Machine Learning (ML) Engineer

KDA Consulting is a Disabled Veteran, Woman-Owned, Certified Disadvantaged Small Business, comprised of a diverse team of professionals driven to tackle the demanding National Defense and Intelligence challenges through IT solutions. We emphasize teamwork and focus on achieving goals to complete deliverables efficiently, on-time, and under budget.

We are currently seeking a Machine Learning Engineer to join our team to support our Government Partner.

Requirements

Primary Job Duties and Required Work Experience:

• Model Development and Deployment: Design, develop, and deploy machine learning models, ensuring they meet performance requirements and can be integrated into production systems.
• Collaborate with Data Scientists: Work closely with data scientists to turn research models into scalable, reliable solutions for real-time applications.
• Data Pipeline Optimization: Collaborate with data engineers to ensure data pipelines are optimized for the needs of ML models, including data pre-processing and feature engineering.
• Automate ML Processes: Implement automated systems for model training, evaluation, and deployment using tools such as Kubeflow, Airflow, or MLflow.
• Model Monitoring and Tuning: Continuously monitor model performance and retrain models as needed to ensure they stay accurate and relevant in production environments.
• Infrastructure Integration: Work closely with cloud and DevOps teams to ensure ML systems are effectively integrated within cloud infrastructure (AWS, Azure, GCP) and align with security and compliance requirements.
• Experimentation and Testing: Conduct A/B testing, model validation, and optimization techniques to ensure models perform effectively across different environments and datasets.
• Stay Current with Advances in ML: Stay updated on the latest developments in machine learning, deep learning, and AI technologies to enhance system performance.

Desired Skills:

• ML/DL Frameworks Expertise: Proficiency with machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn, and experience with deploying models in cloud environments (AWS SageMaker, GCP AI Platform, etc.).
• Programming Languages: Strong skills in Python and R, with knowledge of libraries like NumPy, Pandas, and Matplotlib for data analysis and visualization.
• Data Engineering & Feature Engineering: Experience working with data lakes, big data processing (e.g., Spark, Databricks), and ensuring data pipelines meet the needs of machine learning algorithms.
• Model Lifecycle Management: Hands-on experience with tools that facilitate model training, versioning, deployment, and monitoring, such as MLflow, Kubeflow, or Airflow.
• Cloud Integration: Familiarity with cloud platforms like AWS, Azure, and GCP, with specific knowledge of cloud-based ML services, storage, and security best practices.
• DevOps/ML Ops Practices: Experience implementing CI/CD pipelines for machine learning models and automating workflows to improve collaboration between data scientists and engineers.
• Statistical and Analytical Expertise: Deep understanding of statistical analysis, algorithms, and machine learning techniques (e.g., supervised/unsupervised learning, reinforcement learning, and neural networks).
• Security and Compliance: Understanding of data privacy laws and best practices for securing sensitive data in ML workflows.

Job Requirements

• Active TS/SCI + Full Scope Poly U.S. Government Security is required.

• Education and Years of Experience Requirement: candidate must possess a minimum of 11 years' relevant work experience plus a bachelor’s degree -OR- 9 years’ relevant work experience and a master’s degree.

• Ability to maintain discretion and confidentiality.

• Strong interpersonal skills, especially the ability to network and establish professional relationships.

• Ability to prioritize, demonstrated strong organizational skills, and ability to meet or exceed deadlines.

Physical Demands: Position will require frequent sitting, standing, and/or mobility within an office setting. Employee must be able to use hands to complete work at a workstation/computer, be able to reach, type and manipulate with hands, fingers, and arms; lift and/or move up to 20 pounds; talk, see and hear.

Work Environment: Work is performed on client site in a professional office environment with moderate stress and noise levels. Position requires employee to effectively use a computer, potentially for long periods of time, and to accommodate potentially frequent interruptions. Candidate should be both customer-focused and present a team approach to overall work.

Schedule: Business core hours are Monday through Friday, 0930AM -1430PM.

Standard work hours may vary for this position based upon contract requirements. Position will be located onsite at a customer facility in Herndon, VA.

Americans with Disabilities Act (ADA): KDA is committed to the full inclusion of all qualified individuals. As part of this commitment, KDA will ensure that persons with disabilities are provided reasonable accommodations in the hiring process. We encourage qualified individuals with disabilities to apply. If a reasonable accommodation is needed to participate in the job application or interview process or to perform essential job functions, please contact our hiring team by email [email protected]. For persons who are deaf, hard of hearing, deafblind, or deaf-disabled, KDA will provide an American Sign Language (ASL) interpreter where needed as a reasonable accommodation for the hiring processes.

EEOC: KDA is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.