Pittsburgh, PA

Data Jobs in Pittsburgh, PA

38 jobs found

Include remote jobs

Today

Sr Machine Learning Engineer, ML Systems Engineering - Proactive

Apple Pittsburgh, PA

Pittsburgh, PA

Today

Full time Agentic Ai Ai Agent Artificial Intelligence

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Job Description

Apple is seeking a Senior Machine Learning Engineer to support Proactive Intelligence, applying machine learning and agentic AI to deliver personalized experiences across Apple devices. The position focuses on end-to-end work for agentic machine learning applications in production, including design, implementation, evaluation, and ongoing optimization.

Role Summary

You will build and improve agentic machine learning systems that operate on multimodal inputs and contribute to production-ready intelligence. The work includes running experiments, debugging and optimizing models and systems, and setting up automated evaluation and monitoring so performance can be measured and sustained.

Key Responsibilities

Design, implement, and evaluate data and machine learning systems that use multimodal inputs for production environments.
Plan and execute experiments, including debugging and optimizing agentic machine learning applications.
Build scalable automated processes for evaluation and monitoring.
Support a team culture grounded in respect, empowerment, and opportunities for professional growth.
Commit to engineering excellence by following best practices that enable high-velocity delivery with confidence.
Prioritize user experience and use storytelling to communicate complex technical ideas.
Develop tools and techniques that improve how problems are approached and solved.
Ship software that customers rely on daily.

Required Qualifications

Experience shipping machine learning and agentic systems with a strong software engineering background.
Experience designing, implementing, and evaluating data and machine learning systems on multimodal inputs for production systems.
Ability to plan and conduct experiments, and debug and optimize agentic machine learning applications.
Willingness to ask questions and eagerness to teach and learn collaboratively.
4+ years of experience building production machine learning systems.
MS in Computer Science or equivalent practical experience.
Proficiency in Python.
Proficiency in at least one compiled language: C, C++, Objective-C, Swift, Go, Java, Kotlin, C#, or Rust.

Preferred Qualifications

Production experience training, deploying, and evaluating autonomous agentic systems.
Production experience working with ML pipelines and large datasets.
Experience in resource constrained computing, such as embedded systems or mobile development.
Strong ability to use AI agent assistance effectively as part of software development workflows.

Tech Stack

Python
C, C++
Objective-C, Swift
Go
Java, Kotlin
C#
Rust

Location and Work Mode

Pittsburgh, PA (onsite)

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Today

Machine Learning Engineer

Carnegie Mellon University Pittsburgh, PA

Pittsburgh, PA

Today

Full time Artificial Intelligence Data Processing Data Science

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Job Description

Carnegie Mellon University’s SEI AI Division is seeking a Machine Learning Engineer to engineer secure, robust AI systems that support research into vulnerabilities in AI and ML algorithms, with an emphasis on defenses suitable for government sponsors.

Role focus

In this position, you will develop engineering solutions that help study how AI systems can be attacked, create practical mitigations and defenses, and advance applied adversarial machine learning capabilities.

Counter AI research

Study threat models targeting AI and ML algorithms.
Understand the behaviors of AI algorithms.
Identify weak points and design novel approaches to subvert AI and ML systems.

AI and ML algorithm defense research

Create practical mitigations and defenses for observed attacks affecting AI and ML algorithms.
Evaluate the effectiveness of defensive techniques.

Applied adversarial machine learning

Advance the state of the art in adversarial machine learning.
Develop and transition capabilities to government sponsors.

Key responsibilities

Identify and investigate emerging AI and AI-adjacent technologies.
Define and refine processes, practices, and tools for working with AI.
Design and build well-engineered prototypes of AI systems.
Transition and provide guidance on AI capabilities to government sponsors.
Build machine learning models and systems using frameworks including TensorFlow, PyTorch, Torch, and Caffe, with modern programming languages including Python, C/C++, and Java.
Work with data pipelines, ETL processes, and backend systems.
Work with, extend, and implement state-of-the-art machine learning methods.
Experiment with modern and emerging machine learning frameworks, methods, and algorithms in computer vision, natural language processing, planning and scheduling, and robot control.
Engineer safe, trusted, and reliable machine learning systems.
Conduct rapid prototyping to demonstrate and evaluate technologies in relevant environments.
Evaluate systems for performance and security and test capabilities using novel testing and analysis techniques.
Participate with developers, researchers, designers, and technical leads, collaborating with researchers and government customers to understand challenges, needs, and possible solutions.
Improve the Division’s technical capabilities through mentoring and teaching, participating in design sessions, and sharing insights across SEI.

Required qualifications

Comprehensive knowledge of machine learning; prior experience in adversarial machine learning is desirable but not required.
Demonstrated use of well-established engineering practices to solve difficult problems.
Understanding of how to convert research results into functioning prototypes or capabilities.
Experience leading technical projects in novel areas with limited prior work to build upon.
Strong written and verbal communication skills, including the ability to explain complex technical ideas in lay terms.
Experience publishing written or technical artifacts describing your work.
Strong collaboration skills with colleagues and sponsors.
Ability and willingness to guide and mentor junior team members.
Education and experience: a bachelor’s degree in computer science, statistics, machine learning, electrical engineering, or a related discipline with ten (10) years of experience; OR an MS in the same fields with eight (8) years of experience; OR a PhD in the same fields with five (5) years of experience.
Subject to a background investigation and must be able to obtain and maintain an active Department of War security clearance.
Willingness to work onsite at SEI offices in Pittsburgh, PA or Arlington, VA 5 days per week.
Willingness to travel up to 25% of the time to locations outside of your home location.

Technologies

TensorFlow
PyTorch
Torch
Caffe
Python
C/C++
Java
Computer vision
Natural language processing
Planning and scheduling
Robot control

Location and job details

Location: Pittsburgh, PA (onsite)
Job function: Software/Applications Development/Engineering
Position type: Staff – Regular
Full time
Pay basis: Salary
Minimum experience: 10 years

Benefits

Comprehensive medical, prescription, dental, and vision insurance
Generous retirement savings program with employer contributions
Tuition benefits
Paid time off and observed holidays
Life and accidental death and disability insurance
Free Pittsburgh Regional Transit bus pass
Access to a Family Concierge Team to help navigate childcare needs
Fitness center access

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1d ago

Sr Data Scientist

Agilite Global Solutions Company Pittsburgh, PA

Pittsburgh, PA

1d ago

Full time Senior Ai Ml Artificial Intelligence

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Job Description

Agilite Global Solutions Company is hiring a Senior Data Scientist to strengthen the Data Platform engineering team within a healthcare technology environment. This role focuses on leading AI and ML initiatives end-to-end, from ideation through deployment and scaling, while partnering closely with internal stakeholders to deliver measurable customer outcomes.

What you’ll do

Develop and implement AI and machine learning strategies, taking initiatives from early ideation through deployment.
Stay current with evolving AI and machine learning technologies, tools, and trends.
Build and maintain strong relationships with stakeholders, customers, and partners across internal and external teams.
Promote generative AI adoption through proofs-of-concept and demos for employee and functional groups, including technology, operations, marketing, legal, compliance, people, internal infrastructure, and more.
Lead hands-on when needed by diving deep into technical problem-solving and execution.
Spot opportunities to improve technology capabilities and drive innovation during development.
Apply deep learning, NLP, computer vision, and other AI techniques to improve model performance.
Support model interpretability, fairness, and compliance with data governance policies.
Mentor junior data scientists while contributing to the broader data strategy.
Collaborate with the Innovation team and other engineering leaders to shape and execute AI strategy.

Key skills and qualifications

Proven communication, presentation, and interpersonal skills, with the ability to explain complex AI/ML concepts and outcomes to technical and non-technical audiences.
Experience working with cross-functional and distributed teams in a global, diverse environment.
Experience establishing and enforcing AI/ML best practices, standards, and ethics.
Strong analytical, problem-solving, and decision-making skills, balancing innovation with practicality.
Experience with cloud platforms and services such as AWS, Azure, and GCP.
Experience with generative AI and LLMs.
Experience mentoring, coaching, and developing AI/ML talent.
Demonstrated drive to keep learning and staying current with AI/ML trends and research.
Experience leading and managing AI/ML teams and projects from ideation to delivery and evaluation.
Proficient in Python, R, or other programming languages for data analysis and AI/ML development.
A can-do attitude and commitment to positive cultural impact; strong customer focus.

Education and experience

Bachelor’s Degree in Computer Science or a related field.
12+ years of experience in Software Engineering, Data Science, AI, or Analytics.
6+ years of experience with AI/ML techniques such as deep learning, NLP, recommender systems, reinforcement learning, and large language models (LLMs).
6+ years of experience with AI/ML frameworks and tools including MLFlow, TensorFlow, PyTorch, Keras, and Scikit-learn.

Technologies you’ll work with

AI, machine learning, generative AI, LLMs, deep learning
NLP, natural language processing, computer vision
Python, R
AWS, Azure, GCP
MLFlow, TensorFlow, PyTorch, Keras, scikit-learn
Recommender systems, reinforcement learning

Preferred background

Background in Healthcare AI.
Portfolio of AI/ML publications, patents, or awards.
Experience with DevOps and CI/CD tools and practices such as Git, Jenkins, Docker, Kubernetes, etc.

Location and work conditions

Hybrid environment: Cranberry, PA office.
Ability to travel 10-15% of the time.
Western Pennsylvania, Pittsburgh Area, US East Coast.

Key focus areas include AI/ML strategy, model development and deployment, generative AI enablement, and collaboration across engineering and business functions.

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2d ago

Data Scientist Senior - Internal Audit

PNC Financial Services Group Pittsburgh, PA

Pittsburgh, PA

2d ago

$91k - $186k/yr Full time Python Analytics Artificial Intelligence

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Job Description

Senior Data Scientist supporting PNC’s Internal Audit organization, delivering advanced analytics, machine learning, and AI-enabled solutions to identify, monitor, and assess risk across the enterprise.

Responsibilities

Lead end-to-end delivery of advanced analytics, machine learning, and AI-enabled solutions for Internal Audit priorities, including design, development, testing, deployment, and ongoing maintenance.
Work with audit teams and stakeholders to convert audit objectives, business challenges, and risk considerations into analytics and data products.
Develop predictive, diagnostic, anomaly detection, and risk-focused models to strengthen audit planning, testing, continuous monitoring, and reporting.
Build scalable, maintainable, reusable analytical frameworks, workflows, and data products to improve efficiency across the audit lifecycle.
Identify opportunities to apply automation, machine learning, and generative AI to enhance audit processes and improve risk identification.
Collaborate with technology, data, and enterprise partners to support model deployment, productionization, data pipeline development, and solution maintenance.
Ensure solutions follow established governance, validation, testing, documentation, and lifecycle management standards.
Present analytical results and strategic recommendations to technical and non-technical audiences, translating complex findings into actionable business insights.
Mentor and provide technical guidance to team members while promoting best practices in data science, machine learning, software development, and analytics engineering.
Contribute to the evolution of Internal Audit data science, automation, and AI capabilities through innovation, thought leadership, and continuous improvement.
Lead analytical projects using large volumes of structured and unstructured data to extract actionable business insights.
Direct data gathering, data processing, and data mining across large and complex datasets.
Lead development of algorithms using advanced mathematical and statistical techniques to predict business outcomes and recommend optimal actions to management.
Run methodical analytical experiments to identify opportunities for product and process optimization, using visualization and data storytelling to share insights with management.
Partner with Data Architects, Data Analysts, Data Engineers, and Visualization Experts to develop data-driven solutions.

Requirements

Advanced proficiency in Python and SQL.
Experience with data manipulation and analytical libraries, such as Pandas, NumPy, Scikit-learn, PySpark, TensorFlow, or similar technologies.
Experience working with large-scale data environments, including Hadoop-based platforms, distributed data processing frameworks, and enterprise data ecosystems.
Experience using GitHub or other source control platforms for code management, collaboration, version control, and code review.
Experience with machine learning, statistical modeling, predictive analytics, and data science methodologies.
Experience with natural language processing (NLP), text analytics, document intelligence, topic modeling, and analysis of unstructured data.
Experience developing, validating, deploying, and monitoring production analytics or machine learning solutions.
Familiarity with software package, dependency, and artifact management tools such as Artifactory, Conda, pip, or similar enterprise development technologies.
Familiarity with data visualization platforms such as Power BI or Tableau, or similar tools.
Generative AI experience preferred, including LLMs, prompt engineering, RAG, AI agents, or related technologies.
Understanding of AI governance, model risk management, and responsible AI practices preferred.
Strong problem-solving and critical-thinking capabilities.
Ability to influence stakeholders and communicate effectively across technical and business audiences.
Demonstrated ability to manage multiple priorities and deliver high-quality solutions in a dynamic environment.
Strong collaboration skills and a passion for mentoring and developing others.
Typically requires a university or college degree and 5+ years of industry-relevant experience.
In lieu of a degree, a comparable combination of education, job-specific certifications, and experience (including military service) may be considered.

Technologies

Python, SQL
Pandas, NumPy, Scikit-learn, PySpark, TensorFlow
GitHub
Hadoop
Power BI, Tableau
Artifactory, Conda, pip
Natural language processing (NLP), Topic modeling
Generative AI, Large language models (LLMs), Prompt engineering, Retrieval-augmented generation (RAG), AI agents
Machine learning

Benefits

Medical and prescription drug coverage (with Health Savings Account feature)
Dental and vision options
Employee and spouse/child life insurance
Short and long-term disability protection
401(k) with PNC match
Pension and stock purchase plans
Dependent care reimbursement account
Back-up child/elder care
Adoption, surrogacy, and doula reimbursement
Educational assistance (including select programs fully paid)
Robust wellness program with financial incentives
Maternity and/or parental leave
Up to 11 paid holidays each year
9 occasional absence days each year (unless otherwise required by law)
15 to 25 vacation days each year (depending on career level)

Location and Work Model

Onsite: Pittsburgh, PA 15222
In-office work location options include Cleveland, OH; Pittsburgh, PA; Raleigh, NC; or Birmingham, AL

Compensation

Base salary: $91,000.00 to $185,900.00 per year
Salaries may vary based on geographic location, market data, and individual skills, experience, and education
Incentive eligible; payment based on company, business, and/or individual performance

Application Window

Expected posted duration: two business days from 09/08/2026 (may be longer with business discretion)

Disability Accommodations Statement

If an accommodation is required to participate in the application process, contact AccommodationRequest@pnc.com with subject “accommodation request” and include your name, job ID, and preferred contact method. Applicants may also call 877-968-7762 and say “Workday”. All information provided will be kept confidential and used only to the extent required for reasonable accommodations.

EEO Statement

Equal employment opportunity regardless of race, color, sex, religion, national origin, age, sexual orientation, gender identity, disability, veteran status, or other legally protected categories
Subject to requirements of Section 19 of the Federal Deposit Insurance Act (FDIA); and, for any registered role, the SAFE Act and/or FINRA rules that prohibit hiring of individuals with certain criminal history

California Residents

Refer to the California Consumer Privacy Act Privacy Notice to understand how PNC may use or disclose personal information in hiring practices.

Customer Focused / Managing Risk

Customer Focused: Knowledgeable of values and practices that align with customer needs and satisfaction
Managing Risk: Assessing and effectively managing risks related to business objectives and activities to support PNC’s Enterprise Risk Management Framework

Preferred Skills / Competencies

Analytical Thinking, Competitive Advantages, Data Analytics, Data Mining, Data Science, Machine Learning (ML)
Data Architecture, Data Mining, Disruptive Innovation, Information Capture, Modeling: Data, Process, Events, Objects, Prototyping, Query and Database Access Tools
No required certification(s)
No required license(s)

Sponsorship

PNC will not provide sponsorship for employment visas or participate in STEM OPT for this position

Role Requirements (Summary)

Senior Data Scientist in Internal Audit organization
Minimum experience: 5 years
Education: Masters

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8d ago

IMDb Data Scientist, IMDb Insights and Analytics

Amazon.com Services LLC Pittsburgh, PA

Pittsburgh, PA

8d ago

$136k - $184k/yr Full time Analytics Artificial Intelligence Business Intelligence

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Job Description

Amazon is hiring a Data Scientist for IMDb Insights and Analytics in Pittsburgh, PA to turn business questions into measurable, responsible machine learning outcomes.

Key responsibilities

Translate loosely defined business problems into science problems and iterate on the approach with limited guidance
Establish ground truth by designing sampling, defining a label quality bar, and building datasets across behavioral, text, and catalog domains
Define and evaluate precision, recall, and coverage, including reporting what accuracy is achievable at a given cost
Document failure modes, quantify the cost of each error type, and set thresholds with product and policy partners prior to deployment
Deliver methodology and analysis on medium-size projects in a format that other scientists and business partners can act on
Decide whether to train in-house, fine-tune, or call a language model based on evidence
Use generative AI tooling to scale personal throughput, not only to build end products
Ship solutions that another scientist can test and reproduce
Partner with engineers to move models into production, then define drift monitoring and retraining triggers
Build deep knowledge of the team’s owned areas and mentor teammates on method choice

Requirements

4+ years experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab, etc.)
3+ years in a data scientist or similar role with data extraction, analysis, statistical modeling, and communication
3+ years experience using machine learning/statistical modeling tools and techniques, including parameters that affect performance
Bachelor’s degree
Experience applying theoretical models in an applied environment
Knowledge of machine learning concepts and their application to reasoning and problem-solving

Technologies

SQL
Python
R
SAS
Matlab
Language model
Generative AI tooling

Location and compensation

Location: Pittsburgh, PA (onsite)
Salary: USD 136,000 - 184,000 per year
Minimum experience: 3 years

Benefits

Sign-on payments
Restricted stock units (RSUs)
Health insurance (medical, dental, vision, prescription)
Basic Life & AD&D insurance
Option for Supplemental life plans
EAP
Mental Health Support
Medical Advice Line
Flexible Spending Accounts
Adoption and Surrogacy Reimbursement coverage
401(k) matching
Paid time off
Parental leave

A day in the life

Most of the week focuses on modeling and measurement, including pulling data, building features, running evaluations, and discussing thresholds with evidence rather than opinion
AI tooling is used to handle repetitive work so you can focus on the core science
Remaining time goes to collaboration with product managers, policy partners, and the operations team who use model outputs daily
With a small team, responsibilities span multiple problem areas rather than a single ownership area

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12d ago

Associate Data Scientist

Carnegie Mellon University Pittsburgh, PA

Pittsburgh, PA

12d ago

Full time Artificial Intelligence Data Data Analysis

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Job Description

Work on applied research in statistics, analytics, machine learning, and AI to help government and industry partners address cybersecurity challenges.

Responsibilities

Partner with customers to pinpoint where advanced statistical methods can address their problems
Plan and develop prototype solutions
Build out final products from prototypes
Co-author research proposals
Execute studies and analyze results
Present findings to DoW sponsors and at academic conferences
Design metrics and experimental plans for large-scale cybersecurity research programs
Develop human-in-the-loop machine learning solutions
Build classifiers to identify security vulnerabilities

Requirements

BS in a highly-quantitative field (data science, machine learning, computer science, statistics, or related) plus 3 years of experience, or an equivalent combination of training and experience
OR MS in the same disciplines plus 1 year of experience
OR PhD in data science, machine learning, computer science, statistics, or a related highly-quantitative discipline
Ability and willingness to complete modest travel to various locations to support the SEI’s mission
Subject to a background check and able to obtain and maintain a U.S. Department of War security clearance

Technologies

Languages and data: R; Python (NumPy/SciPy/Pandas/Polars); MATLAB
Forecasting: Prophet, NeuralProphet, Chronos, Lag-Llama
LLM and RAG: LLMs, RAG, LangChain, LlamaIndex, Haystack
APIs and serving: FastAPI, Triton, KServe
Cloud and ML platforms: SageMaker, Vertex AI
Big data: Spark, Trino, Snowflake, BigQuery, Databricks
Modeling libraries: LightGBM, XGBoost, CatBoost
Deep learning: PyTorch, JAX, TensorFlow

Knowledge, Skills, and Abilities

Experience in predictive modeling, data science, and/or AI and machine learning
Deep understanding of statistical modeling and advanced data analytics
Proficiency with at least one mathematical/statistical programming package (examples include R, Python (NumPy/SciPy/Pandas/Polars), MATLAB)
Ability to imagine novel analytical approaches and apply them in a multi-disciplinary environment
Strong communication skills
Expertise in one or more areas:
- Recommendation systems
- Time-series forecasting (Prophet, NeuralProphet, Chronos, Lag-Llama, etc.)
- NLP and LLMs (fine-tuning, RAG, evaluation, prompt engineering)
- Causal inference, uplift modeling, or synthetic controls
- Modern ML frameworks (LightGBM, XGBoost, CatBoost, PyTorch, JAX, TensorFlow)
- LLMs and agentic workflows (LangChain, LlamaIndex, Haystack)
- Model deployment (FastAPI, Triton, KServe, SageMaker, Vertex AI, or similar)
- Big data (Spark, Trino, Snowflake, BigQuery, Databricks)
- Multimodal AI

Desired Experience

Experience in cybersecurity and privacy is a plus
Experience in U.S. Government work and/or with FFRDCs, UARCs, and National Labs is a plus
Demonstrated ability to learn new concepts and grow into new work areas

Benefits

Comprehensive medical, prescription, dental, and vision insurance
Generous retirement savings program with employer contributions
Tuition benefits
Paid time off
Observed holidays
Life and accidental death and disability insurance
Free Pittsburgh Regional Transit bus pass
Access to Family Concierge Team to help navigate childcare needs
Fitness center access

Location and Work Setup

Onsite location: Pittsburgh, PA
Additional location listed: Arlington, VA; Pittsburgh, PA

Job Details

Position type: Staff – Regular
Full time
Pay basis: Salary
Job function: Software/Applications Development/Engineering
Minimum experience: 3 years (for BS route)

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15d ago

Data Scientist II

Amazon.com Services LLC Pittsburgh, PA

Pittsburgh, PA

15d ago

$136k - $184k/yr Full time Artificial Intelligence Business Intelligence Data Analysis

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Job Description

On Amazon Fashion’s NAS Shop and Keep (SHAKE) science team, this role supports data-driven decision-making and scalable machine learning work aimed at improving recommendation systems and reducing retail returns. You will analyze large, complex datasets and partner across science, engineering, product, design, and business to translate insights into measurable product and model improvements.

What you’ll do

Collaborate with applied scientists, data engineers, product managers, UX designers, and business partners to tackle complex questions through data analysis.
Use analytical outputs to improve machine learning recommendation system performance, enhance customer experience, and inform the roadmap for both science and product.
Analyze complex, disparate datasets from multiple sources to extract actionable insights, build segmentation models, and reduce retail returns to improve customer experience.
Communicate clearly across teams to align on key questions and build confidence with senior leaders.
Handle multiple streams of work, including gap analysis of algorithm results, integrating disparate datasets, business intelligence, analyzing engagement metrics, and presenting findings to stakeholders.
Operate effectively in an agile, fast-paced environment on high-visibility initiatives.

Minimum requirements

3+ years of experience with data querying languages (for example SQL), scripting languages (for example Python), or statistical and mathematical software (for example R, SAS, Matlab).
2+ years of data scientist experience.
3+ years of experience with machine learning and statistical modeling data analysis tools and techniques, including understanding parameters that affect performance.
Experience applying theoretical models in an applied environment.
Bachelor’s degree.

Technologies

SQL
Python
R
SAS
Matlab
Perl

Preferred qualifications

Experience in Python, Perl, or another scripting language.
Experience in an ML or data scientist role at a large technology company.
Bachelor’s degree or above in Science, Technology, Engineering, or Mathematics (STEM), or experience defining and creating benchmarks to assess GenAI model performance.
Ability to identify where generative AI could improve products, workflows, or customer experiences.
Experience using generative AI tools to increase workflow efficiency, with a willingness to learn effective prompting and evaluation practices.