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New Grad Machine Learning Jobs in Pittsburgh, PA

Overview LMI is seeking a Machine Learning Operations Engineer (ML Ops Engineer) to support the ... LMI is a new breed of digital solutions provider dedicated to accelerating government impact with ...

Overview LMI is seeking a Machine Learning Operations Engineer (ML Ops Engineer) to support the ... LMI is a new breed of digital solutions provider dedicated to accelerating government impact with ...

Research Engineer

Pittsburgh, PA · On-site

$100K - $300K/yr

We believe massive scale through data-driven machine learning is the key to unlocking these ... Our team consists of individuals with varying levels of experience and backgrounds, from new ...

Research Engineer

Pittsburgh, PA · On-site

$100K - $300K/yr

We believe massive scale through data-driven machine learning is the key to unlocking these ... Our team consists of individuals with varying levels of experience and backgrounds, from new ...

Associate Data Scientist

Pittsburgh, PA

$57K - $57K/yr

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and ... new technologies that will influence national cybersecurity strategy for decades to come. You will ...

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and ... new technologies that will influence national cybersecurity strategy for decades to come. You will ...

Showing results 41-60

New Grad Machine Learning information

See Pittsburgh, PA salary details

$24.8K

$41.3K

$85.4K

How much do new grad machine learning jobs pay per year?

As of Aug 17, 2026, the average yearly pay for new grad machine learning in Pittsburgh, PA is $41,341.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,600.00 and $44,700.00 per year, depending on experience, location, and employer.

What challenges do new graduates face when starting out in a machine learning role, and how can they overcome them?

New grad machine learning engineers often encounter challenges such as bridging the gap between academic knowledge and practical, production-level projects. Adapting to real-world data issues, collaborating with cross-functional teams, and understanding scalable deployment can be daunting at first. To overcome these, it's helpful to seek mentorship, proactively ask questions, and dedicate time to learning best practices in code versioning, model evaluation, and team communication. Engaging in code reviews and participating in team discussions can also accelerate the learning curve and foster professional growth.

What skills and qualifications are needed to thrive as a new grad machine learning?

To thrive as a New Grad Machine Learning Engineer, you need a solid foundation in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch, version control systems like Git, and coursework or certification in data science are highly beneficial. Strong problem-solving abilities, curiosity, and effective communication skills help you collaborate and convey complex technical concepts to diverse teams. These skills and qualities are essential for developing innovative models, ensuring project success, and integrating seamlessly into fast-paced tech environments.

What is the difference between New Grad Machine Learning vs Data Scientist?

AspectNew Grad Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some internshipsBachelor's or Master's in CS, Statistics, or related; some experience
Work EnvironmentEntry-level, team-focused, research and developmentData analysis, modeling, cross-functional collaboration
Employer & Industry UsageTech companies, startups, research labsTech, finance, healthcare, consulting firms

New Grad Machine Learning roles typically focus on foundational skills, internships, and entry-level tasks, while Data Scientist positions often require more experience in data analysis and statistical modeling. Both roles are common in tech industries, but Data Scientists usually handle broader data analysis responsibilities.

What is a new grad machine learning?

New Grad Machine Learning roles are entry-level positions designed for recent graduates who have studied machine learning, artificial intelligence, data science, or related fields. These positions typically involve working with experienced data scientists and engineers to develop, implement, and improve machine learning models and algorithms. New grads in these roles often contribute to projects involving data preprocessing, model training, evaluation, and deployment. The goal is to help new graduates gain hands-on experience and grow their skills in a real-world setting while contributing to the organization's AI initiatives.

What are popular job titles related to New Grad Machine Learning jobs in Pittsburgh, PA?

For New Grad Machine Learning jobs in Pittsburgh, PA, the most frequently searched job titles are:

What job categories do people searching New Grad Machine Learning jobs in Pittsburgh, PA look for?

The top searched job categories for New Grad Machine Learning jobs in Pittsburgh, PA are:

What cities near Pittsburgh, PA are hiring for New Grad Machine Learning jobs?

Cities near Pittsburgh, PA with the most New Grad Machine Learning job openings:

Infographic showing various New Grad Machine Learning job openings in Pittsburgh, PA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $41,341 per year, or $19.9 per hour.

Senior Machine Learning Research Scientist - Frontier Lab

Carnegie Mellon University

Pittsburgh, PA • On-site

$95K - $121K/yr

Full-time

Re-posted 28 days ago


Carnegie Mellon University rating

8.6

Company rating: 8.6 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

67th of 618 rated colleges and universities


Job description

Job Summary:
Carnegie Mellon University is a leading institution in applied artificial intelligence research. The Senior Machine Learning Research Scientist in the Frontier Lab will conduct applied research and develop prototypes for government missions, collaborating across research and engineering disciplines while providing technical leadership.
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.
Company:
Carnegie Mellon University is a research university offering programs and research across engineering, science, arts, and business. Founded in 1900, the company is headquartered in Pittsburgh, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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