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Machine Learning Co Op Jobs in Virginia (NOW HIRING)

Turner Construction

Summer 2026 Intern - VA/DC

Reston, VA · On-site

$15.75 - $20.75/hr

Where applicable, your assignment will support learning that applies to earning educational credits. Essential Duties & Key Responsibilities:Depending on business need and location, the Intern/Co-Op ...

LanceSoft Inc

Process Engineer II

Elkton, VA

... Learning new processes and procedures Recommending, creating, writing process control and ... Experience working in a cGMP environment Work, co-op, or internship experience in industry ...

Turner Construction

Summer 2026 Intern - VA/DC

Reston, VA · On-site

$15.50 - $20.75/hr

Where applicable, your assignment will support learning that applies to earning educational credits. Essential Duties & Key Responsibilities:Depending on business need and location, the Intern/Co-Op ...

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How much do machine learning co op jobs pay per hour?

As of Jun 18, 2026, the average hourly pay for machine learning co op in Virginia is $22.16, according to ZipRecruiter salary data. Most workers in this role earn between $14.04 and $25.72 per hour, depending on experience, location, and employer.

What is the difference between Machine Learning Co Op vs Data Scientist?

AspectMachine Learning Co OpData Scientist
Required CredentialsTypically pursuing a degree in CS, Data Science, or related fields; internships often preferredUsually holds a bachelor's or master's in Data Science, Statistics, or related fields; advanced certifications beneficial
Work EnvironmentInternship setting, often part-time or seasonal, in tech or research companiesFull-time role in various industries, including tech, finance, healthcare, with collaborative teams
Employer & Industry UsageUsed by companies for training and evaluating potential future employees; common in tech and research sectorsHired for analyzing data, building models, and deriving insights; prevalent across multiple industries

While both roles involve working with data and algorithms, a Machine Learning Co Op is typically an internship aimed at gaining experience, whereas a Data Scientist is a full-time professional responsible for developing and deploying data models. The Co Op provides a stepping stone into the field, often leading to a full-time Data Scientist position.

What types of projects do Machine Learning Co-Op students typically work on, and how do they contribute to the team?

Machine Learning Co-Op students often work on a variety of hands-on projects, such as developing data preprocessing pipelines, training and evaluating machine learning models, or supporting ongoing research initiatives. They commonly collaborate with data scientists, engineers, and other interns, contributing fresh perspectives and technical support. Co-Ops may also participate in code reviews, attend team meetings, and present their findings, making them valuable contributors to both experimental and production-level work. This collaborative environment offers plenty of opportunities to learn from experienced professionals while making a real impact on projects.

Which 3 jobs will survive AI?

Machine Learning Co-ops are likely to find that roles requiring complex problem-solving, creativity, and emotional intelligence—such as data scientists, AI ethics specialists, and human-centered design professionals—will persist alongside AI advancements. These jobs involve tasks that are difficult for AI to fully replicate and often require interdisciplinary skills and critical thinking.

Which 5 jobs will survive AI?

Machine Learning Co-ops are likely to continue working in roles that require complex problem-solving, creativity, and human judgment, such as data analysis, AI system development, and research. Jobs that involve interpersonal skills, strategic decision-making, and tasks requiring emotional intelligence are also less susceptible to automation. Skills in critical thinking, domain expertise, and adaptability will help professionals remain relevant as AI advances.

Is ML a high paying job?

Machine Learning Co-ops are typically paid internships that offer competitive hourly wages or stipends, which can vary based on location, education level, and company size. Entry-level roles in machine learning often have higher starting salaries compared to many other tech internships, and full-time positions in the field tend to have above-average salaries due to the specialized skills required, such as programming in Python and experience with frameworks like TensorFlow or PyTorch.

What is a Machine Learning Co-Op?

A Machine Learning Co-Op is a temporary, paid position that allows students or recent graduates to gain hands-on experience working with machine learning technologies in a professional setting. Co-ops typically last several months and are designed to provide practical exposure to real-world projects, such as building models, analyzing data, and collaborating with data scientists or engineers. This role helps participants develop technical skills, gain industry insights, and build a professional network, which can be valuable for future career opportunities in the field of artificial intelligence or data science.

What are the key skills and qualifications needed to thrive as a Machine Learning Co Op, and why are they important?

To thrive as a Machine Learning Co Op, you need strong programming skills (especially in Python), a solid foundation in mathematics and statistics, and coursework or experience in data science or machine learning. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is typically expected. Excellent problem-solving abilities, eagerness to learn, and effective communication help set you apart in collaborative and fast-paced environments. These skills and qualities are crucial for successfully contributing to real-world projects and advancing your expertise in the field.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or executive positions, often requiring advanced skills, extensive experience, and sometimes equity or bonuses. These roles are usually found in large tech companies or specialized AI firms and may involve leadership, strategic planning, and cutting-edge research.
What are the most commonly searched types of Machine Learning jobs in Virginia? The most popular types of Machine Learning jobs in Virginia are:
What cities in Virginia are hiring for Machine Learning Co Op jobs? Cities in Virginia with the most Machine Learning Co Op job openings:
Machine Learning Co Op jobs near you

Artificial Intelligence/ Machine Learning Developer

UNISSANT

Ashburn, VA • On-site

Full-time

Posted 9 days ago

Job description

Unissant, Inc. delivers innovative capabilities to the agencies that keep our nation healthy and safe. We apply our domain expertise, data acumen, and technology know-how to achieve breakthrough results for our clients. Working collaboratively, we advance missions and careers through a focus on honesty, integrity, and dependability. We continuously look for talent excited to join that effort. To learn more about our exciting organization, please visit us at www.unissant.com.

We are seeking an Artificial Intelligence/Machine Learning Developer to join our team and support our federal customer.

Qualified applicants may be subject to a security investigation and must meet minimum qualifications for access to classified information. This is a highly technical position; individuals will be screened by peers in a technical review of skills and experience.

Essential Duties and Responsibilities:

Drive a big data approach to execute government requirements to manage and enrich data to gather new insights. As the AI/ML developer, an ideal candidate will be part of a team to provide consultative, architectural, program, and engineering support for a federal customer.

  • This is a client-facing position working on-site as per the requirements established by the DHS customer.
  • Develop, train, and deploy advanced AI/ML and Gen-AI models.
  • Design and implement innovative AI solutions to address complex business challenges using techniques such as natural language processing and large language models.
  • Optimize model performance, ensuring accuracy, efficiency, and scalability.
  • Develop and maintain user-friendly AI applications and interfaces, including chatbots, virtual assistants, and generative content tools.
  • Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows.
  • Stay up to date with the latest advancements in AI/ML and emerging technologies, such as generative AI and reinforcement learning.
  • Conduct research and experiments to explore new AI techniques and applications, including prompt engineering, Advanced RAGs and fine-tuning LLMs.
  • Ensure compliance with data privacy and security regulations, especially when dealing with sensitive data and generative AI outputs.
  • This role will be responsible for briefing the benefits and constraints of technology solutions to technology partners, stakeholders, team members, and senior levels of management.

Work Experience and Job Skills:

  • 3+ years of experience in the Information Technology field focusing on AI/ML engineering projects, MLOps and DevSecOps and technical architecture specifically.
  • Proficiency in developing, deploying, and fine-tuning generative AI models, including large language models (LLMs).
  • Strong proficiency in programming languages such as Python, R, Java and C/C++ (optional)
  • Experience with machine learning and generative AI frameworks.
  • Experience with natural language processing techniques (e.g., text classification, language generation).
  • Solid understanding of any of the cloud platforms (e.g., AWS, Azure, GCP) and deployment strategies.
  • Solid understanding of MLOps and DevSecOps practices for deploying AI-ML models and applications
  • Proficiency in any front-end development technologies (e.g., React, Angular, Vue.js, HTML, CSS, JavaScript).
  • Knowledge of database systems (e.g., SQL, NoSQL, Vector Database, Graph Database)and data warehousing concepts.
  • An understanding and competency surrounding data storage, accesses, and loading.
    • Databases: PostgreSQL, NoSQL, Vector Databases, Graph Databases etc.
    • ETL/ELT Concepts
    • Data warehouse concepts
    • SQL
  • Competency in data exploration, analytics, and feature engineering. (Python Specific)
    • Pandas / NumPy / Polars / PySpark
    • Plotly / Matplotlib (some form of data visualization)
    • Data encoding / normalizing / regularizing / etc.
  • Understanding of Deep learning concepts and architectures like CNNs, RNNs, LSTM, and GANs and ability to apply to real world data sets and problems.
  • Proficiency in ML Modeling - Scikit-Learn, Tensorflow, Keras, Pytorch.
  • Proficiency in NLP Tools SpaCy, ThinC, Gensim.
  • Knowledge of Gen-AI Tools Hugging Face models, OpenAI models, Grok.
  • General competency in various ML disciplines like Classification, Forecasting, Transformers, Generative, Anomaly Detection and Deep Learning.
  • Enthusiastic, proactive, positive attitude with great listening skills, high integrity, and the ability to work effectively in a team environment.
  • Adaptability to changing priorities and a willingness to learn and grow are essential.
  • Excellent organizational skills, and ability to effectively manage concurrent projects.
  • Comprehensive problem-solving skills with exceptional attention to detail.
  • Ability to learn, evolve, think creatively and proactively.
  • Able to work under pressure (at times) and to be extremely flexible with changing priorities
  • Ability to work independently and in a team setting, take ownership of and complete relatively complex tasks, effectively using available resources, as needed, with minimal guidance.

Education:

  • Bachelor's Degree in Computer Science, Information Technology Management or Engineering is preferred. Alternative work-related experience, Military Duty, and/or specialized or higher education may be substituted.

Certificates, Licenses and Registrations:

  • This federal program requires the candidates to be a United States Citizen.
  • Must have an active DHS clearance.
  • Any related systems engineering, or related technical certifications are desired.
  • AWS/Azure/GCP AI/ML certifications are preferred but not required.

Communication Skills:

  • Must have excellent written and verbal communication skills
  • Ability to convey technical information to non-technical individuals.
  • Demonstrated experience communicating effectively across internal and external organizations.
  • Must work well in a matrixed team environment.

Travel:

  • On-site in Ashburn, VA

Environmental Requirements:

  • Mainly sedentary; in an office environment
  • May be required to lift up to ten (10) pounds
  • Flexible in working extended hours

The above statements are intended to describe the general nature and level of work being performed by the individual(s) assigned to this position. They are not intended to be an exhaustive list of all duties, responsibilities, and skills required. Unissant management reserves the right to modify, add, or remove duties and to assign other duties as necessary. In addition, where applicable and available, reasonable accommodation(s) may be made to enable individuals with disabilities to perform essential functions of this position.

Please note: Candidate(s) will be required to go through pre-employment screening.

Unissant, Inc. is a proud Equal Opportunity Employer! (EOE; M/F/Disability/Vets)

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