Job Title: Machine Learning Engineer Location: Portland, OR - Onsite (Local only / F2F interview ... systems, or LLM-based reasoning • Knowledge of MLOps practices (CI/CD, monitoring, model ...
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Job Title: Machine Learning Engineer Location: Portland, OR - Onsite (Local only / F2F interview ... systems, or LLM-based reasoning • Knowledge of MLOps practices (CI/CD, monitoring, model ...
Machine Learning Engineer
Portland, OR · On-site
Machine Learning Engineer Location: Portland, OR - Onsite (Local only / F2F interview) Duration: 24 ... systems, or LLM-based reasoning • Knowledge of MLOps practices (CI/CD, monitoring, model ...
Machine Learning Engineer
Portland, OR · On-site
Machine Learning Engineer Location: Portland, OR - Onsite (Local only / F2F interview) Duration: 24 ... systems, or LLM-based reasoning • Knowledge of MLOps practices (CI/CD, monitoring, model ...
Machine Learning Engineer
Portland, OR · On-site
Job Title: Machine Learning Engineer Location: Portland, OR - Onsite (Local only / F2F interview ... or LLM-based reasoning Knowledge of MLOps practices (CI/CD, monitoring, model governance ...
Machine Learning Engineer
Portland, OR · On-site
Job Title: Machine Learning Engineer Location: Portland, OR - Onsite (Local only / F2F interview ... or LLM-based reasoning Knowledge of MLOps practices (CI/CD, monitoring, model governance ...
Machine Learning Engineer
$212K - $318K/yr
As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive ... Design and integrate LLM-powered features and AI agent workflows into production systems, ensuring ...
Machine Learning Engineer
$212K - $318K/yr
As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive ... Design and integrate LLM-powered features and AI agent workflows into production systems, ensuring ...
Machine Learning Engineer
Cupertino, CA · On-site
As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive ... Familiarity with LLM evaluation practices including output quality assessment, hallucination ...
Machine Learning Engineer
Cupertino, CA · On-site
As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive ... Familiarity with LLM evaluation practices including output quality assessment, hallucination ...
The Machine Learning Engineer will bridge the gap between data science and software engineering ... Preferred : • Experience with LLM fine-tuning (PEFT/LoRA) • Experience with vector databases ...
New
The Machine Learning Engineer will bridge the gap between data science and software engineering ... Preferred : • Experience with LLM fine-tuning (PEFT/LoRA) • Experience with vector databases ...
New
Machine Learning Engineer
Seattle, WA · On-site
The Machine Learning Engineer will architect and deploy systems that integrate Large Language ... safety using LLM-as-a-judge and human-in-the-loop workflows. • Design and scale backend ...
New
Machine Learning Engineer
Seattle, WA · On-site
The Machine Learning Engineer will architect and deploy systems that integrate Large Language ... safety using LLM-as-a-judge and human-in-the-loop workflows. • Design and scale backend ...
New
Are you a passionate Machine Learning Engineer with a strong background in SageMaker, prompt engineering, and LLM (Large Language Model) model tuning? Do you thrive in a dynamic and innovative ...
Quick apply
Are you a passionate Machine Learning Engineer with a strong background in SageMaker, prompt engineering, and LLM (Large Language Model) model tuning? Do you thrive in a dynamic and innovative ...
Design and develop innovative ML models, Gen AI systems, and software algorithms - including LLM ... Machine Learning model fine-tuning. Familiarity with data engineering concepts and practices.
Design and develop innovative ML models, Gen AI systems, and software algorithms - including LLM ... Machine Learning model fine-tuning. Familiarity with data engineering concepts and practices.
We are seeking a highly experienced Machine Learning Engineer to build, deploy, and optimize Large Language Model (LLM)-based applications, with a strong emphasis on MLOps/LLMOps (LLM operations) and ...
We are seeking a highly experienced Machine Learning Engineer to build, deploy, and optimize Large Language Model (LLM)-based applications, with a strong emphasis on MLOps/LLMOps (LLM operations) and ...
$28 - $45/hr
Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... Deep Learning * Transformers * LLM fundamentals Cloud & MLOps * AWS (SageMaker, S3, EC2)
$28 - $45/hr
Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... Deep Learning * Transformers * LLM fundamentals Cloud & MLOps * AWS (SageMaker, S3, EC2)
Senior Machine Learning Engineer
$107K - $146K/yr
We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the ... Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement You'll ...
Senior Machine Learning Engineer
$107K - $146K/yr
We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the ... Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement You'll ...
$28 - $45/hr
Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... Deep Learning * Transformers * LLM fundamentals Cloud & MLOps * AWS (SageMaker, S3, EC2)
$28 - $45/hr
Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... Deep Learning * Transformers * LLM fundamentals Cloud & MLOps * AWS (SageMaker, S3, EC2)
$28 - $45/hr
Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... Deep Learning * Transformers * LLM fundamentals Cloud & MLOps * AWS (SageMaker, S3, EC2)
$28 - $45/hr
Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... Deep Learning * Transformers * LLM fundamentals Cloud & MLOps * AWS (SageMaker, S3, EC2)
Machine Learning Engineer II
New York, NY · On-site
Staff Machine Learning Engineer Overview: As a Staff Machine Learning Engineer, you will be the ... Experiencebuilding LLM-based AI agent workflows via both no code/low code and traditional high-code ...
Machine Learning Engineer II
New York, NY · On-site
Staff Machine Learning Engineer Overview: As a Staff Machine Learning Engineer, you will be the ... Experiencebuilding LLM-based AI agent workflows via both no code/low code and traditional high-code ...
Staff Machine Learning Engineer Overview: As a Staff Machine Learning Engineer, you will be the ... Experiencebuilding LLM-based AI agent workflows via both no code/low code and traditional high-code ...
Staff Machine Learning Engineer Overview: As a Staff Machine Learning Engineer, you will be the ... Experiencebuilding LLM-based AI agent workflows via both no code/low code and traditional high-code ...
Machine Learning Engineer II
Bethesda, MD · On-site
Staff Machine Learning Engineer Overview: As a Staff Machine Learning Engineer, you will be the ... Experiencebuilding LLM-based AI agent workflows via both no code/low code and traditional high-code ...
Machine Learning Engineer II
Bethesda, MD · On-site
Staff Machine Learning Engineer Overview: As a Staff Machine Learning Engineer, you will be the ... Experiencebuilding LLM-based AI agent workflows via both no code/low code and traditional high-code ...
Machine Learning Engineer - Generative Al Location:Sunrise,FL(Day 1 onsite Hybrid 3 days a week in ... Strong python, have work experiment on LLM, gen AI, Lang chain, Lang Graph, Python API, Google ...
Machine Learning Engineer - Generative Al Location:Sunrise,FL(Day 1 onsite Hybrid 3 days a week in ... Strong python, have work experiment on LLM, gen AI, Lang chain, Lang Graph, Python API, Google ...
Job Summary We are seeking a Machine Learning Engineer with strong hands-on experience in building ... Apply LLM concepts such as RAG, prompting, few-shot prompting, and supervised fine-tuning (SFT)
Job Summary We are seeking a Machine Learning Engineer with strong hands-on experience in building ... Apply LLM concepts such as RAG, prompting, few-shot prompting, and supervised fine-tuning (SFT)
Machine Learning Engineer
Manchester, NH · On-site
We're looking for a Machine Learning Engineer who can operate at the intersection of backend ... Contribute to AI/LLM-driven workflows and orchestration systems that push the boundaries of what ...
Machine Learning Engineer
Manchester, NH · On-site
We're looking for a Machine Learning Engineer who can operate at the intersection of backend ... Contribute to AI/LLM-driven workflows and orchestration systems that push the boundaries of what ...
Machine Learning Engineer Llm information
See salary details
$31.5K - $46.2K
1% of jobs
$46.2K - $61K
1% of jobs
$61K - $75.7K
5% of jobs
$75.7K - $90.4K
6% of jobs
$102.6K is the 25th percentile. Wages below this are outliers.
$90.4K - $105.1K
14% of jobs
$105.1K - $119.9K
14% of jobs
The median wage is $127.2K / yr.
$119.9K - $134.6K
18% of jobs
$134.6K - $149.3K
14% of jobs
$152.3K is the 75th percentile. Wages above this are outliers.
$149.3K - $164K
12% of jobs
$164K - $178.8K
11% of jobs
$178.8K - $193.5K
5% of jobs
$31.5K
$128.8K
$193.5K
How much do machine learning engineer llm jobs pay per year?
As of Jun 5, 2026, the average yearly pay for machine learning engineer llm in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.
What are Machine Learning Engineers (LLM)?
Machine Learning Engineers (LLM) are professionals who design, build, and deploy large language models (LLMs) such as GPT or BERT. They combine software engineering skills with a deep understanding of machine learning algorithms to develop systems that can process and generate human-like text. Their responsibilities often include data preprocessing, model training, fine-tuning, evaluation, and integrating these models into applications. They also work to optimize performance, ensure scalability, and address ethical considerations related to AI language models.
What is the difference between Machine Learning Engineer Llm vs Data Scientist?
| Aspect | Machine Learning Engineer Llm | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's or Master's in CS, AI, or related; experience with ML frameworks | Bachelor's or Master's in CS, Statistics, or related; strong analytical skills |
| Work Environment | Develops, tests, and deploys ML models, often in AI-focused teams | Analyzes data, builds models, and provides insights for decision-making |
| Industry Usage | Used in AI product development, NLP, LLMs, and automation | Applied across finance, healthcare, marketing, and research |
While both roles require strong technical skills and knowledge of machine learning, Machine Learning Engineer Llm focuses on developing and deploying large language models, especially in AI applications. Data Scientists analyze data and build models for insights. The roles often overlap but differ mainly in their focus on deployment versus analysis.
What are some common challenges Machine Learning Engineers face when working with large language models (LLMs) in a production environment?
Machine Learning Engineers working with LLMs often encounter challenges such as optimizing model performance while managing resource constraints like memory and compute power. Additionally, ensuring data privacy and compliance can be complex due to the vast amounts of training data involved. Another common challenge is deploying and monitoring LLMs to maintain accuracy and minimize bias, requiring close collaboration with data scientists, DevOps, and product teams. Regularly updating models to reflect new data and user feedback is also crucial for maintaining relevance and performance in real-world applications.
What are the key skills and qualifications needed to thrive as a Machine Learning Engineer LLM, and why are they important?
To thrive as a Machine Learning Engineer specializing in large language models (LLMs), you need a strong background in computer science, mathematics, and deep learning, typically supported by a relevant degree and experience with NLP techniques. Familiarity with frameworks like TensorFlow, PyTorch, Hugging Face Transformers, and experience working with large-scale data sets and distributed systems are essential, along with knowledge of cloud platforms such as AWS or GCP. Strong problem-solving, collaboration, and communication skills help you translate complex research into practical applications and work effectively with cross-functional teams. These combined skills ensure the ability to develop, fine-tune, and deploy LLMs that deliver real-world value while staying at the forefront of AI advancements.
Contractor
Posted 11 days ago
Job description
Job Description
Job Title: Machine Learning Engineer
Location: Portland, OR - Onsite (Local only / F2F interview)
Duration: 24 Months Contract
Experience Level: 5+ years of experience
Required Qualifications
• Bachelor’s or master’s degree in computer science, Machine Learning, Electrical Engineering, or related field
• 5+ years of experience in machine learning, data science, or AI engineering
• Strong programming skills in Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow)
• Experience with time-series data analysis and anomaly detection
• Hands-on experience with causal inference methods (e.g., Bayesian networks, structural causal models)
• Experience building or working with knowledge graphs (Neo4j, RDF, graph databases)
• Understanding of explainable AI techniques (SHAP, LIME, counterfactual analysis)
• Experience deploying ML models in production systems
• Strong problem-solving skills and ability to work with complex, real-world datasets
Preferred Qualifications
• Experience with fault tree analysis (FTA), reliability engineering, or failure analysis
• Background in industrial systems, semiconductors, manufacturing, or IoT environments
• Experience with graph-based ML / Graph Neural Networks (GNNs)
• Familiarity with RCA methodologies (FMEA, 5 Whys, fishbone diagrams)
• Experience with vector databases, RAG systems, or LLM-based reasoning
• Knowledge of MLOps practices (CI/CD, monitoring, model governance)
• Experience working in air-gapped or high-security environments
All your information will be kept confidential according to EEO guidelines.