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Entry Level Machine Learning Engineer Jobs in Washington

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

Machine Learning Engineer

Arlington, VA · On-site

$110K - $160K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

Machine Learning Engineer III

Centreville, VA · On-site

$129.50K - $183.75K/yr

Worker Type Regular Summary The Machine Learning Engineer III will have the opportunity to interact with R&D Group to develop a variety of innovative computer vision detection, classification ...

Machine Learning Engineer

Arlington, VA · On-site

$90K - $210K/yr

We are seeking a Machine Learning Engineer to join our team at MORSE. You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer ...

The Contractor Team shall evaluate the Sponsor's current Chatbot and Machine Learning (ML ... programming languages. 5. Demonstrated experience implementing, using, and creating data ...

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Entry Level Machine Learning Engineer information

See Washington salary details

$34K

$78.6K

$133.6K

How much do entry level machine learning engineer jobs pay per year?

As of May 28, 2026, the average yearly pay for entry level machine learning engineer in Washington is $78,559.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,300.00 and $88,900.00 per year, depending on experience, location, and employer.

What is an Entry Level Machine Learning Engineer job?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are the key skills and qualifications needed to thrive in the Entry Level Machine Learning Engineer position, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an Entry Level Machine Learning Engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.
What are the most commonly searched types of Machine Learning Engineer jobs in Washington? The most popular types of Machine Learning Engineer jobs in Washington are:
What are popular job titles related to Entry Level Machine Learning Engineer jobs in Washington? For Entry Level Machine Learning Engineer jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning Engineer jobs in Washington look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in Washington are:
What cities in Washington are hiring for Entry Level Machine Learning Engineer jobs? Cities in Washington with the most Entry Level Machine Learning Engineer job openings:
Machine Learning Engineer - Mid Level

Machine Learning Engineer - Mid Level

Eiden Systems Corporation

Sterling, VA

Other

Medical, Dental, Vision, Life, Retirement

Posted 18 days ago


Job description

My Account
Job Openings >> Machine Learning Engineer - Mid Level
Machine Learning Engineer - Mid Level
Summary
Title: Machine Learning Engineer - Mid Level ID: 177 Location: Sterling, VA
More about this 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

Eiden Systems Consulting (ESC) is an equal opportunity employer and is committed to creating an inclusive and respectful workplace. ESC does not discriminate against any employee or applicant based on age, color, disability, gender, national origin, race, religion, sexual orientation, veteran status, or any other classification protected by federal, state, or local law.

In accordance with 41 CFR 60-1.35(c), ESC will not discharge or otherwise discriminate against employees or applicants for discussing, disclosing, or inquiring about their own pay or the pay of another employee or applicant. However, employees who have access to compensation information as part of their essential job functions may not disclose the pay of others to individuals who do not have authorized access-unless such disclosure is made (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or legal action (including those conducted by ESC), or (c) as otherwise required by law.

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