Machine Learning Engineer - Mid Level

Eiden Systems Consulting

$100K — $130K *
Technical Services
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 4-7 years of professional experience in machine learning or data science, with at least 2 years focused on sensor-based or temporal data.
  • B.S. or M.S. in computer science, data science, or applied mathematics.
  • Active Top Secret (TS) clearance required; SCI preferred.
  • Hands-on experience with PyTorch and/or TensorFlow for ML model development and deployment.
  • Strong grasp of machine learning fundamentals, statistics, linear algebra, and probability.
  • Software development experience in Linux/Unix environments.
  • Proficiency in Python and scientific libraries like NumPy.

Responsibilities

  • Design, develop, and optimize ML models for detecting and classifying signals in noisy, high-volume data.
  • Develop and tune deep learning architectures such as CNNs, LSTMs, and Transformers for analyzing temporal data.
  • Apply signal processing techniques to enhance feature extraction and model performance.
  • Build scalable data pipelines for real-time processing of I/Q streams.
  • Evaluate model effectiveness using advanced metrics for imbalanced datasets.
  • Optimize ML models for low-latency execution on edge hardware platforms.
  • Develop modular code with Python, NumPy, and frameworks like PyTorch or TensorFlow.

Benefits

  • Premium health, dental, and vision insurance.
  • 401(k) plan with company match.
  • Life insurance and short- and long-term disability coverage.
  • Support for work-life balance promoting professional and personal well-being.
Full Job Description
ESC is seeking a Mid-Level Machine Learning Engineer to support a mission-focused R&D program developing advanced signal detection and classification capabilities for national security applications. This role focuses on designing, training, and deploying ML models capable of identifying complex signals within high-bandwidth sensors and I/Q data streams. The engineer will work closely with researchers and software engineers to transition prototype algorithms into low-latency, edge-deployed operational systems supporting real-world mission environments.

Responsibilities:
  • Design, develop, and optimize machine learning models for signal detection, classification, and anomaly detection within noisy and high-volume data streams
  • Develop and tune deep learning architectures including CNNs, LSTMs, and Transformer-based models for temporal and sequence-based analysis
  • Apply signal processing techniques such as Fourier and wavelet transforms to support feature extraction and model performance
  • Build scalable data pipelines for real-time I/Q stream processing, including buffering, windowing, normalization, and inference workflows
  • Evaluate model effectiveness using advanced performance metrics including ROC/AUC, precision-recall curves, confusion matrices, and other techniques for imbalanced datasets
  • Optimize machine learning models for low-latency execution on edge and embedded hardware platforms
  • Develop modular, maintainable, and testable code using Python, NumPy, PyTorch and/or TensorFlow
  • Support integration with network-attached sensors, hardware abstraction layers, and real-time data sources
  • Collaborate with software engineers, researchers, and mission stakeholders in an agile R&D environment
  • Participate in code reviews, technical discussions, and continuous improvement efforts using GitLab-based development workflows
  • Support containerized application development and deployment using Docker within Linux/Unix environments

Required Qualifications:
  • Experience: 4-7 years of professional experience in machine learning or data science, with at least 2 years focused on sensor-based or temporal data.
  • Education: B.S. or M.S. in computer science, data science, or applied mathematics.
  • Security clearance: Active Top Secret (TS) clearance required. SCI preferred.
  • Hands-on experience developing and deploying machine learning models using PyTorch and/or TensorFlow
  • Strong understanding of machine learning fundamentals, statistics, linear algebra, and probability
  • Experience developing software in Linux/Unix environments
  • Proficiency in Python and scientific computing libraries such as NumPy
  • Experience with version control and collaborative development workflows
  • Experience working with I/Q data streams and real-time inference pipelines

ESC offers a competitive compensation package that includes premium health, dental, and vision insurance, a 401(k) plan with company match, life insurance, short- and long-term disability coverage, and more. We also prioritize work-life balance, supporting our team in maintaining a healthy blend of professional and personal well-being.

PAY TRANSPARENCY NONDISCRIMINATION PROVISION

Similar Jobs

More Jobs at Eiden Systems Consulting

More Technical Services Jobs

Find similar Machine Learning Engineer - Mid Level jobs: