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Quant Developer Internship Jobs in Virginia (NOW HIRING)

Ametek

Machine Learning Engineer

Herndon, VA · Hybrid

Work with DevOps team to implement robust MLOps practices, including versioning, CI/CD for ML ... closely related quantitative field. * This is a hybrid role in Herndon, VA and no relocation ...

Ametek

Machine Learning Engineer

Herndon, VA · On-site

Work with DevOps team to implement robust MLOps practices, including versioning, CI/CD for ML ... closely related quantitative field. * This is a hybrid role in Herndon, VA and no relocation ...

Level Up Llc

Data Scientist

Reston, VA · On-site

Engineering * Geospatial Analysis * Mathematics * Operations Research * Quantitative Finance * Statistics * Experience analyzing real world data through coursework, thesis research, internships, or ...

Level Up Llc

Data Scientist

Reston, VA · On-site +1

Engineering * Geospatial Analysis * Mathematics * Operations Research * Quantitative Finance * Statistics * Experience analyzing real world data through coursework, thesis research, internships, or ...

AVIAN, LLC

Data Scientist

Reston, VA · On-site +1

Engineering * Geospatial Analysis * Mathematics * Operations Research * Quantitative Finance * Statistics * Experience analyzing real world data through coursework, thesis research, internships, or ...

ActioNet, Inc.

Pricing Analyst

Vienna, VA · On-site +1

Internship, academic, or early professional experience supporting pricing, finance, contracts ... Engineering, Cloud Solutions, Cyber Security and IT Managed Services. With 26+ years of stellar ...

ActioNet

Pricing Analyst

Vienna, VA · On-site +1

Internship, academic, or early professional experience supporting pricing, finance, contracts ... Engineering, Cloud Solutions, Cyber Security and IT Managed Services. With 26+ years of stellar ...

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Quant Developer Internship information

What is a Quant Developer Internship?

A Quant Developer Internship is a temporary position, usually for students or recent graduates, that offers hands-on experience in quantitative finance and software development. Interns work with quantitative analysts and developers to design, implement, and optimize financial models and trading algorithms. The role typically involves programming, data analysis, and collaborating with other teams to solve real-world financial problems. This internship is an excellent opportunity for those interested in combining finance, mathematics, and computer science in a professional setting.

What is the difference between Quant Developer Internship vs Quant Analyst Internship?

AspectQuant Developer InternshipQuant Analyst Internship
Required CredentialsTypically pursuing or holding a degree in Computer Science, Mathematics, or related fieldsUsually pursuing or holding a degree in Finance, Economics, or related fields
Work EnvironmentHands-on coding, software development, and algorithm implementationData analysis, financial modeling, and strategy development
Employer & Industry UsageUsed in hedge funds, investment banks, and trading firms focusing on technology-driven rolesCommon in asset management firms, hedge funds, and financial institutions focusing on market analysis

While both internships involve finance and quantitative skills, Quant Developer Internships focus more on programming and software development, whereas Quant Analyst Internships emphasize financial analysis and modeling. Candidates should choose based on their strengths in coding versus financial analysis.

What are some common challenges faced during a Quant Developer Internship, and how can interns overcome them?

Quant Developer Interns often encounter challenges such as adapting to complex financial models, working with large datasets, and mastering specialized programming languages like Python or C++. To overcome these, interns should proactively seek guidance from senior team members, participate in regular code reviews, and allocate time to strengthen their understanding of both financial concepts and software development best practices. Collaboration and open communication within the team are crucial for navigating technical obstacles and successfully delivering project tasks.

What are the key skills and qualifications needed to thrive as a Quant Developer Intern, and why are they important?

To thrive as a Quant Developer Intern, you need a strong background in mathematics, statistics, and programming, typically demonstrated through a degree in quantitative fields like computer science, mathematics, or engineering. Familiarity with programming languages such as Python, C++, or Java, and experience using financial modeling tools or libraries are highly valued. Analytical thinking, attention to detail, and effective communication are critical soft skills for collaborating with teams and interpreting complex data. These skills and qualities are essential for developing robust quantitative models and contributing effectively to quantitative research and trading strategies.
What are the most commonly searched types of Quant Developer jobs in Virginia? The most popular types of Quant Developer jobs in Virginia are:
What are popular job titles related to Quant Developer Internship jobs in Virginia? For Quant Developer Internship jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Quant Developer Internship jobs in Virginia look for? The top searched job categories for Quant Developer Internship jobs in Virginia are:
What cities in Virginia are hiring for Quant Developer Internship jobs? Cities in Virginia with the most Quant Developer Internship job openings:
Quant Developer Internship jobs near you
Infographic showing various Quant Developer Internship job openings in Virginia as of May 2026, with employment types broken down into 6% Internship, and 94% Full Time. Highlights an 78% In-person, 11% Hybrid, and 11% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Ametek

Herndon, VA • Hybrid

Other

Posted 2 days ago

AMETEK rating

7.9

Company rating: 7.9 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

52nd of 139 rated electronics manufacturers

Job description

We are seeking an earlycareer Machine Learning Engineer who is excited to grow rapidly by building and deploying productiongrade ML systems. The ideal candidate has a strong engineering mindset, has contributed to shipping ML features or products endtoend, and is eager to take ownership across the full lifecycle-from data pipelines to model design to deployment, monitoring, and iteration in realworld environments.

This role offers handson exposure to applied ML, working with IoT datasets, user needs, and product requirements to build scalable solutions that deliver measurable customer ROI.

Responsibilities:

  • Design, build, and deploy ML models into production environments, ensuring reliability, scalability, and performance.
  • Ability to select and apply the appropriate ML approach for a given problem - including supervised learning (e.g., logistic regression, random forest, gradient boosting), unsupervised learning (e.g., clustering, dimensionality reduction), and deep learning techniques when appropriate.
  • Develop and maintain feature engineering pipelines, data preprocessing flows, and training workflows.
  • Collaborate with crossfunctional partners including product, data engineering, DevOps & QA to deliver endtoend ML solutions.
  • Work with DevOps team to implement robust MLOps practices, including versioning, CI/CD for ML, monitoring/alerting, automated retraining, and model governance.
  • Continuously evaluate and improve models by monitoring performance, identifying and addressing bias, detecting data or concept drift, and iterating on features, algorithms, or training processes to maintain reliability over time.
  • Ensure solutions meet security, compliance, and data privacy standards.
  • Document system architectures, modeling decisions, and operational procedures.
  • Work in a high performing scrum team to deliver quality code for stakeholders.

Qualifications - Must Have Skills:

  • 3+ years of professional experience as an ML Engineer, Applied Scientist, or Data Scientist with an emphasis on handson software engineering responsibilities, particularly around productionizing models.
  • Demonstrated contributions to shipping ML models into production-not just prototypes-and supporting their maintenance over time.
  • Proficiency in Python and ML frameworks such as PyTorch and Scikitlearn.
  • Prior hands-on experience with cloud platforms (AWS, Azure, GCP) and ML services (e.g., SageMaker, Vertex AI, Azure ML).
  • Familiarity with GenAI system components and architecture, including vector databases, LLM finetuning, embeddings pipelines, and retrievalaugmented systems (RAG).
  • Experience with MLOps tooling: Docker, Kubernetes, MLflow, Feature Stores, CI/CD pipelines is preferred.
  • Strong understanding of data structures, algorithms, software engineering fundamentals, and distributed systems concepts.
  • Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Engineering, Mathematics, or a closely related quantitative field.
  • This is a hybrid role in Herndon, VA and no relocation assistance is able to be provided.

Other Beneficial Skills:

  • Familiarity with emerging Agentic AI concepts.
  • Familiarity with Edge ML patterns.
  • Experience working with large-scale data pipelines using Spark, Flink, Beam, or similar frameworks.
  • Experience or demonstrated interest in Vision ML, with familiarity in common vision models and techniques for image classification, object detection, and segmentation.
  • Knowledge of observability and monitoring tools for ML systems (Prometheus, Grafana, etc.)
  • Experience with cloud infrastructure and managing resources in the cloud.
  • Master's degree in a relevant field may be considered equivalent to up to 2 years of professional ML engineering experience, particularly when supported by handson coursework, research, internships, or realworld projects involving applied machine learning.

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