1943 Systems Reliability Engineering Intern jobs in Dallas,TX

Engineer Intern

Curtiss-Wright

Grand Prairie, TX 75052

$18-$21/hr

~ 28 min OnsiteUrgently Hiring

Mechanical Engineering or Manufacturing Engineering student in their 2nd, 3rd, or 4th year of studies
CAD Modeling Experience (ideally SolidWorks)
3D Printing Experience (using Simplify3d software)
Design & Build Experience (i.e. Robot team, Catapult Team, HPVC Team, or personal projects)

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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

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Manufacturing Engineer

Megger

Dallas, TX 75217

OnsiteUrgently Hiring

Bachelor's degree in engineering
Analytical and mathematical proficiency
5-8 Years experience directly working in an electro-mechanical manufacturing industry
English fluency
Effective communication skills to interface with assembly personnel
Familiarity with Surface Mount and through hole assembly technologies
Experience with IPC 610 & ISO 9000 standards
Working knowledge of ERP systems, SAP preferred
Lean or Six Sigma Green Belt certification

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Additive Manufacturing Engineering Lab Manager

Lockheed Martin

Fort Worth, TX 76108

~ 44 min OnsiteUrgently HiringFlexible SchedulePaid Time Off

MUST BE A U.S. CITIZEN
This position is located at a facility that requires special access
The selected candidate must be able to obtain a secret clearance
Engineering or other technical bachelor's degree (STEM)
≥8 years of technical experience in metal and polymer additive manufacturing/3D printing technology, preferably in aerospace or defense
Demonstrated success in developing technology roadmaps and securing funding for R&D; projects
Technical leadership capability within challenging technical, cost, and schedule constraints
Strong knowledge of AM processes and material certification for aerospace applications
Team leadership experience in a dynamic, fast-paced environment
Demonstrated collaboration with internal and external customers, DoD labs, and other government agencies on research and development, including CRAD
Demonstrated collaboration with cross-functional teams, including engineering, manufacturing, and supply chain management, to ensure successful integration and identify and mitigate potential risks and issues
Demonstrated skills in conflict resolution, proactive communication, and building collaborative relationships
Experience with development of air vehicle products
Experience preparing and delivering presentations to internal leadership and external customers
Experience with strategic technical planning and proposal development
Knowledge of Earned Value Management
Planning and management of personnel resources, staff development and capital resources. Including recruitment, selection, training, assignments, performance, merit planning, recognition and disciplinary actions
Experience supporting classified and sensitive programs
Schedule: 4x10 hour day, 3 days off per week
Onsite Full-time: The work associated with this position will be performed onsite at a designated Lockheed Martin facility

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Principal Engineer - Python API Development

Fidelity Investments

Irving, TX 75061

~ 22 min OnsiteUrgently HiringEducation 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.

New, Posted 1 day ago

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Lean Manufacturing Engineer

Teledyne

Garland, TX 75040

~ 26 min OnsiteUrgently HiringEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Associate's degree in engineering (Mechanical, Electrical, Materials, Industrial, or related discipline) - required
7-8 years of experience in manufacturing engineering, process development, or continuous improvement - required
Hands-on experience with microelectronics or high-reliability manufacturing processes such as wire bonding, die attach, hermetic sealing, welding, or precision assembly - required
Strong cross-functional communication skills with the ability to coordinate engineering, quality, and manufacturing teams - required
Ability to manage multiple technical initiatives, track actions and risks, and drive timely closure - required

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New, Posted 17 hours ago

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Principal Engineer - Python API Development

Fidelity Investments

Southlake, TX 76092

~ 36 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.

SmartExplore AI is experimental.

New, Posted 1 day ago

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Manufacturing Engineer

Teledyne

Garland, TX 75040

~ 26 min OnsiteUrgently HiringFlexible 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
Strong electro-mechanical troubleshooting skills - required
PC literate - required
Ability to travel "as required" to customer site(s) to provide technical support and training

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Senior Specialist, Manufacturing Engineering

L3 Harris

Richardson, TX 75080

~ 18 min OnsiteUrgently HiringBilingual Preferred

Bachelor's Degree and minimum 6 years of prior Manufacturing Engineering experience
Graduate Degree and a minimum of 4 years of prior Manufacturing Engineering experience
In lieu of a degree, minimum of 10 years of prior Manufacturing Engineering experience
Security clearances may only be granted to U.S. citizens
All applicants will be considered for employment without regard to race, color, religion, age, national origin, ancestry, ethnicity, gender (including pregnancy, childbirth, breastfeeding or other related medical conditions), gender identity, gender expression, sexual orientation, marital status, veteran status, disability, genetic information, citizenship status, characteristic or membership in any other group protected by federal, state or local laws
L3Harris maintains a drug-free workplace and performs pre-employment substance abuse testing and background checks, where permitted by law
L3Harris is proud to be an Equal Opportunity Employer

SmartExplore AI is experimental.

New, Posted 1 day ago

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