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Ml Inference Jobs in Oregon (NOW HIRING)

ClickHouse

Senior Software Engineer (Backend) - AI/ML

OR · Remote

About the team The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning ... Design and implement AI-powered features across the full stack, from backend inference services to ...

Coulson Aviation

CV/ML Engineer

Portland, OR · On-site

$140K - $190K/yr

Work with internal Coulson IT on model deployment and inference infrastructure * Contribute to the ... Background in remote sensing, geospatial ML, or environmental monitoring * Familiarity with real ...

Anno.ai

OR

$104K - $143K/yr

Evaluate and integrate emerging MLOps, distributed training, and edge inference technologies to enhance reproducibility, extensibility, scalability, and deployment speed of ML systems Required ...

CookUnity

OR

Develop causal inference methodologies to understand true incrementality of product changes ... Proven track record building and deploying ML models in production , particularly in ...

ClickHouse

OR

$114K - $137K/yr

Experience deploying AI/ML models in production, including inference APIs and vector databases

Nvidia

OR

Knowledge of ML inference frameworks (vLLM, SGLang, TensorRT-LLM) and their communication requirements. * CUDA programming and NVIDIA GPU architecture expertise. * Proved experience influencing ...

WEKA

OR

... AI/ML infrastructure or high-performance computing. * Deep AI Inference Background: Hands-on ... expertise with LLM serving systems - KV cache reuse, disaggregated prefill/decode, continuous ...

General Motors

Staff ML Compiler Engineer

Salem, OR · On-site

We own the compiler that turns high-level models into fast, reliable inference across GPUs powering ... Experience with ML frameworks (e.g.,PyTorch, TensorFlow, JAX) and software stack (e.g.,ONNX,MLIR ...

Netflix

OR

$466K - $750K/yr

Responsibilities Design and build scalable training and inference systems for LLMs, Multimodal LLMs, and other media ML models. Optimize end-to-end training: data pipelines (streaming, sharding ...

Instacart

Senior Software Engineer II, (ML/AI Platform)

OR · Remote

$122K - $161K/yr

Overview At Instacart, the ML/AI Platform team is a critical part of enabling the business across ... You'll take ownership of defining the platform to enable AI model fine-tuning and batch inference ...

Netflix

OR

$466K - $750K/yr

We are looking for a Senior ML Engineer to bridge the gap between cutting-edge AI research and ... Optimization & Inference: Own the performance side of GenAI. You will optimize model latency and ...

Cresta

OR

$104K - $143K/yr

Familiarity with streaming inference, real-time voice pipelines, or media systems. * Experience working closely with infrastructure or platform teams on production ML deployment, observability, and ...

Nvidia

OR

... inference at scale. * Diagnose and resolve intricate system issues and performance bottlenecks ... Commit to continuous professional growth through formal AI/ML certifications and special projects ...

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Ml Inference information

What is ML inference?

ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.

What is the difference between Ml Inference vs Data Scientist?

AspectML InferenceData Scientist
Required CredentialsKnowledge of machine learning models, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentDeploying models in production, real-time data processingData analysis, model development, research
Industry UsageAI product deployment, software companiesResearch institutions, tech firms, consulting

ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.

Which 3 jobs will survive AI?

For ML Inference roles, jobs that require complex problem-solving, creativity, and emotional intelligence are more likely to persist, such as data scientists, AI ethics specialists, and machine learning engineers. These roles involve tasks that are difficult to automate and often require specialized skills, domain knowledge, and critical thinking. Continuous learning and expertise in AI tools and programming languages like Python or TensorFlow can also enhance job security in this field.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, specialized skills in deep learning, and strong industry demand can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Achieving this level typically requires advanced degrees, certifications, and a proven track record of impactful projects.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch. These positions usually involve leadership responsibilities, strategic planning, and may require multiple years of specialized experience or advanced degrees.

Is ML a high paying job?

Machine Learning (ML) inference roles are generally well-paid due to the specialized skills required, such as knowledge of algorithms, programming, and data analysis. Salaries vary based on experience, location, and industry, but they tend to be higher than average for tech positions. Advanced roles often require proficiency with tools like TensorFlow or PyTorch and may include certifications or advanced degrees.

What are some common challenges faced by ML Inference Engineers when deploying models to production?

ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.

What are the key skills and qualifications needed to thrive in ML Inference, and why are they important?

To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.
What are popular job titles related to Ml Inference jobs in Oregon? For Ml Inference jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Ml Inference jobs in Oregon look for? The top searched job categories for Ml Inference jobs in Oregon are:
What cities in Oregon are hiring for Ml Inference jobs? Cities in Oregon with the most Ml Inference job openings:
Ml Inference jobs near you
Senior Software Engineer (Backend) - AI/ML

Senior Software Engineer (Backend) - AI/ML

ClickHouse

OR • Remote

Other

Posted 24 days ago

Job description

About the team

The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to-end. This includes the Agentic Data Stack, AI Functions, chDB, the in-Console copilot, and the AI/ML partnerships that distribute them - together with the shared components and expertise that let every other ClickHouse team ship AI in the surfaces they own. Our team is looking for highly skilled and experienced software engineers to join us, who will be responsible for designing, building, and operating the products that make ClickHouse the platform of choice for agents and data scientists.

What you will do
  • Feature Development: Design and implement AI-powered features across the full stack, from backend inference services to intuitive frontend interfaces within the ClickHouse Cloud platform.
  • API Architecture: Create robust, scalable APIs that connect ClickHouse's database capabilities with modern AI/ML inference systems and external/internal AI services.
  • Ecosystem Integrations: Implement and maintain integrations with the broader AI/ML ecosystem and standards, ensuring that ClickHouse as a technology works seamlessly with popular frameworks and tools.
  • Technical Integration: Integrate models into production systems with proper monitoring, versioning, observability, and evaluation.
  • Oncall: Participate in the daytime oncall rotation along with the rest of the team.
  • Developer Experience: Design and implement developer tools, SDKs, and documentation that enable users to leverage ClickHouse's AI/ML capabilities.
What you will bring along
  • 5+ years of software engineering experience in production environments
  • Exposure to working directly with AI/ML technologies
  • Backend development experience in TypeScript or Python, with a focus on API design and service architecture
  • A high level of ownership and can drive features from concept to production with minimal supervision
  • Ability to thrive in collaborative environments and can effectively communicate technical concepts to diverse stakeholders
  • Backend development experience in one of Python, Go, or TypeScript, with a focus on API design and service architecture

Nice to have

  • Experience integrating and deploying AI/ML models in production systems, including working with inference APIs and vector databases
  • Familiarity with cloud technologies such as AWS, Azure, or GCP, particularly services related to AI/ML deployment
  • Understanding of database systems and data processing pipelines, with ClickHouse experience being a significant plus

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