1083 Aws Devops Engener jobs in Irving,TX

Bachelor's or Master's degree in Computer Science, Software Engineering, or a closely related engineering discipline
8+ years (typically 10+) building and operating production platforms and services at scale
Deep software engineering expertise in Python and distributed systems
A track record of building production‑grade services, libraries, and internal platforms
Linux fluency and scripting are required
Cloud platform leadership (AWS) —hands-on with S3, Lambda, Batch, Step Functions, EventBridge, CloudWatch, and SNS/SQS—and experience shaping platform patterns that other teams adopt
Experience enabling managed ML services (e.g., SageMaker) as part of broader platform capabilities; exposure to Azure or GCP is beneficial
DevOps and CI/CD at scale, owning standards for automated build/test/deploy (e.g., Jenkins, Git‑based workflows), containerization (Docker), release governance, and multi‑environment promotion for ML‑enabled workloads
Infrastructure as Code (CloudFormation, Terraform/OpenTofu) and platform reliability engineering (SLOs/error budgets, capacity planning, cost observability, incident response, and post‑mortems) for ML serving and data/feature pipelines
ML enablement in production: model packaging, deployment strategies (batch/online/streaming), inference routing, traffic management, performance tuning, observability, and controls for responsible use—without a research or modeling focus
Cross‑org technical leadership: you mentor junior and senior engineers, are a backbone of code review across repos, and routinely consider impacts on upstream/downstream systems when proposing changes
Set platform strategy and standards for ML packaging, deployment, serving, and observability—driving consistent adoption across squads and business units
Partner with Data Scientists to package, scale, and operationalize models; define the APIs, guardrails, and automation that take work from experimentation to reliable production
Enable secure, scalable access to traditional and generative models by collaborating with platform and application engineers to integrate through enterprise gateways and services
Advance model/data observability—tooling for data and feature drift detection, prediction‑quality monitoring and uncertainty signals, and automated diagnostics/ explainability
Lead cross‑platform incident response and post‑mortems, drive systemic fixes, and evolve standards to prevent recurrence—across applications and the platform
Uplevel engineering velocity by introducing reusable frameworks, paved paths, and CI/CD templates that simplify integration, reduce toil, and improve reliability at scale
Reduce cost and complexity across the ML ecosystem through pragmatic technology choices, clear abstractions, and a long‑term platform roadmap
The base salary range for this position is $107,000-216,000 USD per year.
Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.

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Associate, Model Development (Hybrid Position)

Santander Holdings USA

Dallas, TX 75201

Hybrid~ 24 min

Bachelor's Degree: in related field or equivalent demonstrated through a combination of work experience, training, military service, or education - Required
5+ Years Analytics in Financial Services Industry. - Required.
5+ Years Indirect subprime Auto Financial Services Industry experience. - Preferred.
5+ Years Prior experience developing credit scoring models preferred. - Preferred.
Demonstrated experience with logistic regression models, segmentation and variable reduction techniques, hypothesis testing, neural networks, design of experiments, ANOVA, decision trees, and linear regression.
Prior experience working with credit bureau data.
Prior experience using SAS, particularly SAS base, SAS/STAT, PROC SQL, and SAS Macro programming. Additional knowledge of R preferred.
Demonstrated ability to use SQL and SAS to extract data from multiple data sources.
Demonstrated ability to merge, concatenate, clean, and prepare extremely large datasets for statistical analysis and mathematical model development.
Demonstrated ability to create complex pivot tables in MS Excel.
Ability to effectively explain advanced mathematical concepts, techniques, and analyses to a business audience.
Ability to translate analysis into a clear business plan.
Strong written and verbal communication skills.
Ability to delegate and co-ordinate multiple tasks related to the development and monitoring of statistical models.
Ability to maintain confidentiality..

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Product Development Technician - Prototype Fabrication (R&D Lab)

Corning

Keller, TX 76248

~ 36 min OnsiteHealth InsurancePaid Time OffRetirement Benefit

High School Diploma or equivalent
2-6 years of experience in fabrication, machining, and/or 3D printing.
Ability to read and interpret engineering drawings and schematics.
Familiarity with power tools and small machine shop equipment.
Strong attention to detail, organization, and commitment to quality.
Strong communication, teamwork, and problem-solving skills.
Ability to adapt to changing project needs.

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Principal Engineer - Python API Development

Fidelity Investments

Irving, TX 75061

OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's or Master's degree in Computer Science, Software Engineering, or a closely related engineering discipline
8+ years (typically 10+) building and operating production platforms and services at scale
Deep software engineering expertise in Python and distributed systems
A track record of building production‑grade services, libraries, and internal platforms
Linux fluency and scripting are required
Cloud platform leadership (AWS) —hands-on with S3, Lambda, Batch, Step Functions, EventBridge, CloudWatch, and SNS/SQS—and experience shaping platform patterns that other teams adopt
Experience enabling managed ML services (e.g., SageMaker) as part of broader platform capabilities; exposure to Azure or GCP is beneficial
DevOps and CI/CD at scale, owning standards for automated build/test/deploy (e.g., Jenkins, Git‑based workflows), containerization (Docker), release governance, and multi‑environment promotion for ML‑enabled workloads
Infrastructure as Code (CloudFormation, Terraform/OpenTofu) and platform reliability engineering (SLOs/error budgets, capacity planning, cost observability, incident response, and post‑mortems) for ML serving and data/feature pipelines
ML enablement in production: model packaging, deployment strategies (batch/online/streaming), inference routing, traffic management, performance tuning, observability, and controls for responsible use—without a research or modeling focus
Cross‑org technical leadership: you mentor junior and senior engineers, are a backbone of code review across repos, and routinely consider impacts on upstream/downstream systems when proposing changes
Set platform strategy and standards for ML packaging, deployment, serving, and observability—driving consistent adoption across squads and business units
Partner with Data Scientists to package, scale, and operationalize models; define the APIs, guardrails, and automation that take work from experimentation to reliable production
Enable secure, scalable access to traditional and generative models by collaborating with platform and application engineers to integrate through enterprise gateways and services
Advance model/data observability—tooling for data and feature drift detection, prediction‑quality monitoring and uncertainty signals, and automated diagnostics/ explainability
Lead cross‑platform incident response and post‑mortems, drive systemic fixes, and evolve standards to prevent recurrence—across applications and the platform
Uplevel engineering velocity by introducing reusable frameworks, paved paths, and CI/CD templates that simplify integration, reduce toil, and improve reliability at scale
Reduce cost and complexity across the ML ecosystem through pragmatic technology choices, clear abstractions, and a long‑term platform roadmap
The base salary range for this position is $107,000-216,000 USD per year.
Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.

SmartExplore AI is experimental.

Apply Directly

Metal Fabricator/Saw Operator 2nd Shift

Martin Sprocket & Gear

Arlington, TX 76015

~ 29 min OnsiteHealth InsurancePaid Time OffRetirement Benefit

Math skills: Requires average math skills, with the ability to read and comprehend instructions written in English and complete simple logs and reports in English.
Physical capability: Must be physically able to handle heavy items, including lifting, pushing, pulling, and positioning components.
Policy/procedure compliance: Must be able to work scheduled hours and comply with the company's timekeeping policy and all other company policies.
Stamina: Must be able to consistently stand for an entire shift in a non-climate-controlled shop environment.

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IT Architect II-IM Application Development

CHRISTUS Health

Irving, TX 75039

Onsite

Bachelor's degree in Computer Science, Architecture, Information Systems, Electrical Engineering or related field preferred, or four years of relevant experience required.
Five years of increasingly responsible Enterprise architecture experience in Healthcare Hospital systems environments with a wide variety of Information Services applications and technologies is required.
Extensive technical knowledge of Healthcare Hospital systems, databases, networks, operating systems and Information Management “Best Practices”, including: local and wide area networking, network protocols and routing; network, server, and host operating systems; Interoperability, data storage and retrieval systems; system backup and recovery; IP networking, internet and intranet technologies; email, groupware, office automation and collaboration technologies; voice and/or data communications; voice and/or data networking; video conferencing and telemedicine; server hardware, software, and administration.
Security model understanding and maintenance
Solid understanding of Business Intelligence/Data Warehouse environment with involvement in design and development of database solution in both traditional as well as columnar databases.
Experience in data integration with ETL techniques and frameworks
Experience in Big Data querying tools, such as Hive, Impala and Spark SQL

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