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Senior Llm Developer Jobs (NOW HIRING)

Sr. AI/ML Engineer (LLM)

Miami, FL · On-site

$99K - $137K/yr

Role Description This is a full-time, on-site role located in Miami, FL, for a Senior AI/ML ... Collaborate with product managers, data scientist, and software engineers to integrate LLM-based ...

Senior AI Engineer - LLM, RAG

Palo Alto, CA · On-site

$123K - $168K/yr

They are seeking a Senior AI Engineer to lead the development of Retrieval-Augmented Generation ... LLM applications. • Design evaluation strategies to measure performance, accuracy, and user ...

Senior AI Engineer - LLM, RAG

Palo Alto, CA · On-site

$123K - $168K/yr

They are seeking a Senior AI Engineer to lead the development of Retrieval-Augmented Generation ... LLM applications. • Design evaluation strategies to measure performance, accuracy, and user ...

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Senior Llm Developer information

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$25K

$80.3K

$163.5K

How much do senior llm developer jobs pay per year?

As of Jul 22, 2026, the average yearly pay for senior llm developer in the United States is $80,287.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,500.00 and $103,000.00 per year, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior LLM (Large Language Model) developer or AI executive, often involving advanced skills in machine learning, deep learning, and data engineering. These roles usually require extensive experience, specialized knowledge, and may include leadership responsibilities or expertise in cutting-edge AI tools and frameworks. Compensation at this level reflects the complexity and impact of the work, often including bonuses and stock options.

What jobs in the US pay 300,000 a year?

Senior LLM developers and other advanced AI specialists can earn $300,000 or more annually, especially with extensive experience, specialized skills in machine learning, and proficiency in tools like Python and TensorFlow. High-level roles in technology, finance, and consulting firms often reach or exceed this salary level for professionals with advanced expertise and leadership responsibilities.

What is the salary of LLM developer?

The salary of a Senior LLM Developer typically ranges from $120,000 to $180,000 annually, depending on experience, location, and company size. Skilled developers with expertise in machine learning, natural language processing, and relevant tools like Python and TensorFlow are in high demand and may earn higher compensation.

What engineers make $500,000?

Senior LLM developers and AI engineers with extensive experience, advanced skills in machine learning, deep learning, and natural language processing, and often working in high-demand tech companies or specialized research roles, can reach or exceed a $500,000 annual salary. Compensation typically includes base salary, bonuses, and stock options, especially in competitive markets or senior leadership positions.

What are the key skills and qualifications needed to thrive as a Senior LLM Developer, and why are they important?

To thrive as a Senior LLM Developer, you need deep expertise in natural language processing, machine learning, and advanced programming skills, typically supported by a relevant degree and experience with large language models. Proficiency with frameworks like PyTorch or TensorFlow, cloud platforms (AWS, GCP, Azure), and version control systems, as well as familiarity with model fine-tuning and deployment, are essential. Strong problem-solving, communication, and collaboration skills help in leading teams and translating complex requirements into innovative solutions. These skills are crucial for building, optimizing, and maintaining robust language models that meet organizational objectives and stay ahead in a rapidly evolving field.

What is the difference between Senior Llm Developer vs Machine Learning Engineer?

AspectSenior Llm DeveloperMachine Learning Engineer
CredentialsAdvanced degrees in CS, NLP, or AI; experience with LLMsDegrees in CS, Data Science, or related fields; experience with ML frameworks
Work EnvironmentResearch labs, AI startups, tech companies focusing on NLPTech companies, startups, industries applying ML solutions
Industry UsagePrimarily in NLP, AI research, and language model developmentBroader across AI applications, including vision, speech, and data analysis

While both roles require strong AI and ML knowledge, Senior Llm Developers specialize in language models and NLP, whereas Machine Learning Engineers work across various AI domains. The roles often overlap but differ in focus and application areas.

What are some common challenges Senior LLM Developers face when deploying large language models in production environments?

Senior LLM Developers often encounter challenges such as optimizing model performance for latency and scalability while maintaining accuracy. Managing resource-intensive inference and ensuring robust monitoring to detect issues like model drift or biased outputs are also key concerns. Additionally, integrating LLMs with existing systems and coordinating with cross-functional teams, such as MLOps engineers and product managers, is essential for successful deployment. Staying updated with rapidly evolving frameworks and compliance requirements adds to the complexity of the role.

What are Senior LLM Developers?

Senior LLM Developers are experienced software engineers who specialize in building, fine-tuning, and deploying large language models (LLMs) such as GPT, BERT, or similar AI models. They work on advanced natural language processing (NLP) tasks, optimize model performance, and often lead teams in developing AI-driven applications. Their responsibilities include data pipeline development, model training, performance evaluation, and integrating LLMs into products. They are proficient in programming languages like Python, familiar with machine learning frameworks, and stay updated with the latest research in AI and NLP.
More about Senior Llm Developer jobs
What cities are hiring for Senior Llm Developer jobs? Cities with the most Senior Llm Developer job openings:
What are the most commonly searched types of Llm Developer jobs? The most popular types of Llm Developer jobs are:
What states have the most Senior Llm Developer jobs? States with the most job openings for Senior Llm Developer jobs include:
Infographic showing various Senior Llm Developer job openings in the United States as of July 2026, with employment types broken down into 83% Full Time, 3% Part Time, 1% Temporary, and 13% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $80,287 per year, or $38.6 per hour.

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Madison, WI • Remote

$123K - $162K/yr

Full-time

Posted 7 days ago


Job description

Senior Software Engineer: Applied AI (Voice Agents & ML Systems)

AMC Health · Remote (US) · Full-time

The pitch

We build and operate production AI voice agents that hold real phone conversations in a regulated healthcare setting, plus the machine learning and LLM pipelines around them. This is one seat that spans four disciplines that rarely come together: real-time systems, LLM engineering, traditional machine learning, and serious cloud infrastructure, all in production, all with real consequences. If you are the kind of engineer who gets restless doing one thing, this role is the opposite problem.

What you'll work across

Real-time voice AI

  • Streaming, low-latency speech-to-speech systems built on modern LLMs
  • Telephony and real-time media (call control, live audio streaming)
  • Audio handling and the quirks of real human conversation (interruptions, timing, noise)
  • Concurrency on a latency-sensitive path, where p99 matters and a stall is something a caller hears

LLM engineering

  • Wrapping nondeterministic models in deterministic control so they behave reliably in production
  • Multi-model pipelines, prompt design, and cost/latency budgeting
  • Evaluation harnesses, including LLM-as-judge and automated agent-tests-agent approaches
  • Agentic tooling that gives AI systems safe, structured access to infrastructure

Traditional (non-LLM) machine learning

  • End-to-end ML pipelines: feature engineering, model training, and scheduled inference
  • Imbalanced, messy real-world data; calibration and explainability for non-technical consumers
  • Turning research notebooks into reproducible, auditable production pipelines

Cloud and infrastructure

  • Infrastructure as code across multiple environments (we run on AWS)
  • Managed compute, data, streaming, and orchestration services
  • Security engineering in a regulated setting: encryption, least-privilege access, strict data-handling discipline
  • Observability and telemetry-driven debugging, tracing a production issue from a metric anomaly to root cause

Plus occasional full-stack work on internal tools, and an engineering workflow that leans heavily on AI coding assistants, with human accountability for every change.

What you'll actually do

  • Ship and debug code on a live, real-time voice pipeline where latency and correctness are user-facing
  • Design control systems around LLMs: guardrails, budgets, watchdogs, safe fallbacks
  • Build and operate LLM evaluation and batch-analysis pipelines
  • Own traditional ML workflows from data to scheduled production inference
  • Trace production issues from a metric anomaly to root cause, including building the evidence when the cause is a vendor

Must-haves

  • 7+ years building and operating production backend systems, with strong general-purpose programming skills (we work primarily in Python)
  • Experience running distributed systems in the cloud; comfortable debugging from telemetry to root cause
  • Hands-on production experience with LLMs or generative AI (any provider or framework), plus the judgment to know when not to use a model
  • Working fluency across the traditional machine learning lifecycle (you productionize; you do not need to publish)
  • Disciplined in a regulated environment: small, reviewable changes and careful handling of sensitive data

Nice-to-haves

  • Real-time media or telephony experience
  • Front-end / full-stack ability
  • ML pipeline experience, vector search, or embeddings
  • Fluency with AI coding assistants (our workflows assume them, with human accountability for every change)

How we work

Smallest correct change wins. Every behavior change is validated against the live system. Evidence over opinion in debugging. Code review is rigorous. Safety and privacy gate everything.

Work authorization (no exceptions)

This role is open only to US citizens and lawful permanent residents (Green Card holders). We cannot consider candidates who require visa sponsorship now or in the future, and we are unable to make exceptions of any kind.

How to apply

Please submit both of the following:

  • Your LinkedIn profile URL
  • A phone number where we can reach you

A resume is welcome but optional; the two items above are required.