730 Aiml Engineer Information Technology jobs in Little Elm,TX

Principal Engineer - Python API Development

Fidelity Investments

Fort Worth, TX 76102

~ 58 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.

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Information Technology Professional (IT Support)

U.S. Navy

Plano, TX 75025

New, Posted 1 hour ago

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Principal Engineer, IT Systems Engineering

American Airlines

Fort Worth, TX 76101

~ 58 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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Information Technology Professional (IT Support)

U.S. Navy

St Paul, TX 75098

New, Posted 1 day ago

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Principal Engineer - Python API Development

Fidelity Investments

Keller, TX 76244

~ 50 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.

Apply Directly

Manufacturing Engineer

DEAN TECHNOLOGY

Addison, TX 75001

OnsiteHealth InsuranceRetirement Benefit

Education: BSEE/BSME/BSMechE and 5+ years' experience, or the equivalent of 10 years' experience in manufacturing engineering, with electronics background.
Skills / Technical Knowledge / Experience: Working knowledge of mechanical assemblies, tooling, fixtures, tolerances, and assembly drawings.
Skills / Technical Knowledge / Experience: Requires knowledge of fabrication processes, material specification, and general industrial operations.
Skills / Technical Knowledge / Experience: Must be a business minded engineer to provide continuous improvements to products and processes.
Skills / Technical Knowledge / Experience: Must be proficient with program management tools and have the ability to manage and prioritize multiple projects, tasks, and assignments at once.
Must be eligible to work in the United States without sponsorship.

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New, Posted 1 day ago

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Lead Engineer - Operational Technology Network Security

AmerisourceBergen Corporation (Cencora)

Carrollton, TX 75006

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Skunkworks Staff Manufacturing Engineer (Level 4)

Lockheed Martin

Fort Worth, TX 76108

Paid Relocation to Fort Worth, TX

~ 58 min OnsiteFlexible ScheduleEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelors degree required to apply
Experience in a manufacturing environment working cross functionally with other disciplines including industrial engineering, planning, scheduling, Quality Assurance &/or production operations.
Experience supporting vehicle systems installations & integration into a final product and/or rigging experience for moveable surfaces. Experience should include some combination of the following systems: electrical harness installation, fuel systems, hydraulic systems, related systems, landing gear, and door rigging.
Active secret security clearance, with investigation in the last 5 years.
Ability to obtain special program access within 3 months of start date with LM.
Ability to travel 25 - 75% of the time, or based on business needs.
This position requires a government security clearance, you must be a US Citizen for consideration.
Clearance Level: Secret with Investigation or CV date within 5 years

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L-Manufacturing Engineer

The Crosby Group

Richardson, TX 75080

~ 33 min Onsite

Engineering B.S. required
2-7 years related
Proficient in design of tooling, manufacturing systems, and project management
CAM programming
Microsoft Word, Excel and PowerPoint
Ability to use precision measurement devices and knowledge of engineering drawings, blueprints and tolerances
Oral and written communication proficiency
PLC and controls experience preferred
Travel is required occasionally (driving/flying)
Must be able to work necessary hours to accomplish or complete job tasks. Occasional 50+ hour work week may be required
Exposure to moving mechanical parts, fumes, or airborne particles typical to a manufacturing environment
Familiar with CAD system and proficient with one AutoCAD compatible system or computer aided machining program

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Senior Specialist, Manufacturing Engineering

L3 Harris

Richardson, TX 75080

~ 33 min OnsiteBilingual 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.