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Quant Engineer Jobs in Virginia (NOW HIRING)

BTree Solutions, Inc.

AI/ML ENGINEER

Reston, VA · On-site

Understanding of quantitative/statistical/ML/AI modeling methodologies. * Experience in ML engineering, including hands-on experience with Generative AI/LLMs. * Experience with developing and ...

TMC Technologies

Senior Software Engineer

King George, VA · On-site

$114K - $150K/yr

Job Title Senior Software Engineer Location King George, VA 22485 US (Primary) Category Engineering ... quantitative terms and able to translate complexity to approximate time and cost to maintain ...

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Quant Engineer information

What engineer makes $500,000 a year?

Quantitative engineers, or quants, working in finance or hedge funds with extensive experience, advanced degrees, and strong programming skills can earn $500,000 or more annually through base salary, bonuses, and profit sharing. Such compensation typically requires expertise in mathematics, programming languages like Python or C++, and a deep understanding of financial markets. These roles are often located in major financial hubs and demand high levels of performance and specialization.

How much do quants get paid?

Quantitative analysts, or quants, typically earn between $100,000 and $200,000 annually at entry to mid-level positions, with senior roles often exceeding $300,000 including bonuses. Compensation varies based on experience, location, firm size, and performance, with many quants also receiving performance-based bonuses and benefits. Strong skills in mathematics, programming, and finance are essential for higher salaries in this field.

What engineers make $300,000 a year?

Senior quantitative engineers, often called quant researchers or quant developers, can earn $300,000 or more annually, especially with experience, advanced degrees, and expertise in programming languages like Python or C++, as well as knowledge of financial markets and risk management. Compensation typically includes base salary, bonuses, and profit sharing, particularly in hedge funds, investment banks, and proprietary trading firms.

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

To thrive as a Quant Engineer, you need strong quantitative and programming skills, typically supported by a degree in mathematics, physics, computer science, or a related field. Proficiency in programming languages such as Python, C++, or Java, as well as familiarity with statistical analysis tools and financial modeling systems, is essential. Analytical thinking, problem-solving abilities, and effective communication distinguish top performers in this role. These skills enable Quant Engineers to develop robust models and algorithms that drive accurate trading strategies and risk management in fast-paced financial environments.

What are Quant Engineers?

Quant Engineers, or quantitative engineers, are professionals who apply mathematical models, statistical techniques, and computer programming to solve complex problems in finance and related industries. They often work on designing trading algorithms, risk management tools, and pricing models for financial instruments. Quant Engineers typically have strong backgrounds in mathematics, computer science, and finance, and are skilled in programming languages such as Python, C++, or R. Their work helps financial firms make data-driven decisions and optimize strategies in highly competitive markets.

Do I need a PhD to be a quant?

A PhD is not strictly required to become a quantitative engineer, but many roles prefer candidates with advanced degrees in fields like mathematics, physics, or engineering. Strong programming skills, proficiency in tools like Python or C++, and solid quantitative knowledge are essential for success in the field.

What is the difference between Quant Engineer vs Quant Analyst?

AspectQuant EngineerQuant Analyst
Required CredentialsDegree in Math, Finance, or Computer Science; often requires programming skillsDegree in Finance, Economics, or Math; less emphasis on programming
Work EnvironmentDevelops models, algorithms, and software tools for trading and risk managementAnalyzes data, interprets models, and provides insights for trading strategies
Employer & Industry UsageFinancial firms, hedge funds, investment banksFinancial firms, asset management, hedge funds

While both roles involve quantitative analysis, Quant Engineers focus on building and implementing models and software, whereas Quant Analysts primarily analyze data and interpret models to inform trading decisions. The roles often overlap but differ in technical depth and responsibilities.

How do Quant Engineers typically collaborate with traders and other team members to develop and implement trading strategies?

Quant Engineers work closely with traders, researchers, and software developers to design, test, and refine quantitative trading models. They often translate mathematical models into efficient code, analyze large datasets, and ensure strategies are both robust and scalable for real-time trading environments. Frequent communication is key, as Quant Engineers must gather requirements from traders, iteratively backtest ideas, and adapt models based on feedback and market changes. This collaborative process helps ensure strategies are both scientifically sound and practically viable for deployment.
What are popular job titles related to Quant Engineer jobs in Virginia? For Quant Engineer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Quant Engineer jobs in Virginia look for? The top searched job categories for Quant Engineer jobs in Virginia are:
What cities in Virginia are hiring for Quant Engineer jobs? Cities in Virginia with the most Quant Engineer job openings:
Quant Engineer jobs near you
AI/ML ENGINEER

AI/ML ENGINEER

BTree Solutions, Inc.

Reston, VA • On-site

Contractor

Posted 3 days ago

Job description

Job Title: AI/ML ENGINEER
Location: Reston,VA
Duration: 12+ Months
Visa: USC, GC, H1B and EAD
Contract Type: W2
We are seeking a highly skilled and motivated AI/ML Engineer to join our team and drive the development and optimization of AI solutions. This role is ideal for someone who thrives at the intersection of machine learning, large language models (LLMs), and cloud infrastructure. You will collaborate closely with business stakeholders to design, build, and refine intelligent systems that leverage cutting-edge technologies.
Key Responsibilities
  • Collaborate with business teams to understand requirements and translate them into ML models and prompt-based solutions.
  • Design, develop, and fine-tune machine learning models, particularly those involving LLMs and generative AI.
  • Optimize and adapt prompt engineering strategies to improve model performance and relevance.
  • Integrate and deploy models using AWS services including Bedrock, S3, ECS, EC2, Lambda and other AI/ML related services.
  • Build and maintain scalable data pipelines and APIs to support ML workflows.
  • Monitor model performance and iterate based on feedback and metrics.
  • Stay current with advancements in AI/ML and cloud technologies to ensure our solutions remain cutting-edge.

Required Qualifications
  • Bachelor's or master's degree in computer science, Data Science, Engineering, or a related field.
  • 3+ years of experience in machine learning, data science, or AI engineering.
  • Hands-on experience with LLMs (e.g., OpenAI, Anthropic, Cohere) and prompt engineering.
  • Strong proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Deep experience with AWS services, especially Bedrock, S3, EC2, and Lambda
  • Familiarity with MLOps practices and tools for model deployment and monitoring.
  • Excellent problem-solving skills and ability to communicate technical concepts to non-technical stakeholders.
  • Strong programming skills in data analytics related languages and libraries, such as Python, R, Pandas, or JavaScript.
  • Experience with AWS SageMaker for model development and model deployment.
  • Understanding of quantitative/statistical/ML/AI modeling methodologies.
  • Experience in ML engineering, including hands-on experience with Generative AI/LLMs.
  • Experience with developing and deploying AI Agents for business problems.

Preferred Qualifications
  • Experience with fine-tuning or customizing foundation models.
  • Knowledge of data privacy and security best practices in cloud environments.
  • Familiarity with containerization (Docker) and container orchestration is a plus.

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