2

Llm Engineer Remote Jobs in Wisconsin (NOW HIRING)

$139K - $168K/yr

Experience of transformer models and LLM applications * Strong knowledge of Python or C++, or the ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Experience of transformer models and LLM applications * Strong knowledge of Python or C++, or the ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Experience of transformer models and LLM applications * Strong knowledge of Python or C++, or the ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Experience of transformer models and LLM applications * Strong knowledge of Python or C++, or the ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Experience of transformer models and LLM applications * Strong knowledge of Python or C++, or the ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Experience of transformer models and LLM applications * Strong knowledge of Python or C++, or the ... LI-SS2 LI-REMOTE

$139K - $168K/yr

Experience of transformer models and LLM applications * Strong knowledge of Python or C++, or the ... LI-SS2 LI-REMOTE

Der Fokus liegt auf Big-Data-Engineering , ML/LLM-Workloads , MLOps-Automatisierung sowie der ... Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote Projektsprache: Deutsch und Englisch Aufgaben: ...

AI Engineer

Glendale, WI ยท On-site +1

This is a hybrid/remote role that is flexible on location so long as there is flexibility to travel ... Develop LLM-powered features including operator copilots, intelligent alarm management, and natural ...

Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote Projektsprache: Deutsch und Englisch Aufgaben: ... LLM-basierten Conversational-AI-Losungen (z. B. RAG-Applikationen) in Microsoft Azure Aufbau, ...

AI Platform Engineer (Part-time)

Milwaukee, WI ยท On-site +1

$70 - $85/hr

Implement AI workflows leveraging modern LLM technologies * Participate in Agile sprint planning ... Remote candidates are welcomed to apply! Job Type & Location This is a Contract position based out ...

Llm Engineer Remote information

What is the difference between Llm Engineer Remote vs Data Scientist Remote?

AspectLlm Engineer RemoteData Scientist Remote
Required CredentialsAdvanced degree in CS, ML, or related field; experience with NLP and deep learningDegree in CS, Statistics, or related; experience with data analysis and machine learning
Work EnvironmentCollaborative teams, research-focused, often in tech or AI companiesData analysis, model development, reporting; across various industries
Employer & Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, tech, e-commerce, and more

While both roles involve machine learning, Llm Engineers focus on developing large language models and NLP applications, often requiring deep expertise in AI research. Data Scientists analyze data to inform business decisions, with broader industry applications. The roles share some credentials but differ in focus and daily tasks.

What are some typical challenges faced by remote LLM Engineers when collaborating with cross-functional teams?

Remote LLM Engineers often work closely with data scientists, product managers, and software engineers to develop and deploy large language models. One common challenge is ensuring clear and consistent communication across different time zones and technical backgrounds, which can sometimes lead to misaligned project goals or delays. To overcome this, many teams rely on detailed documentation, regular virtual meetings, and collaborative project management tools. Building strong relationships remotely and proactively sharing updates can make collaboration smoother and more productive.

What are the key skills and qualifications needed to thrive as an LLM Engineer in a remote role, and why are they important?

To thrive as an LLM Engineer remotely, you need strong expertise in machine learning, natural language processing, and proficiency with programming languages such as Python, often supported by a degree in computer science or related fields. Familiarity with frameworks like PyTorch or TensorFlow, experience with cloud platforms (AWS, GCP), and knowledge of large language model architectures are commonly required. Excellent problem-solving skills, self-motivation, and effective remote communication make candidates stand out. These capabilities are crucial for developing, deploying, and maintaining advanced language models while collaborating efficiently with distributed teams.

What is an LLM Engineer (Remote)?

An LLM Engineer, or Large Language Model Engineer, is a professional who designs, develops, and optimizes applications using advanced AI language models such as GPT-4 or similar technologies. Working remotely, they are responsible for integrating these models into products, fine-tuning them for specific tasks, and ensuring their performance and reliability. LLM Engineers often collaborate with data scientists, software developers, and product managers to create solutions in areas like chatbots, content generation, and natural language processing. Their work requires a strong background in machine learning, programming, and cloud computing.
What are the most commonly searched types of Llm Engineer jobs in Wisconsin? The most popular types of Llm Engineer jobs in Wisconsin are:
What job categories do people searching Llm Engineer Remote jobs in Wisconsin look for? The top searched job categories for Llm Engineer Remote jobs in Wisconsin are:
What cities in Wisconsin are hiring for Llm Engineer Remote jobs? Cities in Wisconsin with the most Llm Engineer Remote job openings:

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Madison, WI โ€ข Remote

$123K - $162K/yr

Full-time

Posted 12 days ago


Job description

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

AMC Health ยท Remote (US) ยท 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.