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Ml Model Fine Tuning Jobs in Oregon (NOW HIRING)

Model Development & Optimization * Proven ability to perform fine-tuning, supervised/unsupervised ... Understanding of production ML systems, deployment patterns, monitoring, and safety/guardrail ...

Sr. Machine Learning Engineer

Hillsboro, OR

$113K - $156K/yr

... model fine tuning. This role sits at the intersection of research and engineering: the ideal ... Willingness and skill to dive deeply into large, complex ML codebases to isolate and fix subtle ...

AI Engineer

OR · On-site +1

In This Role, You Will: * Lead end-to-end development of AI/ML models: from data ingestion ... Experience building or fine-tuning Large Language Models (LLMs). * Experience deploying models into ...

VP, Solutions Architect - AWS

OR · On-site +1

$64.75 - $85/hr

... ML services. As an AWS AI Solutions Architect, you will serve as a strategic technical advisor ... and model fine-tuning strategies. * Experience architecting RAG, multi-agent, and orchestration ...

... ML services. As an AWS AI Solutions Architect, you will serve as a strategic technical advisor ... and model fine-tuning strategies. * Experience architecting RAG, multi-agent, and orchestration ...

Lead ML/Perception Engineer

OR · On-site +1

$102K - $134K/yr

Direct experience developing or fine-tuning large-scale multi-modal models (e.g., multi-sensor ... Familiar with ML/DL optimization on real-time products with limited compute resources (e.g ...

This role is ideal for a hands-on, applied ML leader who thrives at the intersection of modeling ... Hands-on experience working with LLMs, including prompt engineering, fine-tuning, retrieval ...

Explore and evaluate new AI/ML techniques, tools, and methodologies, applying relevant innovations ... Hands-on experience developing, fine-tuning, or adapting foundation models for domain-specific data ...

Explore and evaluate new AI/ML techniques, tools, and methodologies, applying relevant innovations ... Hands-on experience developing, fine-tuning, or adapting foundation models for domain-specific data ...

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

... model fine tuning, and interface integration to deliver reliable, high quality AI outputs in production environments • Integrate AI capabilities with existing enterprise systems such as ERP, CRM, ...

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

Build and optimize LLM capabilities using retrieval augmented generation, model fine tuning, and interface integration to deliver reliable, high quality AI outputs in production environments

AI Engineer, Sr

Newberg, OR · On-site

$109K - $150K/yr

Build and optimize LLM capabilities using retrieval augmented generation, model fine tuning, and interface integration to deliver reliable, high quality AI outputs in production environments

AI Engineer, Sr

Newberg, OR · On-site

$140 - $220/hr

Build and optimize LLM capabilities using retrieval augmented generation, model fine tuning, and interface integration to deliver reliable, high quality AI outputs in production environments

... models at a global scale. Applied Machine Learning Research at Netflix drives various aspects of ... ML techniques-including LLM pretraining, fine-tuning, and robust offline experimentation-while ...

Applied AI Scientist

OR · On-site

$128K - $215K/yr

Experience building or fine-tuning foundation models, multimodal models, or agentic AI systems . * Familiarity with Google Cloud Platform (GCP) , including large-scale AI/ML infrastructure.

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Ml Model Fine Tuning information

What is ML model fine-tuning?

ML model fine-tuning is the process of taking a pre-trained machine learning model and making small adjustments to its parameters using new data relevant to your specific task. This approach allows you to leverage the general knowledge the model has already learned, while adapting it to perform better on your particular dataset or problem. Fine-tuning is common in fields like natural language processing and computer vision, as it saves time and resources compared to training a model from scratch. The process typically involves retraining the last few layers of the model or using a lower learning rate for the entire model.

What are some common challenges faced when fine-tuning machine learning models in a production environment?

One common challenge when fine-tuning ML models in production is ensuring that the updated models generalize well to new, unseen data without overfitting to recent trends or noise. Additionally, coordinating with data engineers and software developers is crucial to maintain data pipelines and model deployment workflows. Managing computational resources and keeping track of model versions for reproducibility can also be complex, especially in fast-paced or large-scale environments. Regular communication with stakeholders is important to align model updates with business objectives and to ensure the smooth integration of improvements.

What are the key skills and qualifications needed to thrive as an ML model fine tuning specialist, and why are they important?

To thrive as an ML Model Fine Tuning Specialist, you need a solid background in machine learning, statistics, programming (often Python), and experience with model training and evaluation. Familiarity with frameworks such as TensorFlow, PyTorch, and tools like Hugging Face Transformers, along with experience in managing GPUs and cloud platforms, is typically required. Strong problem-solving skills, attention to detail, and effective communication help you understand project requirements and collaborate with data scientists and engineers. These skills are crucial for optimizing model performance, ensuring accurate results, and delivering robust AI solutions tailored to specific business needs.

What is the difference between Ml Model Fine Tuning vs Data Scientist?

AspectMl Model Fine TuningData Scientist
CredentialsKnowledge of machine learning frameworks, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentFocus on model optimization, coding, and experimentationData analysis, modeling, and interpretation
Industry UsageAI/ML development teams, tech companiesResearch, analytics, business intelligence

While Ml Model Fine Tuning involves adjusting pre-trained models to improve performance, Data Scientists analyze data, develop models, and interpret results. Fine tuning is a specialized task within the broader scope of a Data Scientist's role, often requiring similar technical skills but focusing more on model optimization.

What are popular job titles related to Ml Model Fine Tuning jobs in Oregon?

For Ml Model Fine Tuning jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Ml Model Fine Tuning jobs in Oregon look for?

The top searched job categories for Ml Model Fine Tuning jobs in Oregon are:

What cities in Oregon are hiring for Ml Model Fine Tuning jobs?

Cities in Oregon with the most Ml Model Fine Tuning job openings:

Looking for MLOps Engineer in Portland, OR- Hybrid

Saksoft

Portland, OR • On-site

Other

Posted 2 days ago

New


Job description

MLOps Engineer 

Location: Portland, OR- Hybrid

Hybrid: 3 days office

Contract

 JD:

This data science role requires a minimum of 7 years of Python and data science experience, 3 years of AWS experience, and hands-on delivery of machine learning and Generative AI use cases. 

Core Technical Requirements

• Data Science: Minimum 7 years of hands-on coding and model development in Python. 
• Cloud Infrastructure: Minimum 3 years of production experience working within the AWS ecosystem. 
• Machine Learning: Proven background in machine learning with at least 5 distinct, well-documented use cases covering a mix of classification, regression, or forecasting models. 
• Generative AI: Demonstrated delivery of at least 2 Generative AI use cases (Preferred candidates with: keywords such as multimodal applications, image-plus-text processing, or advanced model fine-tuning in GenAI use cases)