1

Llmops Jobs (NOW HIRING)

Lead AI Engineer (ML Ops)

Stamford, CT · On-site

$109K - $144K/yr

High proficiency in MLOps and LLMOps platforms (e.g., MLflow, Kubeflow, Weights & Biases). * Strong DevOps background, including hands-on experience with containerization (Docker, Kubernetes) and CI ...

Lead AI Engineer (ML Ops)

Irving, TX · On-site

$98K - $129K/yr

High proficiency in MLOps and LLMOps platforms (e.g., MLflow, Kubeflow, Weights & Biases). * Strong DevOps background, including hands-on experience with containerization (Docker, Kubernetes) and CI ...

Implement and manage LLMOps workflows, including deployment, monitoring, and scaling of Generative AI systems * Build and maintain agent-based workflows using frameworks like LangChain, CrewAI, or ...

Implement and manage LLMOps workflows, including deployment, monitoring, and scaling of Generative AI systems * Build and maintain agent-based workflows using frameworks like LangChain, CrewAI, or ...

Lead AI Engineer (ML Ops)

Irving, TX · Hybrid

$98K - $129K/yr

High proficiency in MLOps and LLMOps platforms (e.g., MLflow, Kubeflow, Weights & Biases). * Strong DevOps background, including hands-on experience with containerization (Docker, Kubernetes) and CI ...

Cloud Platform Engineer

Charlotte, NC · On-site

$54.50 - $72.75/hr

MLOps / LLMOps pipelines Key Responsibilities (Keywords for Search): * Build enterprise cloud platforms (GCP + Azure) * Implement Terraform-based reusable modules * Design landing zones & governance ...

Senior AI Engineer

Concord, MA · On-site

$114K - $157K/yr

Apply MLOps and LLMOps best practices: monitoring, evaluation, prompt versioning, cost/performance optimization. * Combine traditional AI/ML with modern GenAI approaches to deliver hybrid solutions ...

Apply LLMOps/MLOps practices, including CI/CD pipelines, prompt/version management, automated testing, and monitoring of latency, cost, and response quality. * Develop systems leveraging embeddings ...

Design scalable MLOps / LLMOps / AgentOps foundations: * CI/CD for AI and agent workflows * Observability, telemetry, and quality measurement * Versioning, monitoring, drift detection, and retraining ...

Establish and maintain LLMOps practices, including prompt management, model evaluation, regression testing, observability, and reliability monitoring. * Implement controls for entitlements ...

LLMOps & Testing: * Apply LLMOps best practices for lifecycle management of large language models, including CI/CD pipelines, monitoring, and governance. * Develop and execute testing strategies for ...

Design scalable MLOps / LLMOps / AgentOps foundations: * CI/CD for AI and agent workflows * Observability, telemetry, and quality measurement * Versioning, monitoring, drift detection, and retraining ...

Experience with MLOps/LLMOps tooling and practices (model registry, CI/CD, feature store, prompt/chain/versioning, evaluation, guardrails, monitoring). Strong communication skills with the ability to ...

next page

Showing results 1-20

Llmops information

What jobs can I do with LLM?

With expertise in large language models (LLMs), you can pursue roles such as NLP engineer, machine learning engineer, data scientist, or AI researcher. These jobs typically require skills in programming, deep learning frameworks, and understanding of natural language processing concepts.

What engineer makes $500,000 a year?

Senior machine learning engineers, including those working in Llmops or related AI fields, can earn $500,000 or more annually, especially with extensive experience, specialized skills, and working at top tech companies or in high-demand industries. Compensation often includes base salary, bonuses, and stock options, reflecting expertise in large language models, cloud platforms, and deployment tools.

What jobs make $3,000 a day?

In the context of Llmops, high-paying roles such as AI project managers, machine learning engineers, or data science consultants can earn around $3,000 daily, especially with specialized skills, certifications, and experience in deploying large language models. These roles often require advanced technical knowledge, experience with cloud platforms, and the ability to manage complex AI operations in a fast-paced environment.

What is the difference between Llmops vs Data Scientist?

AspectLlmopsData Scientist
Required credentialsKnowledge of machine learning, AI frameworks, cloud platformsStatistics, programming, data analysis skills
Work environmentAI/ML teams, cloud environments, deployment pipelinesData analysis, modeling, reporting in various industries
Employer usageTech companies, AI startups, research labsFinance, healthcare, tech, retail

While both roles involve working with data and machine learning, Llmops focuses on deploying and maintaining large language models in production environments, requiring expertise in AI infrastructure. Data Scientists primarily analyze data, build models, and generate insights. Llmops professionals ensure models operate efficiently at scale, whereas Data Scientists develop the models and interpret results.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in deep learning, data science, and programming. These roles usually involve leadership, strategic planning, and expertise with tools like TensorFlow or PyTorch, and may include performance-based bonuses or stock options. Such salaries are rare and generally found in top tech companies or specialized AI firms.
More about Llmops jobs
What cities are hiring for Llmops jobs? Cities with the most Llmops job openings:
What states have the most Llmops jobs? States with the most job openings for Llmops jobs include:
Infographic showing various Llmops job openings in the United States as of June 2026, with employment types broken down into 96% Full Time, and 4% Contract. Highlights an 79% Physical, 7% Hybrid, and 14% Remote job distribution.
Lead AI Engineer (ML Ops)

Lead AI Engineer (ML Ops)

Gartner

Stamford, CT • On-site

$109K - $144K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 21 days ago


Job description

About Gartner IT

Join a world-class team of forward-thinking engineers dedicated to delivering innovative digital solutions that empower our analysts and clients. At Gartner IT, we drive organizational transformation through advanced technology, fostering a culture of continuous innovation, outcome-oriented execution, and the belief that impactful ideas can originate from any team member.

About the Role: Lead AI Engineer

We are seeking a Lead AI Engineer to spearhead the end-to-end productionalization of AI initiatives across Gartner. This pivotal role blends deep expertise in AI engineering with hands-on experience in MLOps, LLMOps, and DevOps, enabling the design, deployment, and scaling of enterprise-grade AI solutions that underpin our Consulting & Insight Technology strategy.

Key Responsibilities:

  • Lead the full lifecycle of AI/ML model productionalization, establishing resilient MLOps and LLMOps pipelines for seamless model deployment, orchestration, and monitoring at scale.

  • Architect and implement scalable AI infrastructure and deployment strategies, ensuring robust integration with enterprise platforms and data ecosystems.

  • Define and enforce best practices for AI model lifecycle management, including version control, automated testing, monitoring, and CI/CD processes.

  • Build and maintain production-ready AI systems, driving the integration of advanced analytics and machine learning into core business processes.

  • Champion technical design sessions, mentor engineering teams, and cultivate expertise in modern AI engineering and MLOps tooling.

  • Develop and maintain automated frameworks for model validation, performance monitoring, and drift detection in production environments.

  • Collaborate closely with data science teams to operationalize experimental models, transforming prototypes into reliable, scalable solutions.

  • Continuously evaluate and adopt emerging technologies in AI engineering, MLOps, and LLMOps to enhance organizational AI capabilities.

  • Author comprehensive technical documentation, uphold coding standards, and ensure adherence to enterprise security, compliance, and governance requirements.

Required Qualifications:

  • 4+ years of progressive experience in AI/ML engineering, with a proven track record of deploying and scaling AI solutions in production environments.

  • High proficiency in MLOps and LLMOps platforms (e.g., MLflow, Kubeflow, Weights & Biases).

  • Strong DevOps background, including hands-on experience with containerization (Docker, Kubernetes) and CI/CD pipeline automation.

  • Advanced programming skills in Python, with deep familiarity in ML frameworks (TensorFlow, PyTorch, Scikit-learn).

  • Proficient in leveraging cloud platforms (AWS, Azure, GCP) and their native AI/ML services.

  • Solid experience in infrastructure as code (Terraform, CloudFormation) and configuration management.

  • Expertise in model monitoring, drift detection, and performance optimization for production models.

  • Strong understanding of data engineering pipelines and real-time data processing architectures.

  • Experience designing and developing APIs and working within microservices architectures.

Preferred Qualifications:

  • Experience deploying Large Language Models (LLMs) and Generative AI solutions.

  • Knowledge of AI governance, model explainability, and responsible AI practices.

  • Exposure to edge computing and advanced model optimization techniques.

  • Familiarity with vector databases and retrieval-augmented generation (RAG) architectures.

  • Experience with data mesh architectures and modern data stack technologies.

  • Background in Agile/Scrum methodologies and technical team leadership.

Who You Are:

  • Effective at managing time and meeting deadlines while leading complex AI initiatives.

  • Exceptional communicator, adept at engaging with technical teams, data scientists, and business stakeholders.

  • Highly organized, with strong multitasking, prioritization, and leadership abilities.

  • Eager to embrace and master emerging AI technologies and complex concepts rapidly.

  • Driven by intellectual curiosity and a passion for advancing AI engineering practices.

  • Demonstrated ability to deliver enterprise-scale AI projects on time, within budget, and to the highest standards of quality and reliability.

What you'll receive:

  • Competitive compensation.

  • Limitless growth and learning opportunities.

  • A collaborative and positive culture - join a diverse team of professionals that are as smart and driven as you.

  • A chance to make an impact - your work will contribute directly to our strategy.

  • Enjoy the flexibility of working from home and the energy of collaborating with peers in our dynamic offices.

  • 20+ PTO days plus holidays and floating holidays in your first year.

  • Extensive medical, dental insurance and vision plan.

  • 401K with corporate match, immediate vesting.

  • Health-and-wellness-related allowance programs.

  • Parental leave.

  • Tuition reimbursement.

  • Employee Stock Purchase Plan.

  • Employee Assistance Program.

  • Gartner Gives Charity Match.

And much more!

What are we:

  • Action Oriented - Deliver fast, get great results. We embrace the vision, roadmap to success and the action it takes to make it happen.

  • Intellectually Curious - Seek to learn, love to teach. We're humble and embrace respectful, radical candor with a mindset of ongoing professional and personal development.

  • Collaborative - One team, shared mission. We welcome feedback and understand the value of working together to accomplish more than what is possible individually.

#LI-JD6

#LI-Hybrid

#LI-Technology

Who are we?

At Gartner, Inc. (NYSE:IT), we guide the leaders who shape the world.

Our mission relies on expert analysis and bold ideas to deliver actionable, objective business and technology insights, helping enterprise leaders and their teams succeed with their mission-critical priorities.

Since our founding in 1979, we've grown to 20,000 associates globally who support over 13,000 client enterprises in ~90 countries and territories. We do important, interesting and substantive work that matters. That's why we hire associates with the intellectual curiosity, energy and drive to want to make a difference. The bar is unapologetically high. So is the impact you can have here.

What makes Gartner a great place to work?

Our vast, virtually untapped market potential offers limitless opportunities - opportunities that may not even exist right now - for you to grow professionally and flourish personally. How far you go is driven by your passion and performance.

We hire remarkable people who collaborate and win as a team. Together, our singular, unifying goal is to deliver results for our clients.

Our teams are inclusive and composed of individuals from different geographies, cultures, religions, ethnicities, races, genders, sexual orientations, abilities and generations.

We invest in great leaders who bring out the best in you and the company, enabling us to multiply our impact and results. This is why, year after year, we are recognized worldwide as a great place to work.

Gartner is the world authority on AI

At Gartner, you'll join a company at the very center of the AI revolution. Gartner has proactive, objective guidance throughout clients' AI journeys. We set the standard for how organizations leverage artificial intelligence to drive meaningful impact. You'll have access to unmatched resources, expertise, and technology, and play a key role in helping Gartner and our clients innovate and grow as we leverage AI to transform business and technology landscapes.

It's an exciting time to be at Gartner, with limitless opportunities to make a real impact, grow your skills, and build a lasting, meaningful career in a field that's reshaping the way we operate. If you're passionate about AI and want to be part of a team that's guiding the leaders who shape the world, Gartner is the place for you.

What do we offer?

Gartner offers world-class benefits, highly competitive compensation and disproportionate rewards for top performers.

In our hybrid work environment, we provide the flexibility and support for you to thrive - working virtually when it's productive to do so and getting together with colleagues in a vibrant community that is purposeful, engaging and inspiring.

Ready to grow your career with Gartner? Join us.

Gartner believes in fair and equitable pay. A reasonable estimate of the base salary range for this role is 116,000 USD - 170,000 USD. Please note that actual salaries may vary within the range, or be above or below the range, based on factors including, but not limited to, education, training, experience, professional achievement, business need, and location. In addition to base salary, employees will participate in either an annual bonus plan based on company and individual performance, or a role-based, uncapped sales incentive plan. Our talent acquisition team will provide the specific opportunity on our bonus or incentive programs to eligible candidates. We also offer market leading benefit programs including generous PTO, a 401k match up to $7,200 per year, the opportunity to purchase company stock at a discount, and more.


The policy of Gartner is to provide equal employment opportunities to all applicants and employees without regard to race, color, creed, religion, sex, sexual orientation, gender identity, marital status, citizenship status, age, national origin, ancestry, disability, veteran status, or any other legally protected status and to seek to advance the principles of equal employment opportunity.

Gartner is committed to being an Equal Opportunity Employer and offers opportunities to all job seekers, including job seekers with disabilities. If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access the Company's career webpage as a result of your disability. You may request reasonable accommodations by calling Human Resources at +1 (203) 964-0096 or by sending an email toApplicantAccommodations@gartner.com.

Job Requisition ID:106820

By submitting your information and application, you confirm that you have read and agree to the country or regional recruitment notice linked below applicable to your place of residence.

Gartner Applicant Privacy Link: https://jobs.gartner.com/applicant-privacy-policy


For efficient navigation through the application, please only use the back button within the application, not the back arrow within your browser.