Open MLOps and LLMOps roles: deploying, monitoring and scaling models in production. 20 of these come straight from employers' own careers sites, among them JPMorgan Chase, Caterpillar, Synechron.
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JPMorgan Chase
Senior · 3+ years
Posted today
This role involves designing, developing, and maintaining Java-based backend services and Python-based Databricks applications, with a focus on microservices and AWS deployment.
Caterpillar
Posted yesterday
This role involves deploying and maintaining AI applications, including deep learning, neural networks, and chatbots, to improve performance and efficiency. The MLOps engineer will work on creating CI/CD pipelines, managing models, and collaborating with cross-functional teams.
Synechron
Senior · 10+ years
Posted yesterday
This role involves leading the design, implementation, and governance of enterprise-scale AI and Generative AI solutions, guiding multidisciplinary teams, and ensuring AI initiatives align with business objectives.
Stryker
Senior · 7+ years
Posted 2 days ago
This role involves designing, developing, and maintaining high-performance, scalable MLOps systems and pipelines that interact with AI models in a cloud-native Azure environment, with a focus on Azure Machine Learning.
GE Vernova
Mid level · 3+ years
Posted 2 days ago
This role involves implementing DevOps best practices and optimizing cloud infrastructure to enhance software development and deployment processes, collaborating with teams to boost software quality and delivery, and leveraging cloud platforms like AWS or Azure.
Synechron
Senior · 5+ years
Posted 2 weeks ago
This role involves designing, fine-tuning, and implementing large language models (LLMs), retrieval-augmented generation (RAG) systems, and multimodal agents, with a focus on delivery, performance, and operational security.
Gartner
Director · 9+ years
Posted 3 weeks ago
The Director of Data Engineering will lead the architecture of high‑volume data pipelines, MLOps/LLMOps platforms, and AI model deployment, establishing engineering standards and collaborating with cross‑functional leaders to build scalable, production‑grade data and analytics solutions.
Infosys
Mid level · 3+ years
Posted 3 weeks ago
This role involves consulting on MLOps solutions, translating business requirements into technical solutions, and managing the deployment and operationalization of ML models, primarily using Python and Azure technologies.
EXL Service
Posted 4 weeks ago
This role involves building and operationalizing large-scale AI and NLP solutions on cloud platforms, integrating AI/LLM models into production workflows, and developing scalable data pipelines for processing large volumes of multilingual unstructured text.
Infosys
Posted 4 weeks ago
This role involves designing, deploying, and maintaining scalable MLOps and DevOps solutions on AWS, with a focus on developing and managing CI/CD pipelines for ML model deployment and application releases.
Infosys
Mid level · 5+ years
Posted 29 Sept 2026
This role involves deploying, managing, and optimizing machine learning workloads in production environments, with a focus on the end-to-end ML lifecycle, including model training, deployment, monitoring, automation, performance optimization, and retraining.
Aptiv
5+ years
Posted 28 Sept 2026
This role involves designing, building, and operating production-grade data pipelines and cloud-native services for large volumes of vehicle, sensor, validation, and engineering data. The engineer will work with global teams to make trusted data discoverable, reliable, secure, and ready for analytics and machine learning.
Infosys
Mid level · 2+ years
Posted 19 Sept 2026
This role involves building, automating, and scaling intelligent systems that move from experimentation to production, focusing on CI/CD workflows, infrastructure automation, and MLOps pipelines.
Infosys
Mid level · 3+ years
Posted 19 Sept 2026
This role involves blending DevOps and MLOps practices to build and maintain reliable, scalable, and secure machine learning platforms, focusing on automating pipelines, standardizing deployments, and ensuring smooth transitions from experimentation to production.
Fractal Analytics
Mid level · 3+ years
Posted 15 Sept 2026
This role involves building and maintaining machine learning operations (MLOps) systems, collaborating with data scientists and engineers to deploy and operate advanced analytics models, and automating model development and operations.
Fractal Analytics
Senior · 5+ years
Posted 15 Sept 2026
This role involves building and maintaining machine learning operations (MLOps) systems, collaborating with data scientists and engineers to deploy and operate advanced analytics models, and troubleshooting issues in various environments.
NVIDIA
Senior · 8+ years
Posted 2 Sept 2026
This role involves developing and deploying AI solutions on NVIDIA platforms, advising on ML workloads, and supporting AI initiatives for both internal and external customers, with a focus on performance and scalability.
Fractal Analytics
Senior · 6+ years
Posted 11 Aug 2026
This role involves enabling and automating the end-to-end machine learning lifecycle on Databricks, including building CI/CD infrastructure, deploying ML models, and ensuring scalable job orchestration for AI/ML workloads.
Aptiv
Mid level · 5+ years
Posted 9 Aug 2026
This role involves building and operating MLOps platforms on AWS to support autonomous driving ML workloads, implementing and maintaining highly available, multi-zone training and deployment environments, and operating distributed, multi-GPU training setups.
Quantiphi
Staff · 10+ years
Posted 24 Mar 2026
This role involves leading AI/ML and Generative AI testing strategies, validating ML lifecycle processes, and developing AI testing frameworks, with a focus on AWS services and tools.
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