1101 Hardware Design Engineer jobs in Flower Mound,TX

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Applied Early Career Program - Field Service Engineer

Applied Materials - Dallas, TX

Applied Early Career Program - Field Service Engineer

Paid Relocation to Dallas, TX

Requires Travel

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IT Architect II-IM Application Development

CHRISTUS Health

Irving, TX 75039

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Technical Writer - Level 3

Lockheed Martin

Fort Worth, TX 76137

~ 41 min OnsiteFlexible Schedule

3-6 years of professional technical writing experience in aerospace, defense, or a similarly regulated industry; direct exposure to joint or multi‑agency programs preferred.
Familiarity with systems engineering concepts, system architecture, and/or basic hardware/software terminology; ability to read schematics, block diagrams, and/or software code excerpts.
Bachelor's degree in Engineering, Computer Science, Technical Communication, or a related technical field.
Ability to obtain and maintain a Secret (or higher) clearance as required by the program.
This position requires a government security clearance, you must be a US Citizen for consideration.
Clearance Level: Secret

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Principal Engineer - Python API Development

Fidelity Investments

Flower Mound, TX 75027

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.

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New, Posted 1 day ago

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Vice President Development, Design & Construction

Lifespace Communities

Coppell, TX 75019

$235,200-$341,200/yr

~ 20 min Onsite

Bachelor's degree in Architecture, Engineering, Construction Management, Real Estate Development, or a related field
15+ years of progressive leadership experience managing large-scale capital development, design, construction, or facilities programs
Executive experience overseeing multimillion-dollar redevelopment or new construction portfolios
Expertise in project management, contract negotiation, budgeting, construction administration, and owner representation
Strong knowledge of building systems, codes, regulatory requirements, and capital planning
Demonstrated ability to lead diverse teams of architects, engineers, developers, consultants, and contractors
Exceptional executive presence with the ability to influence senior leadership and boards

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Principal Engineer - Python API Development

Fidelity Investments

Highland Village, TX 75077

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.

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Information Technology Professional (IT Support)

U.S. Navy

Flower Mound, TX 75028

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Travel Cytotechnologist - $2,411 per week

Trustaff Allied

Dallas, TX 75215

$2,411/wk

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Tool Planner / Manufacturing Engineer (Level 2)

Lockheed Martin

Grand Prairie, TX 75051

Hybrid~ 38 minFlexible Schedule

Bachelor's degree or equivalent experience
Ability to communicate effectively
High attention to detail
Knowledge of tool design
Microsoft Office experience
General knowledge of mechanical manufacturing processes
Experience with PLM, MRP, & ERP systems is preferred
Expression of Interest: By applying to this job, you are expressing interest in this position and could be considered for other career opportunities where similar skills and requirements have been identified as a match. Should this match be identified you may be contacted for this and future openings.
Schedule for this Position: 4x10 hour day, 3 days off per week
Relocation Available: Possible
Part-time Remote Telework: The employee selected for this position will work part of their work schedule remotely and part of their work schedule at a designated Lockheed Martin facility. The specific weekly schedule will be discussed during the hiring process.

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New, Posted 9 hours ago

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