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Ml Inference Jobs in Kent, WA (NOW HIRING)

Apple

ML Software Engineer

Seattle, WA

$171K - $258K/yr

Our team builds ML-inference applications and services on Apple Silicon in the datacenter, specifically focusing in recent years on generative AI as part of the Private Cloud Compute component of ...

Lululemon athletica

Senior AI/ML Engineer

Seattle, WA · On-site

$118K - $163K/yr

Implement scalable model serving architectures forreal-timeand batch inference * Developing ... Partner with AI/ML scientists to productionize models while meeting accuracy, performance ...

Amazon

Software Engineer II- AI/ML, AWS Neuron

Seattle, WA · On-site

$111K - $151K/yr

This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch and JAX enabling unparalleled ML inference ...

lululemon

Senior AI/ML Engineer

Seattle, WA

$119K - $163K/yr

Implement scalable model serving architectures forreal-timeand batch inference * Developing ... Partner with AI/ML scientists to productionize models while meeting accuracy, performance ...

Lululemon

Senior AI/ML Engineer

Seattle, WA · On-site

$118K - $163K/yr

Implement scalable model serving architectures forreal-timeand batch inference * Developing ... Partner with AI/ML scientists to productionize models while meeting accuracy, performance ...

lululemon

Senior AI/ML Engineer

Seattle, WA · On-site

$118K - $163K/yr

You will be the technical authority for ML engineering challenges from setting up model training and fine-tuning to architectures and system design for serving AI/ML inference solutions in production.

Amazon

Software Engineer II- AI/ML, AWS Neuron

Seattle, WA · On-site

$111K - $151K/yr

This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch and JAX enabling unparalleled ML inference ...

Amazon

Software Engineer II- AI/ML, AWS Neuron

Seattle, WA

$111K - $151K/yr

This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch and JAX enabling unparalleled ML inference ...

Scale AI

ML Research Engineer, ML Systems

Seattle, WA · On-site

Responsibilities : • Build, profile and optimize our training and inference framework • Collaborate with ML teams to accelerate their research and development and enable them to develop the next ...

Scale AI

ML Research Engineer, ML Systems

Seattle, WA · On-site

Responsibilities : • Build, profile and optimize our training and inference framework • Collaborate with ML teams to accelerate their research and development and enable them to develop the next ...

Scale AI

ML Research Engineer, ML Systems

Seattle, WA · On-site

Responsibilities : • Build, profile and optimize our training and inference framework • Collaborate with ML teams to accelerate their research and development and enable them to develop the next ...

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All JobsMl Inference JobsMl Inference Jobs in Kent, WA

Ml Inference information

See Kent, WA salary details

$42.3K

$138.6K

$221.8K

How much do ml inference jobs pay per year?

As of Jun 13, 2026, the average yearly pay for ml inference in Kent, WA is $138,558.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,200.00 and $153,500.00 per year, depending on experience, location, and employer.

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.
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Ml Inference jobs near you
Software Engineer, Inference AI/ML

Software Engineer, Inference AI/ML

CoreWeave

Bellevue, WA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary:
CoreWeave is The Essential Cloud for AI™, delivering a platform of technology and tools for innovators to build and scale AI. The Software Engineer will join the Inference team to implement features and fixes for model-serving services, focusing on improving latency and reliability on the GPU platform.
Responsibilities:
• Implement well-scoped features and fixes in Python/Go/C++ for model-serving services (e.g., Triton, vLLM, TensorRT-LLM, Ray Serve).
• Write tests, code comments, and short design docs; participate in code reviews.
• Add basic metrics and dashboards; assist with alarms and runbooks.
• Follow on-call runbooks and learn incident response in a guided rotation.
• Contribute to performance experiments (e.g., request batching, concurrency, caching) with guidance.
Qualifications:
Required:
• BS/MS in CS, EE, or related field, or equivalent practical experience.
• Foundations in data structures, algorithms, and networked services.
• Experience with Python or Go (C++ a plus) and Linux fundamentals; Git/CI basics.
• Exposure to containers and Kubernetes (coursework or projects welcome).
• Curiosity about GPU inference concepts (micro-batching, KV cache, streaming).
Preferred:
• Internship or project that deployed a microservice or ML inference demo.
• Coursework/research with PyTorch or TensorFlow; simple CUDA projects a plus.
• Familiarity with Grafana/Prometheus/OpenTelemetry or similar tooling.
Company:
CoreWeave provides cloud infrastructure services designed to support artificial intelligence and high-performance computing workloads. Founded in 2017, the company is headquartered in Livingston, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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