AI / ML Solutions Engineer Job at Cerebras in New Bremen
Cerebras, New Bremen, OH, United States
Location
Remote
Employment Type
Full time
Location Type
Remote
Department
Customer Solutions Group
About Anyscale
At Anyscale, we’re on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray, a popular open‑source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, Spotify, Instacart, Cruise, and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world.
With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert.
Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date.
About the role
We are looking for an AI / ML Solutions Engineer to join Anyscale’s Professional Services team and work directly with customers to design, implement, and scale machine learning and AI workloads using Ray and Anyscale.
This role is ideal for a hands‑on Machine Learning Engineer or MLOps Engineer who enjoys solving real‑world production problems alongside customer teams. You will guide customers through architectural decisions, application refactors, and operational best practices as they adopt Ray for distributed training, data processing, inference, and ML workflows.
In addition to implementation work, you’ll play a key role in enabling customer ML and MLOps teams—helping them understand why architectural changes are needed and how to successfully operate Ray‑based systems in production.
What You’ll Do
Customer Delivery & Implementation
Implement production AI / ML workloads using Ray and Anyscale, such as:
Distributed model training
Scalable inference and serving
Data preprocessing and feature pipelines
Work hands‑on with customer codebases to refactor or adapt existing workloads to Ray
Architecture & Technical Guidance
Advise customers on ML system architecture, including:
Application design for distributed execution
Resource management and scaling strategies
Reliability, fault tolerance, and performance tuning
Guide customers through architectural and operational changes required to adopt Ray and Anyscale effectively
MLOps Enablement
Partner with customer MLE and MLOps teams to integrate Ray into existing platforms and workflows
Support CI/CD, monitoring, retraining, and operational best practices
Help customers transition from experimentation to production‑grade ML systems
Technical Enablement & Knowledge Transfer
Enable customer teams through working sessions, design reviews, training delivery, and hands‑on guidance
Contribute feedback from the field to product, engineering, and education teams
Help develop reference architectures, examples, and best practices based on real customer use cases
What We’re Looking For
Required Experience
5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or ML Systems Engineer
Strong proficiency in Python and experience building production ML systems
Hands‑on experience with distributed systems or scalable ML frameworks (Ray, Spark, Dask, Kubernetes, etc.)
Experience with one or more of:
Distributed training (multi‑node / multi‑GPU)
Model serving and scalable inference
Data pipelines and workflow orchestration
Comfort working directly with customers in a consultative, problem‑solving role
Strong communication skills and ability to explain technical tradeoffs clearly
Preferred Experience
Experience supporting or deploying ML platforms or internal ML infrastructure
Familiarity with cloud environments (AWS, GCP, Azure)
Exposure to MLOps tooling (MLflow, Airflow, Dagster, Kubeflow, etc.)
Prior experience in Professional Services, Consulting, or Customer Engineering roles
Why Join Anyscale Professional Services
Work directly on real‑world AI / ML systems at scale
Partner with leading ML teams across industries
Influence how Ray and Anyscale are adopted in production environments
Combine deep engineering work with customer impact
Competitive compensation, equity, and flexible remote work
Anyscale Inc. is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law.
Anyscale Inc. is an E-Verify company and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish.
#J-18808-Ljbffr
In Summary: Anyscale is on a mission to democratize distributed computing and make it accessible to software developers of all skill levels . The role is ideal for a hands‑on Machine Learning Engineer or MLOps Engineer who enjoys solving real‑world production problems alongside customer teams . We're looking for an AI / ML Solutions Engineer to join the Professional Services team .
En Español: En cualquier escala, estamos en una misión de democratizar la computación distribuida y hacerla accesible a desarrolladores de software de todos los niveles de habilidad. Estamos comercializando Ray, un popular proyecto open-source que está creando un ecosistema de bibliotecas para el aprendizaje automático escalables. Empresas como OpenAI, Uber, Spotify, Instacart, Cruise y muchas más tienen Ray en sus pilas tecnológicas para acelerar el progreso de las aplicaciones de IA hacia el mundo real. Con Anyscale, construimos el mejor lugar para ejecutar Ray, por lo que cualquier desarrollador o científico de datos pueda escalar una aplicación desde su cluster hasta el ML sin necesidad de ser experto en sistemas distribuidos. Además del trabajo de implementación, desempeñará un papel clave en capacitar a los equipos ML y MLOps clientes ayudándoles a comprender por qué se necesitan cambios arquitectónicos y cómo operar con éxito sistemas basados en rayos en la producción. Lo que harás entrega y implementación del cliente Implementar cargas de trabajo AI / ML de producción utilizando Ray y Anyscale, tales como: capacitación de modelos distribuidos Inferencia escalable y servicio Preprocesamiento de datos y tuberías de funciones Trabajar en mano con las bases de código de clientes para refactar o adaptar las cargas existentes a Ray Arquitectura & Orientación Técnica Asesorar a los clientes sobre la arquitectura del sistema ML, incluyendo: Diseño de aplicaciones para gestión de recursos distribuidos y estrategias de ampliación Confiabilidad, tolerancia a fallos y ajuste al rendimiento Guía de clientes a través de cambios arquitectónicos y operativos necesarios para adoptar eficazmente sistemas MLOps Propuesta de colaboración con el cliente MLE y Ejemplos MLOPS Para integrar las plataformas ya existentes y flujos de trabajo A partir de Ray Arquitetura y orientación técnica Conseguir asesoramiento de los clientes acerca de la arquitectotecnia ML/Dirección Tecnológico Las prácticas de fabricación, monitoreo, orientación y rehabilitación de conocimientos experimentales GPLS. es un Empleador de Igualdad en Oportunidades. Los candidatos son evaluados sin tener en cuenta la edad, raza, color, religión, sexo, discapacidad, origen nacional, orientación sexual, estatus de veterano o cualquier otra característica protegida por las leyes federales o estatales. Anyscale Inc. es una empresa E-Verify y puede revisar el Aviso de Participación de Verificación Electrónica y los carteles del derecho a trabajar en inglés y español. #J-18808-Ljbffr
Remote
Employment Type
Full time
Location Type
Remote
Department
Customer Solutions Group
About Anyscale
At Anyscale, we’re on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray, a popular open‑source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, Spotify, Instacart, Cruise, and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world.
With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert.
Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date.
About the role
We are looking for an AI / ML Solutions Engineer to join Anyscale’s Professional Services team and work directly with customers to design, implement, and scale machine learning and AI workloads using Ray and Anyscale.
This role is ideal for a hands‑on Machine Learning Engineer or MLOps Engineer who enjoys solving real‑world production problems alongside customer teams. You will guide customers through architectural decisions, application refactors, and operational best practices as they adopt Ray for distributed training, data processing, inference, and ML workflows.
In addition to implementation work, you’ll play a key role in enabling customer ML and MLOps teams—helping them understand why architectural changes are needed and how to successfully operate Ray‑based systems in production.
What You’ll Do
Customer Delivery & Implementation
Implement production AI / ML workloads using Ray and Anyscale, such as:
Distributed model training
Scalable inference and serving
Data preprocessing and feature pipelines
Work hands‑on with customer codebases to refactor or adapt existing workloads to Ray
Architecture & Technical Guidance
Advise customers on ML system architecture, including:
Application design for distributed execution
Resource management and scaling strategies
Reliability, fault tolerance, and performance tuning
Guide customers through architectural and operational changes required to adopt Ray and Anyscale effectively
MLOps Enablement
Partner with customer MLE and MLOps teams to integrate Ray into existing platforms and workflows
Support CI/CD, monitoring, retraining, and operational best practices
Help customers transition from experimentation to production‑grade ML systems
Technical Enablement & Knowledge Transfer
Enable customer teams through working sessions, design reviews, training delivery, and hands‑on guidance
Contribute feedback from the field to product, engineering, and education teams
Help develop reference architectures, examples, and best practices based on real customer use cases
What We’re Looking For
Required Experience
5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or ML Systems Engineer
Strong proficiency in Python and experience building production ML systems
Hands‑on experience with distributed systems or scalable ML frameworks (Ray, Spark, Dask, Kubernetes, etc.)
Experience with one or more of:
Distributed training (multi‑node / multi‑GPU)
Model serving and scalable inference
Data pipelines and workflow orchestration
Comfort working directly with customers in a consultative, problem‑solving role
Strong communication skills and ability to explain technical tradeoffs clearly
Preferred Experience
Experience supporting or deploying ML platforms or internal ML infrastructure
Familiarity with cloud environments (AWS, GCP, Azure)
Exposure to MLOps tooling (MLflow, Airflow, Dagster, Kubeflow, etc.)
Prior experience in Professional Services, Consulting, or Customer Engineering roles
Why Join Anyscale Professional Services
Work directly on real‑world AI / ML systems at scale
Partner with leading ML teams across industries
Influence how Ray and Anyscale are adopted in production environments
Combine deep engineering work with customer impact
Competitive compensation, equity, and flexible remote work
Anyscale Inc. is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law.
Anyscale Inc. is an E-Verify company and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish.
#J-18808-Ljbffr
In Summary: Anyscale is on a mission to democratize distributed computing and make it accessible to software developers of all skill levels . The role is ideal for a hands‑on Machine Learning Engineer or MLOps Engineer who enjoys solving real‑world production problems alongside customer teams . We're looking for an AI / ML Solutions Engineer to join the Professional Services team .
En Español: En cualquier escala, estamos en una misión de democratizar la computación distribuida y hacerla accesible a desarrolladores de software de todos los niveles de habilidad. Estamos comercializando Ray, un popular proyecto open-source que está creando un ecosistema de bibliotecas para el aprendizaje automático escalables. Empresas como OpenAI, Uber, Spotify, Instacart, Cruise y muchas más tienen Ray en sus pilas tecnológicas para acelerar el progreso de las aplicaciones de IA hacia el mundo real. Con Anyscale, construimos el mejor lugar para ejecutar Ray, por lo que cualquier desarrollador o científico de datos pueda escalar una aplicación desde su cluster hasta el ML sin necesidad de ser experto en sistemas distribuidos. Además del trabajo de implementación, desempeñará un papel clave en capacitar a los equipos ML y MLOps clientes ayudándoles a comprender por qué se necesitan cambios arquitectónicos y cómo operar con éxito sistemas basados en rayos en la producción. Lo que harás entrega y implementación del cliente Implementar cargas de trabajo AI / ML de producción utilizando Ray y Anyscale, tales como: capacitación de modelos distribuidos Inferencia escalable y servicio Preprocesamiento de datos y tuberías de funciones Trabajar en mano con las bases de código de clientes para refactar o adaptar las cargas existentes a Ray Arquitectura & Orientación Técnica Asesorar a los clientes sobre la arquitectura del sistema ML, incluyendo: Diseño de aplicaciones para gestión de recursos distribuidos y estrategias de ampliación Confiabilidad, tolerancia a fallos y ajuste al rendimiento Guía de clientes a través de cambios arquitectónicos y operativos necesarios para adoptar eficazmente sistemas MLOps Propuesta de colaboración con el cliente MLE y Ejemplos MLOPS Para integrar las plataformas ya existentes y flujos de trabajo A partir de Ray Arquitetura y orientación técnica Conseguir asesoramiento de los clientes acerca de la arquitectotecnia ML/Dirección Tecnológico Las prácticas de fabricación, monitoreo, orientación y rehabilitación de conocimientos experimentales GPLS. es un Empleador de Igualdad en Oportunidades. Los candidatos son evaluados sin tener en cuenta la edad, raza, color, religión, sexo, discapacidad, origen nacional, orientación sexual, estatus de veterano o cualquier otra característica protegida por las leyes federales o estatales. Anyscale Inc. es una empresa E-Verify y puede revisar el Aviso de Participación de Verificación Electrónica y los carteles del derecho a trabajar en inglés y español. #J-18808-Ljbffr