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 ...
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 ...
Senior Software Engineer (Typescript / FrontEnd) - AI/ML
OR · Remote
$122K - $161K/yr
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 ...
Senior Software Engineer (Typescript / FrontEnd) - AI/ML
OR · Remote
$122K - $161K/yr
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 ...
... 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
$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 ...
... 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 ...
Develop causal inference methodologies to understand true incrementality of product changes ... Proven track record building and deploying ML models in production , particularly in ...
$114K - $137K/yr
Experience deploying AI/ML models in production, including inference APIs and vector databases
$114K - $137K/yr
Experience deploying AI/ML models in production, including inference APIs and vector databases
Knowledge of ML inference frameworks (vLLM, SGLang, TensorRT-LLM) and their communication requirements. * CUDA programming and NVIDIA GPU architecture expertise. * Proved experience influencing ...
... 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 ...
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 ...
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 ...
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 ...
OR · On-site
$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 ...
Lead Engineer - AI Agent Voice Experience
OR · On-site +1
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 ...
Lead Engineer - AI Agent Voice Experience
OR · On-site +1
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 ...
OR · On-site
... 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 ...
Mentor ML engineers to build expertise in ranking, causal inference, and scalable serving systems. About You Minimum Qualifications * 5+ years applying ML at scale (3+ years in technical leadership ...
Software Engineer 5 - Model Runtime, AI Platform
OR · On-site +1
$466K - $750K/yr
Minimum Job Qualifications Experience in ML systems engineering - building infrastructure for training, fine-tuning, or inference of pre-LLM and post-LLM era models at scale. Strong systems ...
Software Engineer 5 - Model Runtime, AI Platform
OR · On-site +1
$466K - $750K/yr
Minimum Job Qualifications Experience in ML systems engineering - building infrastructure for training, fine-tuning, or inference of pre-LLM and post-LLM era models at scale. Strong systems ...
... inference, uncertainty, and model diagnostics. * Demonstrated AI/ML experience with the ability to ... evaluate when models are appropriate and reliable, and to diagnose conditions under which models ...
New
... inference, uncertainty, and model diagnostics. * Demonstrated AI/ML experience with the ability to ... evaluate when models are appropriate and reliable, and to diagnose conditions under which models ...
New
Software Engineer 4/5 - Data and Feature Infrastructure, AI Platform
OR · On-site +1
$466K - $750K/yr
Design and build a near-real-time feature computation engine to generate ML features for both high-throughput training and low-latency inference applications. Operate and manage the feature ...
Software Engineer 4/5 - Data and Feature Infrastructure, AI Platform
OR · On-site +1
$466K - $750K/yr
Design and build a near-real-time feature computation engine to generate ML features for both high-throughput training and low-latency inference applications. Operate and manage the feature ...
... inference for model calibration, decision making under uncertainty. * Multi-scale modeling from ... Strong ability and understanding of AI/ML concepts and hybrid physics-based AI/ML modeling software.
... inference for model calibration, decision making under uncertainty. * Multi-scale modeling from ... Strong ability and understanding of AI/ML concepts and hybrid physics-based AI/ML modeling software.
Implement ML training and inference pipelines on Amazon SageMaker, including pipelines, endpoints, model registry, and monitoring * Ensure production readiness through versioning, validation ...
Implement ML training and inference pipelines on Amazon SageMaker, including pipelines, endpoints, model registry, and monitoring * Ensure production readiness through versioning, validation ...
Ml Inference information
What is a $900000 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 involving advanced skills in deep learning, data modeling, and programming with tools like Python and TensorFlow. These positions usually require extensive experience, specialized knowledge, and may include leadership responsibilities or strategic decision-making.
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 engineer makes $500,000 a year?
Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their specialized knowledge and impact on product development.
Which 3 jobs will survive AI?
Jobs involving Ml Inference, such as data scientists, machine learning engineers, and AI system architects, are likely to persist as they require specialized expertise in developing, deploying, and maintaining AI models. These roles demand critical thinking, domain knowledge, and skills in programming and data analysis that are less easily automated. Continuous learning and staying updated with AI tools and frameworks are essential for these professions to remain relevant.
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.
Will MLE be replaced by AI?
Machine Learning Engineers (MLEs) design, develop, and optimize AI models and systems. While AI automation tools can assist with certain tasks, MLEs are essential for building, tuning, and maintaining complex models, making complete replacement unlikely in the near term. Their expertise in data handling, model deployment, and system integration remains critical in AI development environments.
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:
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.
- 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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About ClickHouse
Sourced by ZipRecruiter
Industry
Software development
Company size
51 - 200 Employees
Headquarters location
San Francisco, CA, US
Year founded
2016