856 Aiml Engineer Staffing jobs in Haslet,TX

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Manufacturing Engineer (Level 2)

Lockheed Martin

Grand Prairie, TX 75051

~ 40 min OnsiteFlexible SchedulePaid Time Off

1+ years of related experience
Bachelor's degree in Manufacturing Engineering Technology or similar field
Experienced with tooling (fixtures, cutters, and other manufacturing equipment) and CNC machining processes
Experience reducing defects and increasing productivity/throughput
Proven track record of data driven approach to solving problems
MUST BE A U.S. CITIZEN
Secret clearance
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

Euless, TX 76039

~ 29 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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Principal Engineer - Python API Development

Fidelity Investments

Colleyville, TX 76034

~ 31 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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Inspector I Quality Control

Smiths Group

Irving, TX 75061

~ 36 min Onsite

Time management skills.
Must be adaptable to a changing work environment, completing jobs and must be able to deal with frequent change, delays, or unexpected events.
Attention to details and ability to focus on assignment.
Knowledge of reading engineering technical drawings, including GD&T; callouts
Effective English communication skills, including writing.
Knowledge of inspection tools (i.e. scopes, calipers, micrometers, etc) along with ability to focus for an extended amount of time while using microscope.
Have good computer skills and able to use Microsoft office products.

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Principal Engineer, IT Software

American Airlines

Fort Worth, TX 76101

New, Posted 17 hours ago

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Director, AI Strategy Architect

KPMG

Dallas, TX 75217

~ 50 min OnsiteHealth InsuranceRetirement Benefit

Minimum eight years of recent experience in AI/ML, data analytics, and cloud technology, including leadership roles in consulting or technology organizations; AI certifications (for example: Professional AI Architect, Machine Learning Engineer) or equivalent are a plus
Advanced degree from an accredited college or university in computer science, data science, engineering, or related field preferred; minimum of a Bachelor's degree from an accredited college or university is required
Deep knowledge and hands-on experience with Microsoft, AWS, and/or Google Cloud's AI ecosystem (including agent build functionality) to design and orchestrate intelligent multi-agent systems, integrating complex RAG pipelines, and connecting GenAI to proprietary enterprise data (Knowledge Graphs, Vector Databases) that handle complex, dynamic tasks and conversations
Proficient in architecting and implementing AI-powered workflow solutions using Microsoft, AWS, or Google Cloud services (For example: Foundry, Bedrock, Vertex AI), and demonstrating a strong grasp of model-agnostic architectures leveraging both proprietary and open-weight foundational models for scalable, automated systems with expertise in agentic AI and automation
Skilled in designing multi-agent conversational and autonomous AI systems integrated with enterprise applications (CRM, ERP), enhancing customer engagement through smart chatbots and virtual agents to improve user experience and operational efficiency; experienced in conversational AI integration
Deep understanding of scaling AI-driven solutions, GenAIOps/LLMOps (including LLM evaluation frameworks, prompt versioning, routing, and cost optimization), AI governance, and MLOps practices for maintaining models; ability to bring industry consulting insights with a balance of technical and business acumen to deliver strategic, value-driven AI solutions; In-depth knowledge of AI orchestration and best practices
Travel as needed
Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future; KPMG LLP will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa)

SmartExplore AI is experimental.

New, Posted 17 hours ago

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Director, Private Equity IT M&A –Due Diligence and Value Creation

KPMG

Dallas, TX 75217

~ 50 min OnsiteHealth InsuranceRetirement Benefit

Minimum eight years of recent experience in technology
Strong preference for candidates who have held in-house technology leadership roles(such as CIO, CTO, VP-Engineering) within a PE-backed company or a high-growthtech firm; consulting experience focused on the PE sector is also valuable
Master's of Business Administration degree from an accredited college or university is preferred
Minimum of a Bachelor's degree in Information Systems, Computer Science, Finance, or a related field is required
Demonstrated success in leading high-impacttechnology projects in areas such as IT due diligence, technology valuecreation, post-merger integration, or IT architecture modernization
Proven ability to leverage AI-powered tools and platforms to accelerate due diligence,identify opportunities, and enhance project delivery
Proven track record operating in the fast-paced, high-stakesenvironment of Private Equity, leading technology engagements from pre-deal diligence through post-close value creation
Experience with portfoliocompanies in sectors such as Technology, Software, and other tech-enabledindustries is highly preferred
Comprehensive understanding of modern enterprise ITecosystems, including cloud platforms, business applications, infrastructure,and cybersecurity; familiarity with the security, data privacy, andconsiderations of implementing AI/ML solutions
Experience developing and executing go-to-market strategies anddriving business growth, specifically by building and nurturing relationshipswith PE operating partners and deal teams
Willingnessand ability to travel as needed to serve client needs
Mustbe authorized to work in the U.S. without the need for employment-based visasponsorship now or in the future

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

Corning

Keller, TX 76248

~ 18 min OnsiteUrgently HiringHealth 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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Manufacturing Engineer

Megger

Dallas, TX 75217

~ 50 min Onsite

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

SmartExplore AI is experimental.

New, Posted 22 hours ago

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Manufacturing Engineer Sr

Lockheed Martin

Grand Prairie, TX 75051

~ 40 min OnsiteFlexible Schedule

Bachelor's degree in Mechanical, Electrical, Manufacturing or other STEM engineering degree
Experience in a manufacturing environment, with a proven record of influencing production processes through process improvement initiatives
Strong project- and time-management skills to effectively coordinate multiple concurrent activities and deliver results on tight program schedules.
Demonstrated effective communication & interpersonal skills (verbal, written, presentation) and relationship‑building with customers, suppliers, and internal disciplines
Ability to obtain a security clearance.
MUST BE A U.S. CITIZEN - This position is located at a facility that requires special access. The selected candidate must possess an active Secret clearance to start.
This position requires a government security clearance, you must be a US Citizen for consideration.

SmartExplore AI is experimental.