1554 Structural Engineer Design Delivery jobs in Dallas,TX

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Controls Business Development Manager (Building Automation Systems)-Dallas, TX

Top Tempo Technical - Dallas, TX

Controls Business Development Manager (Building Automation Systems)-Dallas, TX

Onsite

New, Posted 1 day ago

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Applied Early Career Program - Field Service Engineer

Applied Materials

Dallas, TX 75221

Paid Relocation to Dallas, TX

Requires TravelUrgently Hiring

Associate degree, recent college graduate, military technical training, trade certification, or equivalent hands-on experience
Basic mechanical aptitude and interest in technical systems
Willingness to learn and read electrical and mechanical schematics
Ability to diagnose and solve basic technical problems
Strong written and verbal communication skills
Basic working knowledge of Microsoft Excel, Word, and PowerPoint
Valid driver's license and ability to obtain a passport, if required for travel
Ability to meet on-site safety, environmental, and customer requirements

SmartExplore AI is experimental.

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Stress Engineer

Saratech

Fort Worth, TX 76101

$85-$90/hr

New, Posted 15 hours ago

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Principal Engineer, IT Systems Engineering

American Airlines

Fort Worth, TX 76101

~ 44 min Onsite

Bachelor's in Computer Science, Computer Engineering, Technology , Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training
8 years experience as a software or platform engineer
5 years of experience with public and private cloud technologies, particularly Kubernetes
Hands-on experience in systems development in a variety of computing architectures and environments
Hands-on experience writing, testing, and maintaining Kubernetes operator code in Go
Strong technical expertise in Kubernetes architecture, including networking patterns, security patterns, service mesh, scheduling, and lifecycle automation.
Experience with Kubebuilder and/or Operator SDK
A test-first mindset and experience using Ginkgo/Gomega
Strong understanding of Kubernetes networking internals and cloud networking concepts.
Experience maintaining and operating large-scale, highly resilient platforms in the public cloud.
Proficient in infrastructure automation & orchestration
Proficient in Agile methodologies
Significant experience in requirements analysis and use case development, with a thorough understanding of software development life cycles, development and technology tools, testing methodologies, and requirements gathering
Ability to create/reengineer integration solutions (architectures) with other enterprise standard technologies
Ability to manage multiple efforts concurrently with the skills to keep complex initiatives moving forward quickly while exercising an appropriate level of procedural discipline
Proven ability to build strong and sustainable relationships with internal and external stakeholders
Ability to adapt to unexpected events, new facts, and rapidly changing circumstances
Ability to thrive in a sense-of-urgency environment and leverage best practices

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Commissioning Engineer

Amazon Data Services

Dallas, TX 75201

Requires TravelHealth InsurancePaid Time OffRetirement Benefit

5+ years of engineering, installation, or startup/commissioning of electrical and mechanical systems experience
Bachelor's degree in Mechanical/Electrical Engineering or 5 years of relevant discipline work experience
High technical competency in either mechanical or electrical or control systems utilized in critical infrastructures, with the capability to learn and be trained in the others.
Understand the design concept and intent by reviewing mechanical or electrical design documentation, including drawings, specifications, vendor submittals and sequences of operations and provide feedback on the same in accordance with Amazon standards for basis of design.
Develop but majorly review commissioning documentation such as test plans, scripts and reports developed by vendors to ensure accuracy in accordance with the design requirements.
U.S Citizenship Required
Ability and willingness to travel domestic and internationally for up to 80% of the year.
Required to provide personal transportation for meetings and job visits away from the office; reimbursed.
Walk job sites in uneven terrain
Work at heights and from ladders
Regularly walk, use hands and fingers, reach with hands and arms, stoop, kneel, crouch or crawl
Lift and/or move up to 49 pounds; and participate in group lifts for 50 pounds or more
Carry objects weighing up to 49 pounds for short distances
Perform physical tasks throughout the day without becoming overly tired
Ability to manipulate small wires and objects easily
Work in a noisy environment
Work in environments that are colder or hotter than a normal office environment

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Manufacturing Engineer

Teledyne

Garland, TX 75040

~ 26 min OnsiteFlexible ScheduleHealth InsurancePaid Time OffRetirement Benefit

BS degree in engineering or related discipline with at least 3 to 5 years of direct or related experience - required
Or minimum 8-10 years working experience as a Manufacturing Engineer or related engineering position of responsibility with demonstrated engineering competency may be considered in place of formal college degree with associated experience
Demonstrates accuracy and proficiency in execution of job responsibilities - required
Good interpersonal and training skills - required
Strong electro-mechanical troubleshooting skills - required
PC literate - required
Strong attention to detail - required

SmartExplore AI is experimental.

New, Posted 23 hours ago

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Machine Learning Engineer

Capital One

Plano, TX 75023

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Principal Engineer - Python API Development

Fidelity Investments

Lewisville, TX 75029

~ 33 min 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.