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Machine Learning Research Intern Jobs in Laurel, MD

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Machine Learning Research Intern information

See Laurel, MD salary details

$25.3K

$42.2K

$87.2K

How much do machine learning research intern jobs pay per year?

As of Aug 17, 2026, the average yearly pay for machine learning research intern in Laurel, MD is $42,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,600.00 per year, depending on experience, location, and employer.

What does a machine learning research intern do?

A Machine Learning Research Intern assists in the development, implementation, and evaluation of machine learning models and algorithms under the supervision of experienced researchers. They often preprocess data, run experiments, analyze results, and contribute to research papers or technical reports. Interns also stay up to date with the latest advancements in machine learning, participate in team meetings, and sometimes help in coding or optimizing existing models. This role provides hands-on experience in applying theoretical knowledge to real-world problems and prepares interns for careers in AI research or development.

What are the key skills and qualifications needed to thrive as a machine learning research intern?

To thrive as a Machine Learning Research Intern, you need a strong foundation in mathematics, statistics, programming (especially Python), and an understanding of machine learning algorithms, typically supported by ongoing or completed studies in computer science or related fields. Familiarity with technical tools such as TensorFlow, PyTorch, scikit-learn, and experience with data analysis libraries are commonly required. Curiosity, problem-solving ability, and effective communication skills help interns stand out by enabling them to collaborate, share insights, and adapt to new research challenges. These skills ensure interns can contribute meaningfully to research projects, quickly learn new techniques, and effectively communicate their findings.

What are some typical challenges faced by machine learning research interns during their projects?

Machine Learning Research Interns often encounter challenges such as dealing with limited or messy datasets, tuning complex model architectures, and balancing innovative research with practical implementation. Additionally, they may need to quickly familiarize themselves with unfamiliar frameworks or tools and effectively communicate technical findings to both technical and non-technical team members. Successfully navigating these challenges can provide valuable learning experiences and help interns build strong problem-solving skills for future roles.

What job categories do people searching Machine Learning Research Intern jobs in Laurel, MD look for?

The top searched job categories for Machine Learning Research Intern jobs in Laurel, MD are:

What cities near Laurel, MD are hiring for Machine Learning Research Intern jobs?

Cities near Laurel, MD with the most Machine Learning Research Intern job openings:

Machine Learning Research Intern jobs near you

Senior Machine Learning Research Scientist - Frontier Lab

Software Engineering Institute | Carnegie Mellon University

Arlington, VA • On-site

$113K - $144K/yr

Full-time

Re-posted 28 days ago

Job description

Job Summary:
Carnegie Mellon University's Software Engineering Institute is focused on applied artificial intelligence research for government missions. The Senior Machine Learning Research Scientist will lead applied research and prototype development while collaborating across engineering and research domains to enhance AI capabilities for government stakeholders.
Responsibilities:
• Execute work within the operational context—understanding users, workflows, constraints, success criteria, and outcomes—so technical decisions are grounded in real mission needs.
• Lead technical execution by defining technical tasking, sequencing work into realistic milestones, maintaining delivery quality, and delegating appropriately across the team.
• Design and run studies, build convincing prototypes and reference implementations, and produce evidence-backed insights that can be matured and transitioned into operational settings.
• Establish credible evaluation strategies and test pipelines that assess performance, robustness, reliability, and trustworthiness in mission-representative scenarios.
• Serve as the primary technical interface when appropriate; translate mission goals into measurable technical outcomes; communicate progress, decisions, and risks clearly to stakeholders.
• Proactively mentor junior staff and teammates, raising the bar for research rigor, engineering practice, and delivery habits across project teams.
• Maintain strong awareness of frontier developments aligned to the Frontier Lab, share insights with the lab, and help shape research directions and future work selection.
• Manage multiple priorities effectively, sustain steady execution cadence, and resolve blockers with minimal oversight.
• Build a strong research culture through internal talks, reading groups, and workshops; and engage with external AI/ML communities (professional societies, consortiums, working groups, and conferences) to strengthen collaboration pathways and keep the lab connected to emerging practice.
Qualifications:
Required:
• BS in Computer Science, Electrical Engineering, Statistics, or related field with 10 years of relevant experience; OR MS with 8 years of relevant experience; OR PhD with 5 years of relevant experience.
• Deep expertise in one or more Frontier Lab-aligned areas (agentic systems, LLM reliability/evaluation, CV evaluation, robustness/assurance, TEVV pipelines, multimodal learning, edge ML).
• Strong engineering capability – can build and maintain high-quality prototypes, evaluation infrastructure, and repeatable experimentation workflows.
• Strong written and verbal communication skills; able to represent technical work credibly to senior stakeholders.
• Demonstrated ability to lead technical workstreams and coordinate multi-person execution.
• Technical judgment: Makes sound architectural and methodological decisions; balances ambition with mission constraints.
• Customer translation: Converts mission needs into tractable technical plans, measurable success criteria, and credible evaluation evidence.
• Scientific leadership: Maintains rigor; identifies flawed assumptions; improves evaluation quality and research practices.
• Mentorship & influence: Elevates team performance through hands-on guidance and strong technical standards.
• Initiative: Proactively identifies risks/opportunities, proposes new work, and creates alignment without directive management.
• Self-direction and time management: Plans work effectively under ambiguity, maintains execution cadence, and escalates risks early.
• Flexible to travel to SEI offices in Pittsburgh, PA and Washington, DC / Arlington, VA, sponsor sites, conferences, and offsite meetings (~10% travel).
• You must be able and willing to work onsite at an SEI office in Pittsburgh, PA or Arlington, VA 5 days per week.
• You will be subject to a background investigation and must be eligible to obtain and maintain a Department of War security clearance.
Preferred:
• Leading applied research projects resulting in effective prototypes, mission-relevant evaluation outcomes, or transitioned methods.
• Publications at strong venues (e.g., NeurIPS / ICLR / ICML, relevant workshops, MLCON), and/or demonstrable impact through applied research artifacts (benchmarks, evaluation suites, open-source, technical reports).
• Designing and operating TEVV efforts including evaluation pipelines, robustness analysis, calibration/uncertainty work, regression suites, and scenario-based evaluation protocols.
• Building agentic capabilities integrated with tools, data systems, and human workflows (decision support, planning, analytic contexts).
• Experience with secure or operational environments and delivery constraints typical of government settings.
• Experience shaping a technical roadmap or research portfolio aligned to sponsor priorities and lab strategy.
Company:
We conduct cutting-edge research and development that accelerates the transition of technology to the Department of War (DoW), delivering measurable impact in support of the national security mission. Founded in 1984, the company is headquartered in Pittsburgh, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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