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Remote Large Language Model Llm Jobs in Michigan

Corning

$111K - $146K/yr

Develop Python-based solutions and work with APIs, JSON payloads, model integrations, and LLM ... A hybrid role based in Obispado, Monterrey, with most work expected to be remote and office ...

Corning

... model integrations, and LLM-enabled workflows. - Support CorningGPT integrations, AI assistant ... remote and office presence as needed. - Opportunity to learn from senior engineers and grow into ...

Corning

... model-connected workflows, and LLM-enabled solutions.Lead or support chatbot, RAG, conversational ... A hybrid role based in Obispado, Monterrey, with most work expected to be remote and office ...

Corning

$93K - $122K/yr

... LLM-based solutions, chatbots, RAG solutions, agents, automations, or model-connected workflows ... to be remote and office presence as needed. -Opportunity to define technical direction ...

Kobie Marketing

AI Engineer

Detroit, MI · On-site +1

Join a National Top Workplace Named a Top Workplace in the USA and Top Remote Workplace, Kobie is ... About the team and what we'll build together Kobie runs some of the largest loyalty programs in the ...

Kobie Marketing

AI Engineer

Detroit, MI

As a remote-first organization headquartered in St. Petersburg, Florida, Kobie values meaningful in ... About the team and what we'll build together Kobie runs some of the largest loyalty programs in the ...

Presence

Communication Disorders Therapist

Boon, MI · Remote

$40 - $55/hr

Provide speech-language teletherapy * Participate in IEP meetings * Complete comprehensive case ... large community of remote providers access to an award-winning platform, assessment and therapy ...

micro1 AI

Digital Chemistry Specialist - Remote

Warren, MI · Remote

$90 - $120/hr

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.

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Remote Large Language Model Llm information

What is a remote large language model LLM?

A Remote Large Language Model (LLM) job involves working with advanced AI models, like GPT or similar, from a remote location. Professionals in these roles may develop, train, fine-tune, or implement large language models for various applications such as natural language processing, chatbots, or content generation. Remote LLM jobs can include positions like machine learning engineer, research scientist, or AI product manager. The work typically requires strong programming skills, experience with AI frameworks, and the ability to collaborate virtually with global teams.

How does a remote large language model LLM engineer typically collaborate with cross-functional teams while working remotely?

Remote LLM Engineers often work closely with data scientists, product managers, and software engineers through virtual meetings, collaborative coding platforms, and shared documentation tools. Regular communication is key, with daily stand-ups or weekly syncs to align on project goals, update progress, and address challenges. They may also participate in code reviews, contribute to design discussions, and support model deployment efforts, all within a distributed team environment. This remote structure encourages self-motivation and proactive communication to ensure project success.

What are the key skills and qualifications needed to thrive as a remote large language model LLM engineer?

To thrive as a Remote Large Language Model (LLM) Engineer, you need a strong background in computer science, machine learning, and natural language processing, typically supported by a relevant degree and experience with large-scale models. Proficiency with programming languages like Python, deep learning frameworks such as PyTorch or TensorFlow, and familiarity with cloud platforms and distributed systems are essential. Excellent problem-solving, communication, and collaboration skills are critical for remote teamwork and translating complex requirements into scalable solutions. These skills ensure the effective development, deployment, and maintenance of advanced language models in fast-evolving, distributed environments.

What is the difference between Remote Large Language Model Llm vs Data Scientist?

AspectRemote Large Language Model LlmData Scientist
Required CredentialsAdvanced degrees in AI, NLP, or related fields; experience with machine learning frameworksDegree in Data Science, Statistics, Computer Science, or related fields; strong analytical skills
Work EnvironmentPrimarily remote, focused on developing and fine-tuning language modelsRemote or on-site, analyzing data, building models, and generating insights
Employer & Industry UsageTech companies, AI research labs, startups working on NLP productsTech firms, finance, healthcare, marketing, and research organizations

While both roles involve data and machine learning, a Remote Large Language Model Llm specializes in developing and refining language models, whereas a Data Scientist focuses on analyzing data, building predictive models, and deriving insights across various domains.

What are the most commonly searched types of Large Language Model Llm jobs in Michigan?

The most popular types of Large Language Model Llm jobs in Michigan are:

What are popular job titles related to Remote Large Language Model Llm jobs in Michigan?

For Remote Large Language Model Llm jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Remote Large Language Model Llm jobs in Michigan look for?

The top searched job categories for Remote Large Language Model Llm jobs in Michigan are:

What cities in Michigan are hiring for Remote Large Language Model Llm jobs?

Cities in Michigan with the most Remote Large Language Model Llm job openings:

Remote Large Language Model Llm jobs near you
Infographic showing various Remote Large Language Model Llm job openings in Michigan as of August 2026, with employment types broken down into 86% Full Time, 8% Part Time, 1% Temporary, and 5% Contract. Highlights an 89% Physical, 5% Hybrid, and 6% Remote job distribution.

Senior, Machine Learning Engineer - End-to-End

Torc Robotics

Ann Arbor, MI • On-site, Remote

$119K - $158K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 24 days ago

Job description

About the Company
At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.
A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight.
Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.
Meet the Team:
As a Senior Machine Learning Engineer - End-to-End (E2E), you will develop and scale learning-based systems that connect multi-modal perception inputs to driving behavior, enabling safe, efficient, and human-like autonomy for real-world freight operations.
You'll work at the intersection of perception, prediction, and planning, contributing to unified learning pipelines that operate in closed-loop environments. This role focuses on owning meaningful portions of the E2E stack, improving model performance at scale, and driving iteration through data, experimentation, and cross-functional collaboration.
This is a hands-on engineering role focused on execution, iteration, and delivery.
What You'll Do
  • Own development and delivery of End-to-End ML models that map multi-modal sensor inputs (camera, LiDAR, radar, maps) to driving-relevant outputs (trajectories, cost functions, or intermediate representations)
  • Train and evaluate models using large-scale datasets from fleet logs, simulation, and synthetic data
  • Analyze model performance, identify failure modes, and drive data-driven improvements in robustness and generalization
  • Design and refine training pipelines, data workflows, and evaluation strategies to improve iteration speed and model quality
  • Contribute to model architecture decisions, including approaches such as imitation learning, reinforcement learning, transformers, and vision-language-action (VLA) models
  • Collaborate closely with Perception, Prediction, Planning, and Simulation teams to ensure alignment across the autonomy stack
  • Support integration of E2E models into simulation and on-vehicle systems for closed-loop validation
  • Improve tooling, experimentation workflows, and reproducibility across the team
  • Mentor junior engineers and contribute to team-level best practices and technical discussions

What You'll Need to Succeed
  • Bachelor's degree with 6+ years, Master's with 4+ years, or PhD with 0-2 years of experience in Machine Learning, Robotics, Computer Science, or a related field with a track record of publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, CoRL)
  • Experience developing and deploying ML models for autonomous systems, robotics, or complex decision-making environments
  • Strong programming skills in Python and PyTorch, with ability to write production-quality ML code
  • Experience training and evaluating models using large-scale datasets and distributed compute environments
  • Solid understanding of ML architectures used in E2E systems, such as Transformers, BEV models, VLA/VLM approaches, or diffusion models
  • Proven ability to debug model behavior, analyze performance metrics, and drive iterative improvements
  • Experience contributing to or influencing model architecture and training strategies
  • Ability to work cross-functionally and integrate ML systems into larger autonomy pipelines

Bonus Points
  • Experience developing End-to-End or mid-to-end models for autonomous driving or robotics
  • Experience with vision-language models (VLMs) or vision-language-action (VLA) systems
  • Familiarity with closed-loop simulation and evaluation frameworks
  • Experience with reinforcement learning or imitation learning in real-world systems
  • Experience with distributed training frameworks (e.g., Ray)
  • Understanding of vehicle dynamics, motion planning, or multi-agent systems

Work Location: For this position, we are open to hiring in Ann Arbor, MI (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United States.
Perks of Being a Full-time Torc'r
Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:
  • A competitive compensation package that includes a bonus component and stock options
  • 100% paid medical, dental, and vision premiums for full-time employees
  • 401K plan with a 6% employer matchFlexibility in schedule and generous paid vacation (available immediately after start date)Company-wide holiday office closures
  • AD+D and Life Insurance

At Torc, we're committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc'rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.
Even if you don't meet 100% of the qualifications listed for this opportunity, we encourage you to apply.
Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
Job ID: 102665
Hiring Range for Job Opening
US Pay Range
$226,400-$271,700 USD

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