The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to ... Design and implement AI-powered features across the full stack, from backend inference services to ...
The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to ... Design and implement AI-powered features across the full stack, from backend inference services to ...
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 ...
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 ...
... embedded ML inference Collaborate with system architecture and software teams to understand use case requirements that could be unique for each environment Translate findings into actionable ...
... embedded ML inference Collaborate with system architecture and software teams to understand use case requirements that could be unique for each environment Translate findings into actionable ...
... embedded ML inference Collaborate with system architecture and software teams to understand use case requirements that could be unique for each environment Translate findings into actionable ...
... embedded ML inference Collaborate with system architecture and software teams to understand use case requirements that could be unique for each environment Translate findings into actionable ...
OR · On-site
$114.40K - $137.40K/yr
... ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should ...
OR · On-site
$114.40K - $137.40K/yr
... ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should ...
OR · On-site
Knowledge of ML inference frameworks (vLLM, SGLang, TensorRT-LLM) and their communication requirements. * CUDA programming and NVIDIA GPU architecture expertise. * Proved experience influencing ...
$129.40K - $175.80K/yr
Knowledge of ML inference frameworks (vLLM, SGLang, TensorRT-LLM) and their communication requirements. * Knowledge of storage networking (NVMe-oF, GPUDirect Storage, S3). * Background of ...
Guide the design of model deployment, inference services, monitoring, and observability for production ML workloads * Contribute to the development of ML-ready representations for geometry, graph ...
Guide the design of model deployment, inference services, monitoring, and observability for production ML workloads * Contribute to the development of ML-ready representations for geometry, graph ...
Senior Machine Engineer, ML Systems and Infrastructure
OR · Remote
$104.40K - $142.90K/yr
Contribute to model deployment, inference services, and production monitoring workflows * Improve data quality, lineage, provenance, and operational transparency across ML pipelines * Contribute to ...
Senior Machine Engineer, ML Systems and Infrastructure
OR · Remote
$104.40K - $142.90K/yr
Contribute to model deployment, inference services, and production monitoring workflows * Improve data quality, lineage, provenance, and operational transparency across ML pipelines * Contribute to ...
OR · On-site
... 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 ...
$122.40K - $161.30K/yr
We are looking for a Senior System Software Engineer to work on Dynamo-Triton Inference Server ... Experience with high-scale distributed systems and ML systems. * Strong communication skills and ...
Senior AI/ML Tooling Engineer
Salem, OR · On-site +1
$144.70K - $261.30K/yr
Identify new opportunities to improve both training and inference efficiency * Build workflows for ... Experience with ML frameworks (e.g., PyTorch, TensorFlow) and NVIDIA developer ecosystem (TensorRT ...
Senior AI/ML Tooling Engineer
Salem, OR · On-site +1
$144.70K - $261.30K/yr
Identify new opportunities to improve both training and inference efficiency * Build workflows for ... Experience with ML frameworks (e.g., PyTorch, TensorFlow) and NVIDIA developer ecosystem (TensorRT ...
... ML tooling, or distributed systems. * 3+ years of engineering leadership experience as a tech lead, TLM, or engineering manager. * Deep understanding of LLM inference mechanics - TTFT, ITL, KV ...
Role Summary Build intelligent capabilities using LLM-based inferencing, agentic AI workflows, and RAG-based solutions leveraging AWS-native AI/ML services. Focus on inference orchestration, vector ...
Role Summary Build intelligent capabilities using LLM-based inferencing, agentic AI workflows, and RAG-based solutions leveraging AWS-native AI/ML services. Focus on inference orchestration, vector ...
AI Engineer
Hillsboro, OR · On-site
Role Summary Build intelligent capabilities using LLM-based inferencing, agentic AI workflows, and RAG-based solutions leveraging AWS-native AI/ML services. Focus on inference orchestration, vector ...
AI Engineer
Hillsboro, OR · On-site
Role Summary Build intelligent capabilities using LLM-based inferencing, agentic AI workflows, and RAG-based solutions leveraging AWS-native AI/ML services. Focus on inference orchestration, vector ...
OR · On-site
$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 ...
$466K - $750K/yr
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, bucketing ...
... inference. * Experience with prompt engineering, RAG and related LLM architecture patterns, and ... ML/LLM services. * Familiarity with CI/CD and infrastructure-as-code practices and tools such as ...
... inference. * Experience with prompt engineering, RAG and related LLM architecture patterns, and ... ML/LLM services. * Familiarity with CI/CD and infrastructure-as-code practices and tools such as ...
... ML and AI infrastructure engineers who power perception, multimodal understanding, and edge inference for Caper Carts. You will own the roadmap for how our carts see and reason about what's in the ...
... ML and AI infrastructure engineers who power perception, multimodal understanding, and edge inference for Caper Carts. You will own the roadmap for how our carts see and reason about what's in the ...
Senior Software Engineer II, (ML/AI Platform)
OR · Remote
$122.40K - $161.30K/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 ...
Senior Software Engineer II, (ML/AI Platform)
OR · Remote
$122.40K - $161.30K/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 ...
Ml Inference information
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 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 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?
| Aspect | ML Inference | Data Scientist |
|---|---|---|
| Required Credentials | Knowledge of machine learning models, programming skills | Degree in data science, statistics, or related fields |
| Work Environment | Deploying models in production, real-time data processing | Data analysis, model development, research |
| Industry Usage | AI product deployment, software companies | Research 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.
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:
Job description
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 will you 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.
- UI/UX Implementation: Build responsive, intuitive user interfaces that make complex AI functionalities accessible and valuable to users of all technical backgrounds.
- 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.
What you bring along:
- 5+ years of software engineering experience in production environments
- Exposure to working directly with AI/ML technologies
- Strong frontend skills with TypeScript/JavaScript and React
- Backend development experience in TypeScript or Python, with a focus on API design and service architecture
- You have a high level of ownership and can drive features from concept to production with minimal supervision
- You thrive in collaborative environments and can effectively communicate technical concepts to diverse stakeholders
Nice to have
- Experience building data-oriented interfaces and visualizations
- 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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About ClickHouse
Sourced by ZipRecruiter
Industry
Software development
Company size
51 - 200 Employees
Headquarters location
San Francisco, CA, US
Year founded
2016