ZipRecruiter

Log In

1

Machine Learning Researcher Jobs in Pittsburgh, PA

Bespoke Labs

Machine Learning Engineer

Pittsburgh, PA · On-site

About Us We are AI researchers and builders who understand how to curate data and RL environments ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

previous pagenext page

Showing results 21-40

All JobsMachine Learning Researcher JobsMachine Learning Researcher Jobs in Pittsburgh, PA

Machine Learning Researcher information

See Pittsburgh, PA salary details

$29.1K

$109.8K

$159.7K

How much do machine learning researcher jobs pay per year?

As of Aug 20, 2026, the average yearly pay for machine learning researcher in Pittsburgh, PA is $109,801.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,000.00 and $149,500.00 per year, depending on experience, location, and employer.

What does a machine learning researcher do?

A Machine Learning Researcher designs, develops, and tests algorithms and models that allow computers to learn from and make decisions based on data. They often work on advancing the field by exploring new methods, improving existing algorithms, and publishing their findings. These researchers collaborate with engineers and data scientists to apply their research to practical problems in areas like computer vision, natural language processing, and robotics. Their work typically involves a combination of mathematics, statistics, programming, and experimentation.

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

To thrive as a Machine Learning Researcher, you need deep expertise in mathematics, statistics, programming (typically Python), and a strong academic background in computer science or related fields. Familiarity with frameworks like TensorFlow or PyTorch and experience with tools for data analysis and model development are standard, often supported by advanced degrees or relevant certifications. Critical thinking, creativity, and effective communication are vital soft skills for developing novel solutions and collaborating across interdisciplinary teams. These skills enable researchers to design innovative algorithms, validate models rigorously, and contribute impactful advancements in the field.

What are some common challenges machine learning researchers face when transitioning from academic research to industry roles?

Machine Learning Researchers often find that transitioning to industry involves adapting to faster project timelines, collaborative workflows, and a focus on scalable, real-world solutions rather than theoretical advances alone. In industry, you'll likely work closely with cross-functional teams, such as software engineers and product managers, to ensure models are both practical and maintainable. Balancing innovation with business objectives, handling production constraints, and communicating complex findings to non-technical stakeholders are some of the key challenges you may encounter.

What is the difference between Machine Learning Researcher vs Data Scientist?

AspectMachine Learning ResearcherData Scientist
Required CredentialsAdvanced degrees in CS, ML, or related fields; research experienceDegree in CS, statistics, or related; strong analytical skills
Work EnvironmentResearch labs, academia, R&D departmentsBusiness environments, tech companies, consulting
Employer & Industry UsageUniversities, research institutions, tech firmsCorporations, startups, finance, healthcare
Common Search & ComparisonFocus on theoretical ML advancementsFocus on data analysis & business insights

While both roles involve working with data and algorithms, Machine Learning Researchers primarily focus on developing new algorithms and advancing ML theory, often in research or academic settings. Data Scientists apply these techniques to analyze data, generate insights, and support business decisions in industry environments.

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

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

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

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

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

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

Machine Learning Researcher jobs near you
Infographic showing various Machine Learning Researcher job openings in Pittsburgh, PA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 22% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $109,801 per year, or $52.8 per hour.

Senior Machine Learning Research Scientist - Frontier Lab

Software Engineering Institute

Pittsburgh, PA • On-site

$95K - $121K/yr

Full-time

Re-posted 25 days ago

Job description

What We Do
At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering challenges related to building, deploying, and sustaining AI-enabled systems for high-impact government missions.
The Frontier Lab advances AI engineering and transitions frontier AI capabilities to government stakeholders through applied research, rapid prototyping, short-cycle TEVV, and technical advisory.
Position Summary
As a Senior Machine Learning Research Scientist in the Frontier Lab, you will serve as a senior individual contributor and technical leader, shaping and executing applied research and prototype capability development for government and DoW missions. This role spans the research-engineering spectrum: some SR MLRS hires may lean more research-heavy and others more engineering-heavy, but successful candidates collaborate effectively across both.
You will operate with high autonomy, represent technical work with customers and stakeholders, and help guide Frontier Lab research direction-while remaining hands-on in development, evaluation, and delivery. Your work may span Frontier Lab focus areas such as:
  • Agentic AI for mission workflows (e.g., planning, analysis, decision support) where autonomous and human-guided agents interact with tools, data systems, and operators.

  • AI test, evaluation, verification, and validation (TEVV) to improve confidence in performance, robustness, uncertainty, and trustworthiness of ML-enabled systems.

  • Mission-tailored language models, including techniques to improve accuracy and reliability, reduce hallucinations, and integrate structured knowledge for operational tasks.

  • Mission modalities and multimodal learning, including sensor fusion and learning under noisy, sparse, or constrained data conditions (including synthetic data and weakly-/self-supervised approaches).

  • AI at the tactical edge, enabling capability under constrained compute/connectivity through efficient inference, compression, rapid adaptation, and update/redeploy patterns.

Key Responsibilities / Duties
Senior MLRS staff are expected to operate with a high degree of autonomy and technical ownership while remaining hands-on in development, evaluation, and delivery.
  • Mission-context execution: Execute work within the operational context-understanding users, workflows, constraints, success criteria, and outcomes-so technical decisions are grounded in real mission needs.

  • Technical leadership / Tech lead: Lead technical execution by defining technical tasking, sequencing work into realistic milestones, maintaining delivery quality, and delegating appropriately across the team.

  • Applied research and prototyping: Design and run studies, build convincing prototypes and reference implementations, and produce evidence-backed insights that can be matured and transitioned into operational settings.

  • Evaluation, assurance, and evidence: Establish credible evaluation strategies and test pipelines that assess performance, robustness, reliability, and trustworthiness in mission-representative scenarios.

  • Customer-facing technical ownership: Serve as the primary technical interface when appropriate; translate mission goals into measurable technical outcomes; communicate progress, decisions, and risks clearly to stakeholders.

  • Mentorship and talent development: Proactively mentor junior staff and teammates, raising the bar for research rigor, engineering practice, and delivery habits across project teams.

  • State-of-the-art awareness and agenda shaping: 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.

  • Self-direction and time management: Manage multiple priorities effectively, sustain steady execution cadence, and resolve blockers with minimal oversight.

  • Community building (internal and external): 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.

Requirements
  • Education / Experience

  • 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.

Knowledge, Skills, & Abilities (KSAs)
  • 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.

Desired Experience
  • 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.

Other Requirements
  • 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.

Location
Arlington, VA, Pittsburgh, PA
Job Function
Software/Applications Development/Engineering
Position Type
Staff - Regular
Full time/Part time
Full time
Pay Basis
SalaryMore Information:
  • Please visit "Why Carnegie Mellon" to learn more about becoming part of an institution inspiring innovations that change the world.
  • Click here to view a listing of employee benefits
  • Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran.
  • Statement of Assurance

Apply