Jobs in the United States

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Added 9 mins ago
Physical AI Senior Engineer
TNA Toyota Motor Engineering & Manufacturing North America, Inc. Company
Georgetown, KY
Toyota’s Manufacturing Innovation & Transformation (MIT) – Manufacturing Center of Excellence is looking for a passionate and highly motivated Physical AI Senior Engineer.
Added 26 mins ago
Manufacturing Engineer - Rochester, NY
Military Spouse Jobs & VetJobs
United States
The Manufacturing Engineer leads engineering activities from concept initiation through implementation and control. This role develops and applies advanced engineering judgment, technical…
Added 50 mins ago
2027 Associate Engineer / Engineer Aeronautical - WAFB MO
Northrop Grumman
Whiteman Air Force Base, MO
+ Adapts machine, tooling, or equipment design to optimize efficiency and integrate with existing operations.
Added 55 mins ago
B
Machine Learning Engineer, AI
Biohub
Redwood City, CA
- $241,000 to $301,000 USD / year
The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is for Senior Machine Learning Engineer $214,000 -$268,000 and for Staff Machine…
Added 55 mins ago
B
Machine Learning Engineer, AI
Biohub
NY
- $241,000 to $301,000 USD / year
The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is for Senior Machine Learning Engineer $214,000 -$268,000 and for Staff Machine…
Added 59 mins ago
OI
Embedded Software Engineer, DSP
OceanComm, Inc.
Chicago, IL
- $90,000 to $150,000 USD / year
This is a high-ownership role on a small, quickly growing team. You will not be one engineer among hundreds working on a narrow subsystem; you will have direct visibility into the full…
Added 59 mins ago
OI
Senior Embedded Software Engineer, DSP
OceanComm, Inc.
Chicago, IL
- $140,000 to $175,000 USD / year
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Added 1 hour ago
Applied AI Health System Engineer [Health Services-Provider] – Senior Manager
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What You Must Have
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Google Cloud Engineer, Experienced Associate
PwC
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Las Vegas, NV
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Principal Engineer, Privacy
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Seattle, WA
A track record of operating as a Principal engineer or equivalent: setting technical direction that multiple teams adopted, and delivering company-critical, multi-year initiatives
Added 1 hour ago
Sr. Consulting Manager- Logistics Consulting
Cognizant
Liberty Hill, TX
What You Must Have to Be Considered
Added 1 hour ago
Automation and Controls Engineer
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Haslet, TX
As a member of the technical staff, the Automation and Controls Engineer is responsible for the design and implementation of control systems for automated TIAC (Turbine Inlet Air Cooling)…
Added 1 hour ago
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Sr Data Engineer
McAfee, Inc.
Frisco, TX
- $123,650 USD / year
Design, build, optimize, and maintain scalable data pipelines and analytical datasets supporting analytics, machine learning, and AI use cases.
Added 1 hour ago
Lead Tech Mechanical Engineer
BD (Becton, Dickinson and Company)
El Paso, TX
…feat. It takes the imagination and passion of all of us - from design and engineering to the manufacturing and marketing of our billions of MedTech products per year - to look at the…
Added 1 hour ago
Data Engineer Intern
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Irving, TX
As a Data Engineer Intern, you will work alongside experienced engineers and architects to build scalable data products, cloud-native data pipelines, and modern data platforms that support…
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Data Engineer 4 (Cloud Operations Resilience Engineering) (MEG)
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Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions in full-stack development tools and technologies
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Data Engineer 5 (Cloud Operations Resilience Engineering) (MEG)
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Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions in full-stack development tools and technologies
Added 1 hour ago
Sr.Principal Engineer-Full Stack
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Plano, TX
Our team is seeking a highly motivated person to fill an opening as a Sr.Principal Engineer-Full Stack to help our growing needs.
Added 1 hour ago
Operations AI Engineer - Early Career
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Fort Worth, TX
A collaborative engineer with strong expertise in applied statistics, machine learning, and data visualization. You thrive in fast‑paced, global environments, possess excellent…
Added 1 hour ago
Data Scientist Asc - Early Career
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A collaborative engineer with strong expertise in applied statistics, machine learning, and data visualization. You thrive in fast‑paced, global environments, possess excellent…
Added 1 hour ago
DFM RET Engineer
Texas Instruments
Dallas, TX
At 28nm and below, photolithography cannot simply print a chip design as drawn but rather optical diffraction causes critical features to print incorrectly, with direct consequences to…
Added 1 hour ago
C
Data AI Solutions Architect
Cognizant
Dallas, TX
- $170,000 to $200,000 USD / year
This position follows a hybrid work model and can be based in either:
Added 1 hour ago
AI Methodology Design/CAD Engineer
Apple
Austin, TX
As part of the Hardware Technology CAD team, you'll help bring AI methodology to chip design. You will work end to end with design teams and CAD flow owners on complex design and CAD…
Added 1 hour ago
AI Methodology Design/CAD Engineer
Apple
Austin, TX
As part of the Hardware Technology CAD team, you'll help bring AI methodology to chip design. You will work end to end with design teams and CAD flow owners on complex design and CAD…

Pearson

Lead Specialist, AI Scientist

Remote, United States

The full-time salary range for this role is $140,000 – $160,000.

Apply on hccz.fa.em3.oraclecloud.com About employer

Applications open in a new tab.

Job details

Pay: The full-time salary range for this role is $140,000 – $160,000.
Apply by: Nov 20, 2026
Posting language: English
Posted: Nov 3, 2026

Original job description

Role Overview We are seeking a Lead Specialist, Applied AI Systems Engineer, to design, build, and continuously improve the intelligent systems that support Pearson’s work developing the next generation of K–12 assessment and learning. This role sits within the Measurement & Learning team and operates at the intersection of Content Development, Learning Science, Technology, AI Science, and Psychometrics, partnering closely with software engineers and the AI Data & Knowledge Architect to turn assessment and measurement expertise into testable AI capabilities within our assessment authoring system, which supports formative and summative assessment for Pearson and its partners. This hands-on role joins in the early phases of this work, improving and extending complete AI systems built on a shared knowledge foundation, rather than focusing on prompts or chatbots. The work spans predictive machine learning, statistical methods, retrieval, graph-based approaches, generative and agentic AI, and deterministic software, chosen for reliability rather than novelty. We are particularly interested in innovators who have built AI or machine-learning systems whose outputs must be rigorously evaluated against ground truth, expert judgment, or reliable evidence, such as scientific, healthcare, financial, cybersecurity, legal, or assessment applications. Candidates whose experience is mainly in conversational or customer-service AI should also show substantial experience evaluating systems against defined performance standards. Experience in education, learning, or assessment is strongly preferred when it involves the systems beneath products, such as domain and skill models, learner models, standards and competency frameworks as structured data, or adaptive and recommendation engines, rather than standalone tutoring, chatbot, or content-generation applications. End-to-End AI Systems Design

Design complete, modular AI systems spanning knowledge and data inputs, retrieval, models, agents, tools, deterministic services, human review, evaluation, and integration
Break complex problems into the right combination of predictive ML, statistical methods, generative models, retrieval, graph reasoning, deterministic software, and human decision points
Build working systems and reference implementations, and partner with software engineers to bring them into the assessment authoring system
Design architectures that can evolve as models, data, domain knowledge, and evaluation evidence change

Agentic & Knowledge-Grounded AI

Design and implement agentic and multi-step workflows using models, tools, retrieval, state, structured outputs, and human decision points
Build knowledge-grounded systems that use graph, semantic, vector, and hybrid retrieval as appropriate
Co-design knowledge and graph architecture with the AI Data & Knowledge Architect, contributing substantively rather than treating the knowledge layer as a black box
Develop AI capabilities for content creation and revision, verification, alignment across frameworks, guidance, and analytic insights

Evaluation-Driven Development

Make evaluation part of how systems are built, not a final step
Build and maintain evaluation benches, including expert-adjudicated datasets, challenge sets, regression suites, and protected holdout data
Partner with psychometricians and content experts to turn domain expectations into measurable criteria
Analyze failure modes, critical errors, and performance across meaningful data and task slices, not only aggregate metrics
Monitor deployed systems for drift and emerging failures, and use findings to drive improvement

Machine Learning, Model Adaptation & Data

Develop predictive models, classifiers, and ranking methods where they outperform generative AI
Evaluate tradeoffs among prompting, retrieval, structured knowledge, model selection, and model adaptation, without locking the architecture to a single provider
Apply parameter-efficient fine-tuning and other adaptation methods when evaluation evidence shows they add value
Turn expert judgments and adjudicated examples into versioned evaluation and training assets, keeping training data strictly separate from protected evaluation data
Design synthetic-data approaches with rigorous quality controls, never treating generated data as ground truth by default

Innovation, Judgment & Responsible AI

Work with a high degree of autonomy on problems that have no established solutions
Prototype quickly, test assumptions empirically, and pivot when evidence warrants
Build AI that is accurate, transparent in its reasoning, auditable, and designed to support rather than supplant human expertise
Uphold responsible AI and data practices, including privacy, security, fairness, and appropriate use of student and content data

Cross-Functional Collaboration

Partner with Technology teams and software engineers to integrate AI capabilities into the assessment authoring system
Collaborate with AI Science colleagues and the AI Data & Knowledge Architect on shared architecture and methods
Work with psychometricians and learning scientists to translate measurement and learning requirements into evaluation criteria
Partner with content development teams to understand workflows, quality requirements, edge cases, and human-review needs
Communicate findings, tradeoffs, and limitations clearly to technical and non-technical audiences

Required Qualifications

Advanced degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related field, or equivalent experience
Experience designing and building complete AI or machine-learning systems end to end, not only isolated models or prompts
Strong breadth across predictive ML, statistical learning, and LLM-based, agentic, and retrieval-grounded systems, with judgment about when each fits
Demonstrated experience evaluating probabilistic systems against ground truth or expert judgment, including evaluation datasets, error analysis, and regression testing
Experience with knowledge graphs and knowledge-grounded AI sufficient to contribute to architecture decisions
Strong Python proficiency, and experience with TypeScript or the ability to become productive quickly in a TypeScript codebase
Track record of innovating beyond established practice, with sound technical judgment and high autonomy
Ability to collaborate closely with engineers and domain experts, translating expertise into requirements and evaluation criteria

Preferred Qualifications

Experience building the knowledge and inference layers of education, learning, or assessment systems, such as skill or competency graphs, learner or domain models, standards alignment engines, adaptive or recommendation logic, or the inference behind learner insight reporting
Experience building AI or ML systems in evidence-sensitive domains such as scientific, healthcare, financial, legal, or assessment applications
Hands-on experience with parameter-efficient fine-tuning or other model-adaptation methods
Experience designing, filtering, and validating synthetic data for evaluation or model improvement
Experience building expert-annotated datasets, adjudication protocols, or evaluation platforms
Experience with graph-grounded agents, hybrid retrieval, or other knowledge-intensive AI applications
Familiarity with ontologies, semantic models, or hybrid neural-symbolic architectures
Experience with calibration, uncertainty estimation, drift detection, or model monitoring
Experience with TypeScript, AWS, PostgreSQL, and graph data stores; our environment also uses Go, Python, and ML lifecycle tools such as MLflow
Familiarity with educational measurement, psychometrics, or learning science

Design Philosophy

Complete systems over isolated models
Evaluation as part of engineering, not an afterthought
Innovation at the edge of current practice, grounded in evidence
Transparent, auditable, and accurate AI
AI that supports rather than supplants human expertise
The right method for the problem, not the newest one

Why This Role Matters This role will build the intelligent core of an industry-defining assessment system. The goal is not convincing AI output but systems whose quality can be measured, explained, and continuously improved. By inventing new approaches and proving they work, this engineer will help define what intelligent formative and summative assessment can become. Compensation at Pearson is influenced by factors including skill set, experience, and location. The full-time salary range for this role is $140,000 – $160,000. This position is eligible to participate in an annual incentive program. Information on benefits can be found here. Applications will be accepted through 20th November 2026. This window may be extended depending on business needs. Apply today and imagine the impact you can make.

Apply on hccz.fa.em3.oraclecloud.com About employer

More about this job

Skills

Machine learning
Cybersecurity
Tutoring
Chatbot
ML
Content creation
Collaboration
Computer science
Artificial intelligence
Statistics
Python
TypeScript
Grading systems
Reporting
Estimating
AWS
PostgreSQL
Go
Mlflow

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Work requirements

Jobs in the United States