AI Platform Engineer Jobs

Discover the latest remote and onsite AI Platform Engineer roles across top active AI companies. Updated hourly.

Check out 14 new AI Platform Engineer opportunities posted on The Homebase

Tech Lead, Android Core Product - Malmö, Sweden

New
Top rated
Speechify
Full-time
Full-time
Posted

Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve performance, latency, throughput, and efficiency of deployed models. Build tools to identify bottlenecks and sources of instability, then design and implement solutions to address the highest priority issues.

$140,000 – $200,000
Undisclosed
YEAR

(USD)

Malmö, Sweden
Maybe global
Remote

Tech Lead, Android Core Product - Iași, Romania

New
Top rated
Speechify
Full-time
Full-time
Posted

Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a diverse range of use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve performance, latency, throughput, and efficiency of deployed models. Build tools to provide visibility into bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.

$140,000 – $200,000
Undisclosed
YEAR

(USD)

Iași, Romania
Maybe global
Remote

Tech Lead, Android Core Product - Timișoara, Romania

New
Top rated
Speechify
Full-time
Full-time
Posted

Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases; deploy and operate the core machine learning inference workloads for the AI Voices serving pipeline; introduce new techniques, tools, and architecture to improve the performance, latency, throughput, and efficiency of deployed models; build tools to identify bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.

$140,000 – $200,000
Undisclosed
YEAR

(USD)

Timișoara, Romania
Maybe global
Remote

Tech Lead, Android Core Product - Bath, United Kingdom

New
Top rated
Speechify
Full-time
Full-time
Posted

Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases; deploy and operate core ML inference workloads for the AI Voices serving pipeline; introduce new techniques, tools, and architecture to improve performance, latency, throughput, and efficiency of deployed models; build tools to identify bottlenecks and sources of instability and design and implement solutions to address priority issues.

$140,000 – $200,000
Undisclosed
YEAR

(USD)

Bath, United Kingdom
Maybe global
Remote

Tech Lead, Android Core Product - Newcastle, United Kingdom

New
Top rated
Speechify
Full-time
Full-time
Posted

Work alongside machine learning researchers, engineers, and product managers to bring the AI Voices to customers for a diverse range of use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of deployed models. Build tools to provide visibility into bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues.

$140,000 – $200,000
Undisclosed
YEAR

(USD)

Newcastle, United Kingdom
Maybe global
Remote

Tech Lead, Android Core Product - Nottingham, United Kingdom

New
Top rated
Speechify
Full-time
Full-time
Posted

Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases; deploy and operate the core ML inference workloads for the AI Voices serving pipeline; introduce new techniques, tools, and architecture to improve performance, latency, throughput, and efficiency of deployed models; build tools to identify bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.

$140,000 – $200,000
Undisclosed
YEAR

(USD)

Nottingham, United Kingdom
Maybe global
Remote

Tech Lead, Android Core Product - Cork, Ireland

New
Top rated
Speechify
Full-time
Full-time
Posted

Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases, deploy and operate the core ML inference workloads for AI Voices serving pipeline, introduce new techniques, tools, and architecture to improve performance, latency, throughput, and efficiency of deployed models, build tools to identify bottlenecks and sources of instability, and design and implement solutions to address the highest priority issues.

$140,000 – $200,000
Undisclosed
YEAR

(USD)

Cork, Ireland
Maybe global
Remote

Tech Lead, Android Core Product - Athens, Greece

New
Top rated
Speechify
Full-time
Full-time
Posted

Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a diverse range of use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of deployed models. Build tools to gain visibility into bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues.

$140,000 – $200,000
Undisclosed
YEAR

(USD)

Athens, Greece
Maybe global
Remote

Tech Lead, Android Core Product - Turin, Italy

New
Top rated
Speechify
Full-time
Full-time
Posted

Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a diverse range of use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of deployed models. Build tools to gain visibility into bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues.

$140,000 – $200,000
Undisclosed
YEAR

(USD)

Turin, Italy
Maybe global
Remote

Tech Lead, Android Core Product - The Hague, Netherlands

New
Top rated
Speechify
Full-time
Full-time
Posted

Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for various use cases; deploy and operate the core ML inference workloads for the AI Voices serving pipeline; introduce new techniques, tools, and architecture to improve performance, latency, throughput, and efficiency of deployed models; build tools to identify bottlenecks and instability sources and design and implement solutions to address priority issues.

$140,000 – $200,000
Undisclosed
YEAR

(USD)

The Hague, Netherlands
Maybe global
Remote

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Frequently Asked Questions

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[{"question":"What does a AI Platform Engineer do?","answer":"AI Platform Engineers develop and maintain the infrastructure that supports machine learning workloads. They collaborate with data scientists and software engineers to deploy, manage, and optimize AI models. Their responsibilities include implementing automation pipelines, ensuring 99.9% uptime of AI services, and establishing monitoring systems. They also design platform architectures for model training and deployment at scale, while maintaining security and governance standards."},{"question":"What skills are required for AI Platform Engineer?","answer":"Key skills for AI Platform Engineers include proficiency with cloud platforms (AWS, GCP, Azure), containerization tools like Docker and Kubernetes, and CI/CD pipelines. Experience with MLOps tools such as MLflow, SageMaker, and Azure ML is essential. Strong programming abilities in Python and knowledge of ML frameworks like TensorFlow are valuable. Infrastructure automation skills and understanding of distributed systems are also critical for success in this specialized engineering role."},{"question":"What qualifications are needed for AI Platform Engineer role?","answer":"Most AI Platform Engineer positions require a bachelor's degree in Computer Science, Engineering, or a related technical field. Employers typically look for at least 3 years of experience in platform engineering, DevOps, or AI/ML infrastructure roles. Cloud computing certifications from AWS, GCP, or Azure are highly valued. Practical experience with containerization, MLOps practices, and data pipelines is essential to demonstrate proficiency in building robust AI infrastructure."},{"question":"What is the salary range for AI Platform Engineer job?","answer":"The research provided doesn't include specific salary information for AI Platform Engineers. Compensation typically varies based on location, experience level, company size, and industry. Given the specialized technical knowledge required for AI infrastructure and the critical nature of maintaining high-availability platforms for machine learning workloads, these positions often command competitive salaries in the technology sector."},{"question":"How long does it take to get hired as a AI Platform Engineer?","answer":"The hiring timeline for AI Platform Engineer positions isn't specified in the research. The hiring process typically involves technical assessments of cloud platform knowledge, containerization skills, and MLOps experience. With employers requiring 3+ years of related experience, candidates usually need to demonstrate proficiency in multiple technical domains. Those with relevant backgrounds in platform engineering, DevOps, or ML infrastructure may transition more quickly into these specialized AI jobs."},{"question":"Are AI Platform Engineer job in demand?","answer":"Yes, AI Platform Engineer roles are in high demand as organizations prioritize AI readiness and enterprise-scale adoption through 2026. These specialists are crucial for building the infrastructure necessary to deploy and scale AI capabilities. The specialized knowledge of both platform engineering and AI/ML workloads makes qualified candidates particularly valuable as companies seek to maintain 99.9% uptime for critical AI services while scaling their machine learning operations."}]