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4 jobs found

Today

Applied AI Engineer

Nucor Business Technology Dallas, TX

Dallas, TX

Today

Full time Backend Developer Ai Application Development Artificial Intelligence

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Job Description

Nucor Business Technology is seeking an Applied AI Engineer to engineer, deploy, and support full-stack, AI-driven web applications on enterprise AI platforms. The role sits at the intersection of applied machine learning, software delivery, and enterprise enablement, with close collaboration across OT, IT, cybersecurity, and business SMEs to support reliability, safety, and compliance.

This onsite position in Dallas, TX, United States involves building proofs-of-technology, moving validated results into scalable solutions, and maintaining the DataOps and MLOps tooling that powers production workloads.

What you will do

Build, deploy, and support AI applications and workflows for division, commercial, and corporate teams on enterprise AI platforms.
Stand up proofs of value, validate results quickly, and scale wins into solutions that are supportable.
Configure, maintain, and support DataOps and MLOps tooling, including pipelines, job orchestration, feature stores, monitoring, and CI/CD.
Rapidly create custom AI and ML solutions for time-sensitive needs across scrap, EAF, casting, rolling, finishing, logistics, and commercial workflows.
Develop and deploy full-stack enterprise applications powered by AI.
Conduct design and development reviews, test, troubleshoot, and enhance software applications.
Deliver technical deep-dives, demonstrations, and internal training.
Create user playbooks and quick-start guides, supporting enablement and training sessions.
Collaborate with OT, IT, and cybersecurity teams, along with business SMEs, to align with Nucor guardrails for reliability, safety, and compliance.
Work effectively in ambiguity with hands-on practices in mill environments.
Write application specifications and documentation.
Continuously identify technical risks and gaps and develop mitigation strategies aligned to upcoming team needs.

Skills and experience

Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related discipline.
Equivalent combinations of experience and education will also be considered.
3+ years delivering AI or ML applications on enterprise platforms, or a relevant degree with strong internships or projects.
1+ year experience with Python, SQL, notebooks, version control, and baseline CI/CD concepts.
Experience operating production pipelines and jobs, including alerting and observability.
Demonstrated ability to initiate, lead, and uphold safety policies, practices, procedures, and housekeeping standards at all times.

Technologies

C3.ai
Palantir Foundry
Python, SQL
CI/CD, Git
JavaScript, React, Redux, Vue, Backbone, Angular
Azure
Power BI, Tableau, Qlik
Figma

Preferred qualifications

Experience with enterprise AI application platforms and their semantic or object models (for example, C3.ai model types or Palantir Foundry ontology).
Strong software development background with Python and JavaScript, including modern JavaScript frameworks such as React, Redux, Vue, Backbone, or Angular.
Proficiency with Git or other version control systems.
Experience deploying software to major cloud platforms such as Azure.
Solid understanding of SQL and NoSQL databases, data structures, algorithms, and time-series data analysis, including cleansing and normalization.
Working knowledge of Agile software development methodologies.
Strong grasp of common machine learning techniques, applications, and trade-offs.
Experience with data visualization tools including Power BI, Tableau, or Qlik.
Familiarity with Figma or similar design and prototyping tools for UI/UX collaboration.
Exposure to plant historians, MES, event streams, or edge integrations.
Experience managing continuous improvement projects and implementing supply chain AI applications.
Ability to translate business needs into system requirements and communicate effectively across technical and business teams.

Benefits

Medical, Dental, Vision
Disability Insurance
401K and Roth accounts
Profit sharing
Pay-for-performance bonuses
Paid parental leave
Tuition reimbursement
Stock program
Scholarships

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Today

Mid-Level AI & Machine Learning Engineer

Fieldwire San Francisco, CA

San Francisco, CA

Today

$170k - $195k/yr Full time AI Ai Engineer Ai/ml Developer

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Job Description

Fieldwire is building AI foundations that help turn construction documents and images into usable information inside its platform. As a Mid-Level AI & Machine Learning Engineer, you will adapt and deploy AI models for document and image understanding, with a focus on model performance in production and context-aware outputs that fit users’ workflows.

This hybrid role is based in San Francisco, California, with Fieldwire’s headquarters centrally located off Embarcadero BART.

What you will do

Architect, build, and maintain AI foundations across the full stack, embedding capabilities into core platform functionality
Evaluate and select open-source models, then adapt them to domain-specific use cases using fine-tuning, transfer learning, and lightweight training
Deploy and operate models in Fieldwire’s infrastructure, including GPU-backed environments with an emphasis on inference performance, resource utilization, throughput, and latency
Build solutions for image understanding, including visual object detection, classification, and segmentation
Extract and interpret information from PDFs, scanned documents, images, and other complex visual content by combining OCR, document layout analysis, and multimodal models
Apply AI and computer vision techniques to surface relevant, context-aware information within users’ workflows
Debug production issues across services and multiple levels of the stack
Contribute to improving engineering standards, tooling, and processes

Required qualifications

Bachelor’s or Master’s degree in Computer Science (or equivalent work experience)
3+ years of experience in a Fullstack, Backend, AI Engineering, or Machine Learning role
Practical experience in machine learning, including training, evaluating, and deploying models
Hands-on experience with computer vision and image-processing techniques
Knowledge of modern toolchains used to develop high-quality applications
Strong ability to write clean, well-tested, and modular code

Technologies you may work with

Open-source models, fine-tuning, transfer learning
OCR, document layout analysis, multimodal models
Transformers, vision-language models
GPU-backed environments
Rust, Ruby on Rails, Angular

Preferred experience

Working with pretrained models and adapting them to domain-specific tasks through fine-tuning and transfer learning
Understanding modern model architectures, including transformers and vision-language models
Experience with image and document processing, such as OCR, document layout analysis, or extracting structured information from PDFs and images
Experience building production systems, preferably in Rust, Ruby on Rails, or Angular

Compensation

Estimated pay range: $170,000 - $195,000 per year
Actual salary offer will consider factors including skills, qualifications, and experience

Benefits

Corporate bonus with a range up to 30%

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1d ago

School of Nursing Full Stack AI Engineer

University of Texas at Austin Austin, TX

Austin, TX

1d ago

$70k - $70k/yr Full time Backend Developer Artificial Intelligence Data Analytics

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Job Description

The School of Nursing is seeking a Full Stack AI Engineer to design, deploy, and maintain AI applications that support nursing education and faculty research.

Responsibilities

Build and maintain applications using Python, TypeScript, and React or Next.js, including backend APIs, databases, authentication, role-based access, and deployment in university-approved cloud environments.
Implement production large language model applications using retrieval-augmented generation (RAG), source citations, tool calling, and guardrails.
Evaluate retrieval quality and performance, including factual grounding, citation accuracy, unsafe outputs, latency, and cost before and after release.
Ensure factual answers are traceable to approved sources and source versions.
Provide handling for insufficient or conflicting evidence, including declining unsupported answers and routing questions to human review.
Develop tools for faculty authoring, content approval, and review.
Convert educator-authored rubrics into measurable criteria, assessment logic, and evaluation cases, including faculty validation and review of AI-generated feedback.
Translate investigator-approved protocols into application features, including study-specific workflows, approved intervention content, participant interactions, and reproducible data collection and exports.
Implement protocol amendments in coordination with the research team.
Build learning assessments, learner progress tracking, and dashboards for educational outcomes, engagement, intervention delivery, and study measures.
Separate educational records from research datasets and permissions as required by each project.
Implement automated tests, CI/CD, monitoring, backups, and recovery procedures.
Maintain version control for code, prompts, source materials, rubrics, assessments, and AI model configurations.
Apply access controls, secure secret management, data minimization, and safe logging.
Protect student records, research data, and inadvertently entered patient information through university-approved procedures and services.
Scope projects with faculty, document architecture and operating procedures, train users, resolve technical issues, and coordinate with university IT, security, accessibility, and research support teams.

Requirements

Bachelor’s degree in computer science, software engineering, information systems, or a related field (or equivalent combination of relevant education and experience), subject to the approved university job classification.
Demonstrated proficiency in Python and TypeScript and experience developing applications with React or Next.js, including backend APIs, relational or other appropriate databases, authentication, Git, and cloud deployment.
Demonstrated experience deploying and maintaining at least one LLM-enabled application used by people beyond the development team, with responsibility for reliability and iteration.
Practical experience with RAG, citations, tool calling, guardrails, and repeatable LLM evaluations, including recognition of hallucinations, prompt injection, and limitations of AI-generated assessments.
Experience with automated testing, monitoring, and CI/CD, and working knowledge of application security, privacy, and accessibility fundamentals.
Ability to translate faculty learning objectives, rubrics, and research requirements into testable software behavior, and to communicate technical choices clearly to nontechnical collaborators.
Ability to manage competing priorities, estimate effort, document decisions, and maintain software through deployment and ongoing support.

Preferred Qualifications

Current enrollment in, or completion of, a master’s program in artificial intelligence, computer science, data science, or a related field.
Experience with nursing or health professions education, virtual patient simulation, digital health interventions, or human participant research.
Experience building content-management, educator-review, content-approval, learning assessment, and analytics workflows.
Experience with Canvas or Moodle integration, LTI, xAPI, or SCORM, and with university identity and access systems.
Experience implementing accessible interfaces, including keyboard and screen-reader access, and age-appropriate, user-centered user experiences.

Technology Stack

Python, TypeScript, React, Next.js
Large language model, retrieval-augmented generation (RAG), tool calling
Git, CI/CD, cloud deployment
Authentication, relational databases

Working Expectations and Oversight

Faculty retain responsibility for educational content, clinical accuracy, rubrics, assessment interpretation, and approval of source materials.
Investigators retain responsibility for research protocols, consent language, and required research approvals.
The engineer implements approved requirements and flags technical risks, gaps, and limitations.
Applications must clearly distinguish educational simulation and research activities from real-patient diagnosis or treatment.
Any research intervention that includes health guidance must remain within its approved protocol, with defined human oversight and escalation pathways.
Supervisors and faculty partners will prioritize a manageable project portfolio within the 30-hour workweek, including maintenance and support.
Work schedule, reporting relationship, formal job classification, benefits, and exemption status will be finalized through university HR.

Salary

$70,000 annual for a 30 hour assignment

Required Application Materials

Resume.
Brief statement describing relevant experience.
Examples of deployed applications or a portfolio.
Describe your individual contribution, deployment approach, evaluation methods, and maintenance responsibilities.

Confidential or proprietary materials are not required.

Application Notes (Non-UT Employees or Contingent Workers)

Resume is prompted the first time you apply; then you can upload a new Resume for subsequent applications.
Any additional required materials are uploaded in the Application Questions section (multi-select files).
Before submitting, ensure all required materials are uploaded.
After submission, you cannot make changes.

Application Notes (Current UT Employees or Contingent Workers)

Must apply within Workday by searching for Find UT Jobs.
If a current employee: log in to Workday, update your Worker Profile sections via the Career link before applying.
The application is one page and prompts you to upload your resume.
Respond to application questions to upload additional required materials noted above.

Employment Eligibility

Regular staff employed in their current position for the last six continuous months are eligible for openings recruited through University-Wide or Open Recruiting.
Staff eligible for promotion/transfer may apply without supervisor approval.

Retirement Plan Eligibility

Teacher Retirement System of Texas (TRS), subject to being at least 20 hours per week and at least 135 days in length.

Background Checks

A criminal history background check will be required for finalist(s) under consideration.

Employment Eligibility Verification (I-9)

If hired, complete the federal Employment Eligibility Verification I-9 form.
Present acceptable and original documents to prove identity and authorization to work in the United States.
Documents must be presented no later than the third day of employment.
Failure to do so will result in loss of employment at the university.

E-Verify

The University of Texas at Austin uses E-Verify to check work authorization of all new hires effective May 2015.
Company ID number for E-Verify: 854197.
For more information: E-Verify Poster (English and Spanish) [PDF], Right to Work Poster (English) [PDF], Right to Work Poster (Spanish) [PDF].

Compliance (Title IX and Clery Act)

Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act).
If this position is identified as a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting.
The Clery Act requires prospective employees be notified of the availability of the Annual Security and Fire Safety report.
You may access the most recent report online or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.

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9d ago

Full-Stack Data Engineer

Base-2 Solutions Doral, FL

Doral, FL

9d ago

Full time Backend Developer Analytics Data

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Job Description

Base-2 Solutions is hiring a Full-Stack Data Engineer (onsite in the United States) to support USSOUTHCOM J26 ENHANCED DOMAIN AWARENESS.

Responsibilities

Develop, maintain, and optimize data integration pipelines, API services, and front-end interfaces for geospatial and structured data visualization.
Build and support full-stack capabilities for data visualization, dashboarding, and analytics within ESRI-based GIS platforms and data lake environments.
Work with data lake platforms including Databricks and Kubernetes, plus ESRI ArcGIS environments.
Implement metadata-driven search and retrieval functionality in secure web applications.
Integrate APIs to enable data interoperability across internal systems, the data lake, ESRI ArcGIS, and external sources.
Create and deploy full-stack applications supporting geospatial workflows within ESRI-based GIS platforms, Unity Catalog, and cloud-based databases.
Design and implement RESTful and GraphQL APIs for data retrieval and integration between the data lake, ESRI ArcGIS, and external sources.
Manage CI/CD pipelines and containerized deployments on Kubernetes.
Implement API authentication mechanisms to help ensure secure access to research products.
Optimize database queries and indexing strategies for large-scale geospatial and structured datasets.

Requirements

Bachelor’s degree in Computer Science, Data Engineering, or a related field.
OR minimum 5 years of equivalent experience in full-stack development and data engineering.
Demonstrated experience building and deploying full-stack applications for data visualization, dashboarding, and analytics within ESRI-based GIS platforms, Unity Catalog, and cloud-based databases.
Experience implementing RESTful and GraphQL APIs for data retrieval and integration.
Experience managing CI/CD, containerized deployments in Kubernetes, and API authentication mechanisms.
Experience optimizing database queries and indexing strategies for large-scale geospatial and structured datasets.
Active Top Secret/SCI security clearance.
U.S. citizenship required.

Technologies

Databricks
Kubernetes
ESRI ArcGIS
Unity Catalog
RESTful APIs
GraphQL
AWS
Microsoft Azure

Preferred Qualifications

AWS Certified Data Analytics - Specialty
Microsoft Certified: Azure Data Engineer Associate
ESRI ArcGIS Developer Certification

Benefits

Competitive fixed salary or hourly pay (based on experience, skills, location, and internal equity).
Employee referral bonuses up to $10,000 per hired referral.
Additional bonus opportunities for exceptional performance and contributions to business development and company growth (role-dependent).
100% company-paid medical premiums for employees and eligible dependents.
Choose from multiple plan options with CareFirst, Kaiser, and UnitedHealthcare: PPO, POS, HMO, and HSA-compatible plans.
100% company-paid dental premiums for employees and eligible dependents.
100% company-paid vision premiums for employees and eligible dependents.
100% company-paid premiums for short-term disability.
100% company-paid premiums for long-term disability.
100% company-paid premiums for accidental death & dismemberment (AD&D).
100% company-paid life insurance up to $200,000.
401(k) with immediate vesting: 4% company match plus 4% non-elective company contribution (8% total).
401(k) pre-tax and Roth options.
Up to 20 days of flexible paid time off (PTO).
11 paid floating holidays.
Flexible work schedules, including flex time and compressed work periods (contract and project-dependent).

Job Details

Requisition ID: 5447
Location: Doral, FL
Work type: On-Site
Shift: First
Referral eligibility: Eligible
U.S. citizenship required: Yes

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Full Stack Developer Data Jobs

Applied AI Engineer

Mid-Level AI & Machine Learning Engineer

School of Nursing Full Stack AI Engineer

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