, you will collaborate with cross-functional teams to identify opportunities for applying machine learning techniques, collect and preprocess data, design and train models, and deploy solutions into production environments. This role not only offers the chance to work with state-of-the-art technologies but also allows you to make a significant impact in the field of machine learning. In this position, you will be responsible for architecting and integrating ML models, algorithms, tools, and techniques into existing or new environments. You will work closely with data scientists to design, develop, and integrate ML models and algorithms to address specific problems such as classification, regression, clustering, and recommendation systems. Your role will also involve introducing ML and pattern recognition to discover hidden insights, as well as conducting data integrity and validation actions. You will be expected to exercise creativity in applying non-traditional approaches to the analysis of unstructured data, supporting high-value use cases through multi-dimensional visualization. The ideal candidate will possess strong technical and computational skills in engineering, physics, and mathematics, along with the ability to code, design, develop, and deploy sophisticated applications using advanced structured data analysis techniques. You will utilize advanced tools and computational skills to interpret, connect, predict, and make discoveries in complex cyber-security data, delivering actionable recommendations for business and analytic decisions. Additionally, you will recommend and implement interactive reports, visual analytics, and dashboards focused on understanding and utilizing deep packet inspection of structured and unstructured collected digital data. Staying updated on the latest advancements in large data analytics and machine learning research will be crucial, as will identifying opportunities for innovation and improvement.

Responsibilities

• Research, develop, implement, and deploy machine learning models and algorithms to solve cyber analytical challenges.
• Collaborate with cross-functional teams to identify opportunities for applying machine learning techniques.
• Collect and preprocess data for model training and analysis.
• Design and train machine learning models for various applications such as classification, regression, and clustering.
• Architect and implement data processing and ETL algorithms, ensuring data integrity and validation.
• Work with data scientists to integrate ML models and algorithms into existing systems.
• Exercise creativity in analyzing unstructured data and applying multi-dimensional visualization techniques.
• Implement processing on high-volume, high-velocity data streams.
• Utilize advanced tools to interpret and analyze complex cyber-security data.
• Recommend and implement interactive reports and visual analytics for data insights.
• Stay updated on advancements in machine learning and data analytics technologies.

Requirements

• 7-10 years of experience in machine learning, data science, or related fields.
• Experience working with cyber-security data.
• Proficiency in statistical analysis and visualization of complex data.
• Understanding of data hygiene methods via ETL processes.
• Solid understanding of machine learning algorithms and techniques, including supervised and unsupervised learning.
• Hands-on experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Experience with data processing and analysis tools like Python, SQL, and Spark.
• Excellent problem-solving and analytical skills with attention to detail.
• Strong communication and collaboration skills, able to work independently or in a team.

Nice-to-haves

• Experience with Apache Spark, Apache Streaming, and Jupyter Hub.
• Working knowledge of networks and network traffic data.
• Experience with containerization technologies such as Docker and Kubernetes.
• Familiarity with big data technologies like Elastic Search and Apache Hadoop.
• Experience deploying ML models in production environments using containerization.
• Publications or contributions to ML-related research projects or open-source initiatives.

Benefits

• Remote work flexibility
• Opportunities for professional development
• Collaborative work environment
• Access to state-of-the-art technologies