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Internship Machine Learning Engineer Jobs in Maryland

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Internship Machine Learning Engineer information

What does an internship machine learning engineer do?

An Internship Machine Learning Engineer works alongside experienced engineers to help develop, test, and deploy machine learning models. Their responsibilities may include cleaning and preparing data, writing code for model training, evaluating model performance, and contributing to research tasks. Interns often learn to use popular frameworks such as TensorFlow or PyTorch and gain hands-on experience with real-world datasets. This role is designed to help students or recent graduates apply their academic knowledge to practical problems while developing industry-relevant skills.

What types of projects and responsibilities can I expect as an internship machine learning engineer?

As an Internship Machine Learning Engineer, you will typically support the development, testing, and deployment of machine learning models under the guidance of senior engineers. Your responsibilities may include data preprocessing, exploratory data analysis, implementing algorithms, and evaluating model performance. You'll often collaborate closely with data scientists, software engineers, and product managers, gaining exposure to real-world workflows and tools. This hands-on experience is invaluable for building technical skills and understanding how machine learning solutions are integrated into larger products.

What are the key skills and qualifications needed to thrive as an internship machine learning engineer, and why are they important?

To excel as an Internship Machine Learning Engineer, you typically need a solid background in mathematics, programming (especially Python), and foundational machine learning concepts, often supported by coursework or relevant project experience. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is common, along with proficiency in data processing libraries. Curiosity, strong problem-solving abilities, and effective teamwork and communication skills help set candidates apart. These competencies ensure you can contribute meaningfully to projects, adapt to new challenges, and collaborate productively in a rapidly evolving technical environment.

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

AspectInternship Machine Learning EngineerData Scientist Intern
Required CredentialsBasic programming, introductory ML knowledgeStatistics, data analysis, programming
Work EnvironmentDeveloping ML models, coding, testingData analysis, visualization, reporting
Employer & Industry UsageTech companies, startups, AI firmsTech, finance, healthcare, consulting

Internship Machine Learning Engineers focus on developing and testing machine learning models, often requiring programming and basic ML knowledge. Data Scientist Interns analyze data, create visualizations, and generate insights. Both roles are common in tech and data-driven industries, but ML Engineer internships emphasize model deployment, while Data Science internships focus on data analysis and reporting.

What are the most commonly searched types of Machine Learning Engineer jobs in Maryland?

The most popular types of Machine Learning Engineer jobs in Maryland are:

What cities in Maryland are hiring for Internship Machine Learning Engineer jobs?

Cities in Maryland with the most Internship Machine Learning Engineer job openings:

Machine Learning Engineer/Scientist

Precise Systems

Edgewood, MD • On-site

Full-time

Medical, Life, Retirement

Re-posted 11 days ago


Job description


Precise Systems delivers integrated, mission-ready solutions that advance warfighter readiness and strengthen our nation's most critical defense programs. Through the power of our combined capabilities, we provide deep expertise in Advanced Engineering; Digital Transformation; Electromagnetic Warfare; Interactive Training & Simulation; Physical Sciences Research; Platform Lifecycle Support; and Foreign Military Sales. Unified by decades of trusted performance and expanded through strategic growth, our team applies innovative technologies, engineering rigor, and customer-focused execution to solve complex challenges and accelerate mission success. Guided by our commitment to partnership, precision, and performance, we deliver the scalable solutions and technical excellence our customers depend on-today and into the future.
We are seeking a Machine Learning Engineer or Scientist with experience in the physical sciences to support innovative chemical and biological defense projects that integrate automation, and physical science principles. The selected candidate will apply their academic and practical knowledge, experience, and expertise in chemical & biological research and perform data analytics using data science principles. The role involves integrating predictive performance metrics into laboratory processes using pythonic dashboards, adapting metrics and models to project needs, developing pipelines for chemical or biological data, and executing them in laboratory settings to achieve desired outcomes.
This role requires in-person support.
Duties:
  • Under the guidance of senior professionals, the individual will perform tasks encompassing research, development, testing, and evaluation of machine learning models towards chemical and biological datasets. The candidate will contribute to advancing chemical and biological research and development that drives innovation to out-pace emerging threats while simultaneously providing modern solutions
  • Collaborate with interdisciplinary teams to develop machine learning solutions for biological/chemical challenges.
  • Develop and apply state-of-the-art machine learning (ML) tools and algorithms to optimize DoD research efforts.
  • Perform internal verification and validation of models and code to ensure deployments for real laboratory use.
  • Develop and implement dashboards or other graphical user interfaces for automation for laboratory experimentation.
  • Analyze biological or chemical data using languages such as Python and R to derive mathematical insights and improve system performance.
  • Employ DevSecOPs and MLOps to integrate machine learning processes into secure data pipelines.
  • Collaborate with academic and industry partners to test and refine algorithms and biological systems in diverse environments.
  • Perform research to keep models and analysis up to date with the latest advancements.

Required Education:
  • Master's degree in Computer Science, Computer Engineering, Computational Biology, Bioinformatics
  • OR Bachelor's degree in a relevant field with 5 years of experience in a laboratory and/or computational environment.

Preferred Education:
  • Ph.D. in Computational Biology/Chemistry, Machine Learning, Physical Sciences, or a related field with 1 year of experience in a laboratory and/or computational environment.

Required Experience:
  • 3 years of experience in a laboratory and/or computational environment.
  • Hands-on experience applying machine learning algorithms and data science techniques to physical science problems.
  • Proficiency in Python and other programming languages commonly used in machine learning and data analysis.
  • Familiarity with physical science and laboratory experience.
  • Proficiency with software development approaches such as agile, git, DevSecOps, and/or MLOps.
  • Advanced communication skills for interacting with interdisciplinary teams, government representatives, and industry partners.
  • Willingness to learn new technologies and take on new challenges.
  • Strong written and oral communication skills, excellent interpersonal skills, and proficiency in PC software packages for data analysis and visualization.

Preferred Experience:
  • Expertise in advanced machine learning frameworks (e.g., TensorFlow, PyTorch) and their application to biological data.
  • Experience with bioinformatics tools and databases.
  • Experience performing wet laboratory experimentation to validate software and models.
  • Knowledge of automation systems and robotics for laboratory workflows.
  • Collaboration with academic and industry partners on synthetic biology and machine learning projects.

Must be able to obtain and maintain a Secret security clearance. Due to the sensitivity of customer related requirements, U.S. Citizenship is required.
Precise Systems values employee contributions, promotes diverse opportunities for professional growth, and prioritizes overall well-being. Our comprehensive professional services benefits package includes health insurance, life and accidental death and dismemberment coverage, disability insurance, retirement plans, holiday pay, employee-managed leave, and professional growth opportunities.
We recognize exceptional performance and alignment with our core values through our STAR Award recognition program.
Compensation at Precise Systems is determined by various factors, including education, experience, skills, competencies, and contract-specific requirements. The salary range for this position is $76,709.46 - $115,064.18 (annualized USD). This range represents the standard pay for this role and is just one component of Precise Systems' total compensation package.
Precise Systems is committed to fair and equitable pay practices in alignment with applicable pay transparency laws and equal employment opportunity standards.
Precise Systems is dedicated to a shared vision and core values of Integrity, Respect, and Responsibility, which foster innovation and drive our continued success in the global marketplace. Precise Systems and its subsidiaries are Equal Opportunity /Affirmative Action Employers. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, protected veteran status, status as an individual with a disability, or any legally protected status under federal, state, or local law. Visit www.GoPrecise.com for a listing of current openings and our comprehensive, employee friendly benefits summary. Precise Systems participates in E-Verify.