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Ai Model Training Jobs (NOW HIRING)

SmartIPlace

Lead AI Engineer or Architect[Hybrid]

Atlanta, GA · On-site

$53.25 - $72.75/hr

USC, GC, GC-EAD, H4-EAD Mandatory Skills: • Lead the team • Platform • Pipelines Automation (Data Pipelines, AI / Model Training Pipelines, Deploying Application, Models Automation through ...

Globe Telecom, Inc.

AI Cloud Engineer

Globe, AZ

$53 - $70.75/hr

AI Integration & Model Deployment * Work closely with AI teams to build and manage cloud-based environments for AI model training, validation, and deployment. * Develop and maintain CI/CD pipelines ...

IntraEdge

AI Data Engineer

Detroit, MI

$113K - $136K/yr

Deploy AI models: Automate the training and deployment of AI/ML models into production via APIs and microservices. * Monitor and troubleshoot: Implement data observability tools to monitor pipeline ...

Gallatin AI, Inc

AI Software Engineer

El Segundo, CA · On-site

$80K - $210K/yr

We build AI systems that determine how logistics decisions are made - not just how they're executed ... Establish scalable MLOps pipelines and real-time inference services to streamline model training ...

Mercor

AI Research Scientist - PhD

San Francisco, CA · Remote

$55 - $80/hr

Evaluate and improve AI model training and outputs to ensure accuracy and depth. * Collaborate with AI research teams to enhance training data quality and performance. * Work independently and ...

Merlin Labs

Director, AI Core Software

Boston, MA · On-site

$274K/yr

Own the architecture of the AI Core stack from data pipelines and model training infrastructure through to real-time onboard inference and control. * Establish and enforce engineering standards, code ...

Merlin Labs

Director, AI Core Software

Boston, MA

$274K/yr

Own the architecture of the AI Core stack from data pipelines and model training infrastructure through to real-time onboard inference and control. * Establish and enforce engineering standards, code ...

Nvidia

Solutions Architect, AI Models

Santa Clara, CA

$74 - $97.50/hr

Tackle sophisticated AI challenges by applying skills across the AI model lifecycle-from data processing and orchestration to training, post-training, reinforcement learning (RL), evaluation, and ...

Archer

Senior AI Systems Engineer

San Jose, CA · On-site

$160K - $180K/yr

Deploy, scale, and manage resilient infrastructure services tailored for distributed AI model training and low-latency inference. * Maturity & MLOps: Utilize and maintain end-to-end tooling-including ...

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Ai Model Training information

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How much do ai model training jobs pay per hour?

As of Jun 30, 2026, the average hourly pay for ai model training in the United States is $31.37, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $39.18 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Ai Model Training position, and why are they important?

To excel in AI Model Training, you need a strong background in machine learning, programming (especially Python), data analysis, and a relevant degree such as computer science or engineering. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud computing platforms, and certifications in AI or data science are highly advantageous. Strong problem-solving skills, attention to detail, and the ability to communicate complex ideas effectively make candidates stand out. These competencies are crucial for developing accurate, efficient AI models and collaborating seamlessly within multidisciplinary teams.

What are the typical work responsibilities of someone in AI Model Training?

Professionals in AI Model Training are typically responsible for collecting, preparing, and processing large datasets, designing and implementing machine learning models, and evaluating their performance using statistical methods. You may work closely with data engineers, software developers, and product managers to ensure models meet business objectives and integrate smoothly into existing systems. Regular responsibilities also include tuning hyperparameters, troubleshooting model issues, and staying up-to-date with the latest advancements in AI. This role often involves a mix of independent technical work and collaborative problem-solving sessions with the broader team.

What is an AI Model Training job?

An AI Model Training job involves preparing, training, and optimizing machine learning models using data. Professionals in this role preprocess datasets, select appropriate algorithms, adjust model parameters, and evaluate performance to improve accuracy. They work with frameworks like TensorFlow or PyTorch and may fine-tune models for specific tasks such as image recognition or natural language processing. This job requires expertise in data science, programming, and statistical analysis to ensure models perform efficiently in real-world applications.

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What cities are hiring for Ai Model Training jobs? Cities with the most Ai Model Training job openings:
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Ai Model Training jobs near you
Infographic showing various Ai Model Training job openings in the United States as of June 2026, with employment types broken down into 11% Internship, 45% Full Time, 22% Part Time, and 22% Contract. Highlights an 33% In-person, and 67% Remote job distribution, with an average salary of $65,246 per year, or $31.4 per hour.
Product Manager, AI Platforms (R4991)

Product Manager, AI Platforms (R4991)

Shield AI

San Diego, CA • On-site

Full-time

Posted 23 days ago

Key responsibilities

  • Own the roadmap for foundation model training workflows, including dataset ingestion, curation, labeling, synthetic data generation, and training pipelines.

  • Lead the development of model governance and auditability tooling, including model cards, dataset rights, lineage tracking, safety gates, and compliance evidence.

  • Collaborate with Engineering, Research, Product, Customer Engagement, and Solutions teams to ensure model outputs meet mission and platform constraints.

Job description

Founded in 2015, Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software and V-BAT and X-BAT aircraft. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
Job Description:
The AI Platform Product Manager will drive the strategy and execution of Shield AI's next-generation autonomy intelligence stack-enabling customers and internal teams to train, evaluate, and deploy foundation and domain models that power resilient autonomy at the edge. This PM owns the product vision and roadmap for the Hivemind AI Platform (Forge, training pipelines, data infrastructure, evaluation, and deployment toolchains), ensuring we can manufacture, govern, and field advanced world models, robotics foundation models, and vision-language-action systems safely and at scale.
This role sits at the intersection of AI/ML, autonomy, model lifecycle, infrastructure, and product strategy. The PM partners closely with engineering, AI research, Hivemind Solutions, and field teams to deliver the tooling that enables sovereign autonomy, AI Factories at the edge, and continuous learning-capabilities that are central to Shield AI's strategic direction.
This is a high-impact role for an experienced product leader excited to define how foundation models are trained, validated, governed, and deployed across thousands of autonomous systems in highly contested environments.
What you'll do:
  • AI Model Development & Training Platform
  • Own the roadmap for foundation model training workflows, including dataset ingestion, curation, labeling, synthetic data generation, domain model training, and distillation pipelines.
  • Define requirements for world models, robotics models, and VLA-based training, evaluation, and specialization.
  • Lead the evolution of MLOps capabilities in Forge, including data lineage, experiment tracking, model versioning, and scalable evaluation suites.
  • Data, Simulation & Synthetic Data Factory
  • Define product requirements for synthetic data generation, simulation-integrated data flywheels, and automated scenario generation.
  • Partner with Digital Twin, Simulation, and autonomy teams to convert natural-language mission inputs into data needs, training procedures, and model variants.
  • Safe Deployment & Model Governance
  • Lead the development of model governance and auditability tooling, including model cards, dataset rights, lineage tracking, safety gates, and compliance evidence.
  • Build guardrails and workflows to safely deploy models onto edge hardware in disconnected, GPS- or comms-denied environments.
  • Partner with Safety, Certification, Cyber, and Engineering teams to ensure traceability and evaluation pipelines meet operational and accreditation requirements.
  • Edge Deployment & AI Factory Integration
  • Partner with Pilot, EdgeOS, and hardware teams to integrate foundation-model-based perception and reasoning into autonomy behaviors.
  • Define requirements for distillation, quantization, and inference tooling as part of the "three-computer" development and deployment model.
  • Ensure closed-loop workflows between cloud model training and edge-native execution.
  • Cross-Functional Leadership
  • Collaborate with Engineering, Research, Product, Customer Engagement, and Solutions teams to ensure model outputs meet mission and platform constraints.
  • Translate advanced AI capabilities into intuitive workflows that platform OEMs and partner nations can use to build sovereign AI factories.
  • Sequence foundational capabilities that unblock autonomy, simulation, and customer-facing product teams.
  • User & Customer Impact
  • Develop deep empathy for ML engineers, autonomy developers, and Solutions engineers who rely on the platform.
  • Capture operational data gaps, mission-driven model needs, and domain-specific specialization requirements.
  • Lead demos and onboarding for model-development capabilities across internal and external teams.

Required qualifications:
  • 7+ years of experience in product management or highly technical ML/AI product roles.
  • 2+ years of experience in a hands-on software development role.
  • Strong engineering background (Computer Science, Electrical Engineering, Robotics, or related field).
  • Deep understanding of foundation models, robotics models, multimodal models, MLOps, and training infrastructure.
  • Experience managing complex products spanning data pipelines, cloud training clusters, model governance, and edge deployments.
  • Proven success partnering with research teams to transition ML innovations into stable, production-grade workflows.
  • Familiarity with simulation-based data generation and large-scale data management.
  • Excellent communicator with strong cross-functional leadership skills.

Preferred qualifications:
  • Experience working on autonomy, robotics, embedded AI, or mission-critical systems.
  • Hands-on familiarity with GPU infrastructure, distributed training, or data lakehouse architectures.
  • Experience supporting defense, dual-use, or safety-critical AI systems.
  • Background designing or operating AI Factory-style pipelines (data - training - evaluation - distillation - edge deployment).
  • Advanced degree in engineering, ML/AI, robotics, or a related field.

$190,000 - $290,000 a year
#LI-DM2
#LE
Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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