Jobs in the United States

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Added 6 mins ago
AI Engineer 5
Capital One
San Jose, CA · San Francisco, CA · McLean, VA · Cambridge, MA · NY
At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create…
Added 6 mins ago
AI Engineer 4
Capital One
San Jose, CA · San Francisco, CA · McLean, VA · Cambridge, MA · NY
At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create…
Added 7 mins ago
Hardware Machine Learning Engineer
IMC
NY
We are deploying machine learning directly onto custom hardware – and we want you to help drive it from the ground up. This is an initiative where you'll have the rare opportunity to…
Added 10 mins ago
Sr. SDET - 3056958
APEX SYSTEMS, LLC
SALT LAKE CITY, UT
Added 11 mins ago
Principal Engineer
NetApp
San Jose
Agentic AI & Machine Learning Systems: Architect and deliver agentic AI and machine learning systems that operate reliably at NetApp fleet scale, including the data, evaluation, and safety…
Added 11 mins ago
ASIC Design Verification Engineer, Machine Learning
Google
Sunnyvale, CA
As an ASIC Design Verification Engineer, you will be part of a team developing ASICs used to accelerate computation in data centers. You will have dynamic, multi-faceted responsibilities in…
Added 20 mins ago
Analytics Engineer
Tantalus
Chattanooga, TN
Apply AI, machine learning, and automation techniques to improve reporting accuracy, scalability, and insight generation.
Added 20 mins ago
Analytics Engineer
Tantalus
Raleigh, NC
Apply AI, machine learning, and automation techniques to improve reporting accuracy, scalability, and insight generation.
Added 22 mins ago
Principal Engineer
NetApp, Inc.
San Jose, CA
Agentic AI & Machine Learning Systems: Architect and deliver agentic AI and machine learning systems that operate reliably at NetApp fleet scale, including the data, evaluation, and safety…
Added 23 mins ago
UG
Principal Data Engineer - Remote
UnitedHealth Group
Eden Prairie, MN
- $112,700 to $193,200 USD / year
As a Principal Data Engineer within the Optum Insight Engineering AI team, you will design and develop robust public cloud data systems, services, and reusable patterns that drive massive…
Added 31 mins ago
A
Applied AI and Machine Learning Engineer
Aurex
Huntsville, AL
- $120,000 to $170,000 USD / year
Applied AI and Machine Learning Engineer – Mid-Level
Added 31 mins ago
Artificial Intelligence (AI) Engineer
Robert Half
Cincinnati, OH
We are looking for an Artificial Intelligence (AI) Engineer to join a long-term contract opportunity based in Cincinnati, Ohio. In this role, you will create and operationalize AI and…
Added 40 mins ago
Sr Lead Software Engineer - Agentic Pricing & AI/ML
JPMC page
Jersey City, NJ
Proven experience designing end-to-end machine learning platforms or MLOps pipelines spanning model training, deployment, serving, monitoring, and governance
Added 41 mins ago
Senior AI Product Engineer
Citian
Washington, DC
You’ll work with some of the brightest minds in the software and transportation industries. Our engineers and data scientists apply the latest in emerging tech, Artificial Intelligence, and…
Added 41 mins ago
AI Engineer - Data Success
Citian
Washington, DC
You’ll work with some of the brightest minds in the software and transportation industries. Our engineers and data scientists apply the latest in emerging tech, Artificial Intelligence, and…
Added 41 mins ago
Software Support Engineer
Symbotic LLC
USA Andover, MA
Symbotic is an automation technology leader reimagining the supply chain with its end-to-end, AI-powered robotic and software platform. Symbotic reinvents the warehouse as a strategic asset…
Added 1 hour ago
O
Principal Application Software Engineer- Oracle Health
Oracle
United States
- $99,600 to $209,500 USD / year
Artificial Intelligence and Machine Learning platforms
Added 1 hour ago
O
Senior Application Software Engineer- Oracle Health
Oracle
United States
- $86,100 to $187,000 USD / year
Artificial Intelligence and Machine Learning platforms
Added 1 hour ago
Staff Engineer 3
SLAC National Accelerator Laboratory
Menlo Park, CA
Research, evaluate and develop new controls technologies that can improve accelerator performance, reliability, automation and maintainability, including emerging applications of AI and…
Added 1 hour ago
Senior Software Engineer, YouTube Ads Marketplace Optimization
Google
Mountain View, CA
Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.
Added 1 hour ago
Senior Software Engineer, AI/ML Recommendations, Rankings, Predictions, YouTube
Google
Mountain View, CA
3 years of experiencewith end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
Added 1 hour ago
Research Engineer, Responsibility, DeepMind
Google
Mountain View, CA
Experience with Cloud AI/Machine learning systems and tools (e.g., Kaggle, TensorFlow, PyTorch etc.).
Added 1 hour ago
ASIC Engineering Intern, Formal Verification
Meta
Sunnyvale, CA
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy,…
Added 1 hour ago
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Software Engineer Data & AI II (Full Time) – United States
Cisco
San Jose, CA
- Full-time
You are a passionate software engineer with expertise in developing scalable data pipelines, designing robust analytics platforms, and building infrastructure to support machine learning…
Added 1 hour ago
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NPS Research Engineer (Part Time) - 30667
HII
Monterey, CA
- Part-time
Know & Grow Your People - Commit to learning and supporting team success.

Electric Power Engineers

Data Engineering, Architecture & Applied Data Science, III

Austin, TX, United States

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Job details

Apply by: Nov 4, 2027
Experience: This is a hands-on individual contributor role for a professional with 4–5 years of relevant experience.
Posting language: English
Posted: Nov 4, 2026

Original job description

Overview

We are designing the grid of the future!

EPE is seeking a Staff Engineer III with demonstrated experience in data engineering, data architecture, and applied data science to support utility and energy-sector consulting engagements. You will help clients translate fragmented data and complex business requirements into well-designed data models, reliable data pipelines, integrated workflows, and statistically rigorous analytical solutions. Your work will span data discovery, architecture and integration design, hands-on development, machine learning, and model maintenance.

This is a hands-on individual contributor role for a professional with 4–5 years of relevant experience. You will independently deliver defined technical components and workstreams, collaborating with senior technical staff and client architects on broader architectural decisions. Depending on the engagement, responsibilities may involve direct implementation or design specifications and advisory support for client-owned implementation.

Responsibilities

How you can make an impact:

Data Engineering

Design, develop, test, and maintain repeatable ETL/ELT pipelines that ingest, transform, reconcile, and deliver data from databases, files, APIs, and other approved sources.
Using agentic workflows, Develop reusable Python and SQL components for data cleansing, standardization, aggregation, validation, and feature preparation.
Implement scheduling, dependency management, logging, failure handling, and monitoring for assigned data workflows.
Profile source data and establish automated checks for completeness, validity, consistency, uniqueness, and freshness.
Develop record-matching and entity-resolution logic to reconcile customer, asset, device, program, and operational records.

Data Architecture and Integration Design

Translate business, analytical, and operational requirements into documented data architecture and integration designs for defined solutions or components.
Develop conceptual, logical, and physical data models, entity relationship diagrams, schemas, data dictionaries, and source-to-target mappings.
Define identifiers, relationships, reference data, authoritative sources, reconciliation rules, and requirements for retaining historical changes.
Design data flows connecting source systems, staging and storage layers, analytical datasets, models, and downstream applications.
Document data lineage and requirements for ownership, access, retention, and auditability, and prepare implementation-ready specifications and handoff documentation.

Applied Data Science

Apply probability, statistical inference, regression, hypothesis testing, and uncertainty quantification to real-world client problems.
Develop and validate forecasting, classification, anomaly-detection, clustering, and prioritization models as appropriate to the application.
Perform feature engineering, model selection, tuning, and evaluation against meaningful baselines.
Address data leakage, overfitting, class imbalance, sampling bias, and time-dependent validation requirements.
Monitor deployed models, investigate false positives and false negatives, and support recalibration and retraining.

Client and Technical Delivery

Participate in requirements workshops, technical interviews, architecture reviews, and client working sessions.
Prepare clear technical reports, process maps, design documentation, and analytical presentations.
Deliver assigned work within agreed scope, schedule, budget, and quality expectations.
Identify and escalate data-access constraints, technical dependencies, methodological limitations, and delivery risks.
Contribute to peer reviews, reusable technical methods, and guidance for less-experienced colleagues.
Use AI-assisted development responsibly, validating outputs and protecting client information.

Qualifications

Bring your passion, here's what’s needed:

Bachelor’s degree in computer science, data science, statistics, mathematics, engineering, or a closely related quantitative discipline.
4–5 years of relevant professional experience, including hands-on work in data engineering and applied data science, with demonstrated contributions to data architecture or integration design.
Experience building and maintaining repeatable data pipelines or integrations, including testing, scheduling or orchestration, logging, and data-quality validation, beyond one-time data preparation or exploratory notebooks.
Experience designing data models, schemas, relationships, and source-to-target mappings, and explaining the rationale behind design decisions.
Strong Python and SQL proficiency, including complex queries, data transformation, relational databases, structured and semi-structured data, and APIs/JSON.
Working experience with at least one cloud or distributed-data platform, such as Databricks, Azure, AWS, Google Cloud, or an equivalent environment.
Strong understanding of probability distributions, conditional probability, sampling, statistical inference, regression, confidence and prediction intervals, and uncertainty.
Practical experience developing and evaluating statistical or machine learning models, including appropriate validation and interpretation of results.
Hands-on experience with pandas, NumPy, scikit-learn, and statistical libraries such as SciPy or statsmodels.
Experience with Git, code review, testing, technical documentation, and reproducible analyses.
Ability to communicate technical designs, analytical findings, assumptions, and limitations to technical and nontechnical audiences.

Preferred Qualifications

Experience with AI / agentic coding workflow processes and automating workflows and analytical processes.
Experience with Databricks, Spark/PySpark, Delta Lake, or comparable distributed-data technologies.
Experience with dimensional modeling, warehouse/lakehouse design, metadata management, or data catalogs.
Experience with workflow orchestration, CI/CD, model versioning, experiment tracking, or model monitoring.
Experience with time-series or probabilistic forecasting, Bayesian methods, simulation, or optimization.
Familiarity with XGBoost, LightGBM, PyMC, PyTorch, or TensorFlow, without an expectation of expertise in every framework.
Experience with utility datasets, DER registries, load forecasting, sensor analytics, or engineering automation.
Master’s degree in a relevant quantitative or technical discipline.

Be a part of an innovative team shaping the grid of the future through advanced energy intelligence. For more than half a century, Electric Power Engineers (EPE) has partnered with power and energy clients across the globe, providing consulting expertise and energy intelligence software solutions for complex engineering and grid modeling challenges. As leaders in the renewables space, we are focused on building a modern, secure, and resilient grid. Join us in making an impact on the communities we serve and the environment in which we live. Together we can transform the future of energy.

How we support you:

Comprehensive health and wellness benefits including medical, dental, and vision with 100% premium coverage for you
Generous PTO and paid holidays
MyShare Employee Ownership Program
Work with industry leaders
401K, up to a 4% match (100% vested from day 1)

Location: This position will be located in City, State

Travel: Occasional travel may be needed (10% or less)

EPE is an equal opportunity/AA/Disability/Veteran employer. The EEO is the Law poster, and its supplement are available using the following links: EEOC is the Law Poster

Third-Party Recruiting Notification

EPE does not accept unsolicited resumes from third-party recruiters. Any unsolicited third-party resumes forwarded by recruiters to EPE via our career page or to any of our managers or employees will be considered public information, may be treated as a direct application from the person identified in the resume, and will not be eligible for placement fee payment to the agency. EPE will not pay a fee to a third-party recruiter or agency without a previously signed third-party agreement and has not coordinated their recruiting activity with the appropriate member of the Talent Acquisition team.

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