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Machine Learning Software Engineer Jobs in Washington

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site

Collaborate with a cross-functional team comprising other ML Engineers, Software Engineers, DevSecOps Engineers, and Data Scientists. * Develop machine learning models and pipelines that are integral ...

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site +1

As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning applications and software systems at scale. You'll implement computer vision machine learning applications ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... You will collaborate closely with researchers, software engineers, red teamers, and subject-matter ...

NT Concepts

Machine Learning Engineer

Herndon, VA · On-site +1

As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning applications and software systems at scale. You'll implement computer vision machine learning applications ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... You will collaborate closely with researchers, software engineers, red teamers, and subject-matter ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... You will collaborate closely with researchers, software engineers, red teamers, and subject-matter ...

NT Concepts

Machine Learning Engineer

Herndon, VA · On-site

Collaborate with a cross-functional team comprising other ML Engineers, Software Engineers, DevSecOps Engineers, and Data Scientists. * Develop machine learning models and pipelines that are integral ...

Ametek

Machine Learning Engineer

Herndon, VA · Hybrid

Strong understanding of data structures, algorithms, software engineering fundamentals, and distributed systems concepts. * Bachelor's degree in Computer Science, Machine Learning, Artificial ...

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Machine Learning Software Engineer information

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$71.9K

$167.1K

$232.7K

How much do machine learning software engineer jobs pay per year?

As of Jun 20, 2026, the average yearly pay for machine learning software engineer in Washington is $167,085.00, according to ZipRecruiter salary data. Most workers in this role earn between $135,900.00 and $195,900.00 per year, depending on experience, location, and employer.

What does a Machine Learning Software Engineer do?

A Machine Learning Software Engineer designs, develops, and deploys machine learning models within software applications. They work on data preprocessing, model training, optimization, and integration into production systems. Their role requires expertise in programming (Python, Java, or C++), machine learning frameworks (TensorFlow, PyTorch, or Scikit-learn), and cloud platforms. They collaborate with data scientists and software engineers to build scalable ML solutions.

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

To thrive as a Machine Learning Software Engineer, you need a solid understanding of programming (especially Python), algorithms, data structures, and mathematics, ideally backed by a degree in computer science, engineering, or a related field. Experience with frameworks such as TensorFlow or PyTorch, familiarity with cloud platforms (AWS, Azure, or GCP), and relevant certifications in data science or machine learning are highly valuable. Strong problem-solving skills, effective communication, and the ability to work collaboratively with cross-functional teams set outstanding candidates apart. These competencies are crucial for building deployable, scalable, and maintainable machine learning solutions that address real business challenges.

What are the day-to-day responsibilities of a Machine Learning Software Engineer?

As a Machine Learning Software Engineer, your daily tasks typically include developing and optimizing machine learning models, collaborating with data scientists and product teams to define requirements, and integrating models into production systems. You’ll work extensively with large datasets to preprocess, analyze, and validate data, as well as monitor model performance and iterate on solutions when needed. It's common to participate in code reviews, contribute to architectural decisions, and maintain documentation for reproducibility and knowledge sharing. This role offers a dynamic and intellectually stimulating environment, making it ideal for those who enjoy solving complex technical problems and working at the intersection of engineering and data science.

What are the most commonly searched types of Machine Learning Software Engineer jobs in Washington? The most popular types of Machine Learning Software Engineer jobs in Washington are:
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What job categories do people searching Machine Learning Software Engineer jobs in Washington look for? The top searched job categories for Machine Learning Software Engineer jobs in Washington are:
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Machine Learning Software Engineer jobs near you
Machine Learning Engineer

Machine Learning Engineer

Venture Global LNG

Arlington, VA

Other

Posted 19 days ago

Job description

Venture Global LNG ("Venture Global") is a long-term, low-cost provider of American-produced liquefied natural gas. The company's two Louisiana-based export projects service the global demand for North American natural gas and support the long-term development of clean and reliable North American energy supplies. Using reliable, proven technology in an innovative plant design configuration, Venture Global's modular, mid-scale plant design will replace traditional designs as it allows for the same efficiency and operational reliability at significantly lower capital cost.
The Machine Learning Engineer will design, develop, and maintain the productionization of machine learning, deep learning, generative AI, large language models, simulation, and optimization algorithms. This includes building pipelines for training and deploying deep learning and other machine learning algorithms and enabling models to run efficiently in production. The main data engineering work will be done in Databricks and PySpark.
The ideal candidate will have excellent technical proficiency, excellent communication skills, a self-driven mindset, and the willingness to continuously learn new things.
This position will report to the Director of Business Intelligence and is structured within IT under the Vice President of Applications.
The position will be located in Arlington, VA and will require commuting to the office 5 days a week.
Responsibilities
  • Work with business stakeholders to define project requirements.
  • Orchestrate, scale, setup and improve model serving pipelines.
  • Improve model accuracy through feature engineering, tuning, and observability.
  • Improve model computational performance through all aspects of the pipeline, including tuning clusters/job compute, partitioning, caching, feature engineering code, tuning setup, etc.
  • Integrate machine learning models into production environments, ensuring reliability and scalability.
  • Evaluate pretrained models and software from vendors and support integration into production environments.
  • Develop comprehensive project plans for implementing machine learning and AI projects including solution architectures, resourcing, and dependencies.
  • Provide ETL requirements to data engineers to effectively curate files for data analytics.
  • Work with data scientists, data engineers, and business analysts to translate business requirements into machine learning solutions.
  • Build software solutions that are maintainable, scalable and provide quantifiable business value.
  • Continuously focus on quality architecture, quality code, and ruthless management of technical debt.
  • Continuously push the practice forward, learning and testing newer and better ways of performing work.

Required Qualifications
  • 5 years of machine learning engineering, software engineering, or data science experience.
  • Bachelors in a quantitative field of study.

Preferred Qualifications
  • Masters in a quantitative field of study.
  • Experience with the Azure, AWS, or other cloud ecosystems.
  • Experience in building secure data processing pipelines.
  • Proficient in utilizing data lakes, CI/CD pipelines, Databricks, Unity Catalog, and Git.
  • Experience working with streaming.
  • Expertise in building machine learning solutions using cloud data services.
  • Exceptional skills in data processing languages such as SQL, Python, or Scala.
  • Exceptional skills in feature engineering, model optimization, and parameter tuning.

Venture Global LNG is an Equal Opportunity Employer. We do not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law.
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