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Entry Level Machine Learning Engineer Jobs in Washington, DC

Kepora

Machine Learning Engineer

Herndon, VA · On-site

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

GEICO

Machine Learning Engineer II

Bethesda, MD · On-site

$105K - $215K/yr

Leverage expertise in machine learning, software engineering, and system architecture to independently drive the development of production-ready models. Work closely with cross-functional teams, from ...

Geico

Machine Learning Engineer II

Bethesda, MD · Hybrid

$105K - $215K/yr

Leverage expertise in machine learning, software engineering, and system architecture to independently drive the development of production-ready models. Work closely with cross-functional teams, from ...

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All JobsMachine Learning Engineer JobsEntry Level Machine Learning Engineer JobsEntry Level Machine Learning Engineer Jobs in Washington, DC

Entry Level Machine Learning Engineer information

See Washington, DC salary details

$34K

$78.6K

$133.6K

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

As of Jun 9, 2026, the average yearly pay for entry level machine learning engineer in Washington, DC 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 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 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 most commonly searched types of Machine Learning Engineer jobs in Washington, DC? The most popular types of Machine Learning Engineer jobs in Washington, DC are:
What are popular job titles related to Entry Level Machine Learning Engineer jobs in Washington, DC? For Entry Level Machine Learning Engineer jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning Engineer jobs in Washington, DC look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in Washington, DC are:
Entry Level Machine Learning Engineer jobs near you
Infographic showing various Entry Level Machine Learning Engineer job openings in Washington, DC as of May 2026, with employment types broken down into 52% Full Time, 44% Part Time, 2% Temporary, and 2% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $78,559 per year, or $37.8 per hour.
Machine Learning Engineer - Computer Vision

Machine Learning Engineer - Computer Vision

CaseGuard

Arlington, VA • On-site

Full-time

Posted 28 days ago

Job description

Job Summary:
CaseGuard is a software company that helps law enforcement agencies, federal agencies, hospitals, schools, airports, and others manage all their media redaction needs in one easy-to-use redaction software. They are seeking a highly skilled and motivated Machine Learning Engineer specializing in Computer Vision to develop and deploy machine learning models focused on image and video processing.
Responsibilities:
• Design, develop, and deploy computer vision models for tasks such as object detection, object tracking, video segmentation, and facial recognition.
• Optimize and fine-tune deep learning algorithms for real-time performance.
• Work closely with the software engineers and product teams to identify opportunities for leveraging data.
• Collect, clean, and preprocess large datasets to prepare for model training and evaluation.
• Evaluate and optimize machine learning models for accuracy, performance, and scalability.
• Deploy models into production environments and monitor their performance to ensure reliability.
• Stay up-to-date with the latest advancements in computer vision and artificial intelligence.
• Collaborate with cross-functional teams to integrate machine learning solutions into business processes.
• Document processes, models, and implementations to ensure reproducibility and scalability.
Qualifications:
Required:
• Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Experience in deep learning models, their training, and hyperparameter tuning using libraries such as TensorFlow, PyTorch, and Transformers or other Huggingface tools.
• Experience with data manipulation tools such as Pandas, NumPy, and SQL.
• Strong programming skills in Python and C++.
• Experience in MLOps principles and model deployment and instrumentation on cloud platforms such as AWS, Azure, or Google Cloud for model deployment and knowledge with efficient serving tools such as ONNX, triton, and vllm.
• Proficiency in working with image and video data, including preprocessing and augmentation techniques.
• Strong understanding of machine learning algorithms, including supervised and unsupervised learning and deep learning.
• Strong communication skills and the ability to work collaboratively in a team environment.
Preferred:
• Familiarity with containerization and orchestration tools like Docker and Kubernetes.
• Experience with version control systems such as Git.
• Understanding software engineering best practices, including code review, testing, and documentation.
• Experience with Large Language Models (LLMs) is a great plus.
• Experience with data annotation tools and processes.
Company:
CaseGuard is the world’s leading AI-powered Redaction and Investigation Solution. Founded in , the company is headquartered in Arlington, Virginia, US, , with a team of 51-200 employees. The company is currently Growth Stage.

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