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Internship Machine Learning Quant Jobs (NOW HIRING)

... closely related quantitative field. * This is a hybrid role in Herndon, VA and no relocation ... internships, or real-world projects involving applied machine learning. #LI-WA1 #LI-HYBRID ...

About the Role As a Machine Learning Engineer at Shipwell, you'll play a pivotal role in building ... Bachelor's Degree in a quantitative field such as Physics, Engineering, Computer Science, or ...

This job will validate and develop machine learning models and algorithms to solve complex problems ... Conduct quantitative and qualitative model validation according to Model Risk Management Policy to ...

About the Role At Poesis, machine learning and artificial intelligence open the door to improved ... Familiarity with quantitative investing, portfolio construction, or risk management * Experience ...

This job will validate and develop machine learning models and algorithms to solve complex problems ... Conduct quantitative and qualitative model validation according to Model Risk Management Policy to ...

This job will validate and develop machine learning models and algorithms to solve complex problems ... Conduct quantitative and qualitative model validation according to Model Risk Management Policy to ...

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Machine Learning * Factor Models Mock Interviews Conduct realistic mock interviews including ... Internship recruiting * Full-time recruiting * Networking strategy * Referral strategy * Recruiting ...

Be Seen First

Machine Learning * Factor Models Mock Interviews Conduct realistic mock interviews including ... Internship recruiting * Full-time recruiting * Networking strategy * Referral strategy * Recruiting ...

Machine Learning Engineer

Irving, TX · On-site +1

$96K - $144K/yr

... internship, or thesis in each of the following: Java, Python, or Node.js; NLP (Scikit-Learn ... Quantitative analysis techniques, including clustering, regression, and pattern recognition;

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Internship Machine Learning Quant information

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$25.5K

$42.6K

$88K

How much do internship machine learning quant jobs pay per year?

As of Jul 11, 2026, the average yearly pay for internship machine learning quant in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is the difference between Internship Machine Learning Quant vs Data Scientist Intern?

AspectInternship Machine Learning QuantData Scientist Intern
Required CredentialsStrong programming skills, basic finance knowledge, coursework in machine learningStatistics, programming, domain knowledge, coursework in data analysis
Work EnvironmentFinancial firms, hedge funds, quantitative trading teamsTech companies, startups, research labs
Industry UsageFinance, trading, quantitative researchTechnology, marketing, healthcare analytics
Common Search IntentInternship roles in finance with machine learning focusInternship roles in data science across industries

Internship Machine Learning Quant roles typically focus on applying machine learning techniques to financial data within trading and investment firms. Data Scientist Intern positions are broader, spanning various industries like tech and healthcare, emphasizing data analysis and modeling. While both require programming and analytical skills, the finance-specific knowledge is more critical for Machine Learning Quant internships.

More about Internship Machine Learning Quant jobs
What cities are hiring for Internship Machine Learning Quant jobs? Cities with the most Internship Machine Learning Quant job openings:
What are the most commonly searched types of Machine Learning Quant jobs? The most popular types of Machine Learning Quant jobs are:
What states have the most Internship Machine Learning Quant jobs? States with the most job openings for Internship Machine Learning Quant jobs include:
Infographic showing various Internship Machine Learning Quant job openings in the United States as of July 2026, with employment types broken down into 9% Internship, 1% As Needed, 68% Full Time, 20% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Machine Learning Engineer

Machine Learning Engineer

Ametek

Herndon, VA • On-site

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.


AMETEK rating

7.6

Company rating: 7.6 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

68th of 142 rated electronics manufacturers


Job description

We are seeking an early-career Machine Learning Engineer who is excited to grow rapidly by building and deploying production-grade ML systems. The ideal candidate has a strong engineering mindset, has contributed to shipping ML features or products end-to-end, and is eager to take ownership across the full lifecycle-from data pipelines to model design to deployment, monitoring, and iteration in real-world environments.
This role offers hands-on 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 cross-functional partners including product, data engineering, DevOps & QA to deliver end-to-end 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 hands-on 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 Scikit-learn.
  • 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 fine-tuning, embeddings pipelines, and retrieval-augmented 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 hands-on coursework, research, internships, or real-world projects involving applied machine learning.

#LI-WA1
#LI-HYBRID
Compensation
Employee Type: Salaried
Currency: USD
Salary Minimum: 130,000
Salary Maximum: 155,000
Incentive: No
Disclaimer: Where a specific pay range is noted, it is a good faith estimate at the time of this posting. The actual salary offered will be based on experience, skills, qualifications, market / business considerations, and geographic location.
For more information on AMETEK's competitive benefits, please click here.
AMETEK, Inc. is a leading global provider of industrial technology solutions serving a diverse set of attractive niche markets with annual sales over $7.5 billion.
AMETEK is committed to making a safer, sustainable, and more productive world a reality. We use differentiated technology solutions to solve our customers' most complex challenges. We employ 22,000 colleagues, in 35 countries, that are grounded by our core values: Ethics and Integrity, Respect for the Individual, Inclusion, Teamwork, and Social Responsibility. AMETEK is a component of the S&P 500. Visit https://www.ametek.com/careers for more information.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class. Individuals who need a reasonable accommodation because of a disability for any part of the employment process should call 1 (866) 263-8359.

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