machine learning platform engineer

Glow Beauty On Demand

Job Title ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Job Description ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Location: Dubai, UAE Industry: Technology / AI / Food &amp; Q-commerce Function: Machine Learning Engineering Gender: Any Candidate Nationality: Any Job Type: Full-time Role Overview Talabat, the leading on-demand food and Q-commerce app in the region, is seeking an experienced ML Platform Engineer to design, develop, and scale robust machine learning and generative AI platforms. The role involves building end-to-end ML infrastructure, enabling fast experimentation, efficient model deployment, and seamless monitoring to support next-generation AI-driven solutions for millions of users. Key Responsibilities * Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models * Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes * Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate * Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference * Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability * Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals * Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components * Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows Qualifications and Experience * Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) * Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles * Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain * Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm) * Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis * Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems * Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies

ML Platform Engineer

Job Title ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Job Description ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Location: Dubai, UAE Industry: Technology / AI / Food &amp; Q-commerce Function: Machine Learning Engineering Gender: Any Candidate Nationality: Any Job Type: Full-time Role Overview Talabat, the leading on-demand food and Q-commerce app in the region, is seeking an experienced ML Platform Engineer to design, develop, and scale robust machine learning and generative AI platforms. The role involves building end-to-end ML infrastructure, enabling fast experimentation, efficient model deployment, and seamless monitoring to support next-generation AI-driven solutions for millions of users. Key Responsibilities * Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models * Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes * Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate * Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference * Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability * Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals * Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components * Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows Qualifications and Experience * Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) * Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles * Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain * Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm) * Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis * Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems * Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies

Job Title ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Job Description ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Location: Dubai, UAE Industry: Technology / AI / Food &amp; Q-commerce Function: Machine Learning Engineering Gender: Any Candidate Nationality: Any Job Type: Full-time Role Overview Talabat, the leading on-demand food and Q-commerce app in the region, is seeking an experienced ML Platform Engineer to design, develop, and scale robust machine learning and generative AI platforms. The role involves building end-to-end ML infrastructure, enabling fast experimentation, efficient model deployment, and seamless monitoring to support next-generation AI-driven solutions for millions of users. Key Responsibilities * Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models * Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes * Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate * Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference * Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability * Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals * Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components * Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows Qualifications and Experience * Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) * Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles * Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain * Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm) * Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis * Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems * Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies

ML Platform Engineer Generative AI & Machine Learning Infrastructure

Job Title ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Job Description ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Location: Dubai, UAE Industry: Technology / AI / Food &amp; Q-commerce Function: Machine Learning Engineering Gender: Any Candidate Nationality: Any Job Type: Full-time Role Overview Talabat, the leading on-demand food and Q-commerce app in the region, is seeking an experienced ML Platform Engineer to design, develop, and scale robust machine learning and generative AI platforms. The role involves building end-to-end ML infrastructure, enabling fast experimentation, efficient model deployment, and seamless monitoring to support next-generation AI-driven solutions for millions of users. Key Responsibilities * Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models * Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes * Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate * Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference * Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability * Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals * Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components * Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows Qualifications and Experience * Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) * Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles * Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain * Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm) * Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis * Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems * Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies What We Offer * Opportunity to work on advanced ML and AI projects impacting millions of users in the Middle East * Competitive salary and benefits package * A collaborative, innovation-driven environment with cutting-edge tools and technologies * Career development in one of the fastest-growing tech ecosystems in the region

ML Platform Engineer Generative AI & Machine Learning

Allstate Insurance

<div>At Allstate, great things happen when our people work together to protect families and their belongings from life&rsquo;s uncertainties. And for more than 90 years our innovative drive has kept us a step ahead of our customers&rsquo; evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection.
Job Description
We are looking for a Cloud Platform Engineer to support and accelerate our Machine Learning development and deployment workflows. In this role, you'll work at the intersection of machine learning, infrastructure, and software engineering&mdash;building tools and platforms that empower data scientists and ML engineers to iterate, deploy, and scale models efficiently. 
 
You will leverage test driven development and continuous integration to ensure agility and quality of products. You will actively participate in the decision-making process of the team ensuring that the simplest appropriate technology and design is chosen to meet user needs. 
 
The internal Allstate job title used for this role is Cloud Platform Engineer Senior Consultant II.<h3 class="jobSectionHeader">
Key Responsibilities</h3>
Designs, builds, and maintains infrastructure for ML experimentation, model training, and deployment.<ul><li>
Develops and manages CI/CD pipelines for ML workflows (data ingestion, model training, testing, and deployment).</li><li>
Implements and manages ML platforms (e.g., MLflow, Kubeflow, SageMaker, Vertex AI) to support reproducibility and scalability.</li><li>
Creates tools and environments to automate data versioning, model tracking, and artifact management.</li><li>
Collaborates with data scientists to enable self-service access to compute resources and production systems.</li><li>
Monitors, logs, and alerts on ML system health and model performance in production.</li><li>
Enforces MLOps best practices across teams, including governance, model validation, and rollback strategies.</li><li>
Ensures infrastructure security, cost-efficiency, and compliance.</li><li>
Practices daily paired programming and test-driven development in writing software and building product</li><li>
Participates in executing the strategy, keeping the customer needs and wants in mind</li><li>
Establishes continuous integration, continuous delivery, and continuous deployment pipelines and practices</li><li>
Participates in retrospectives to gather feedback and derive actionable items to improve the team and the product</li><li>
Participates in iteration planning meetings ensuring that the team has a common understanding of each story and chores in a team&rsquo;s backlog</li></ul><h3 class="jobSectionHeader">
Education</h3><ul><li>4 year Bachelors Degree (Preferred)</li></ul><h3 class="jobSectionHeader">
Experience</h3><ul><li>
2+ years of experience with software development languages such as Python, Java. (Preferred)</li><li>
2+ years of experience with Cloud Technologies such as Azure and/or AWS. (Preferred)</li><li>
1+ years of experience with DevOps. (Preferred)</li><li>
1+ years of experienced with Infrastructure as Code technologies such as Terraform, Cloud Formation etc. (Preferred)</li><li>
Exposure to machine learning frameworks and distributed data processing tools like Apache Spark or equivalents.</li></ul><h3 class="jobSectionHeader">
Supervisory Responsibilities</h3><ul><li>This job does not have supervisory duties.</li></ul><h3 class="jobSectionHeader">
Education &amp; Experience (in lieu)</h3><ul><li>In lieu of the above education requirements, an equivalent combination of education and experience may be considered.</li></ul>
Primary Skills
Shift Time
Shift B (India)
Recruiter Info
Shriya Kumari
skuow@allstate.com
About Allstate
Joining our team isn&rsquo;t just a job &mdash; it&rsquo;s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger &ndash; a winning team making a meaningful impact.
The Allstate Corporation is one of the largest publicly held insurance providers in the United States. Ranked No. 84 in the 2023 Fortune 500 list of the largest United States corporations by total revenue, The Allstate Corporation owns and operates 18 companies in the United States, Canada, Northern Ireland, and India. Allstate India Private Limited, also known as Allstate India, is a subsidiary of The Allstate Corporation. The India talent center was set up in 2012 and operates under the corporation's Good Hands promise. As it innovates operations and technology, Allstate India has evolved beyond its technology functions to be the critical strategic business services arm of the corporation. With offices in Bengaluru and Pune, the company offers expertise to the parent organization&rsquo;s business areas including technology and innovation, accounting and imaging services, policy administration, transformation solution design and support services, transformation of property liability service design, global operations and integration, and training and transition.
Learn more about Allstate India here.</div>

Cloud Platform Engineer Consultant II

Delivery Hero

<div>Company Description 
Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat&rsquo;s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.
We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.
Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner. 
Job Description 
Summary
 As the leading delivery platform in the region, we have a unique responsibility and opportunity to positively impact millions of customers, restaurant partners, and riders. To achieve our mission, we must scale and continuously evolve our machine learning capabilities, including cutting-edge Generative AI (genAI) initiatives. This demands robust, efficient, and scalable ML platforms that empower our teams to rapidly develop, deploy, and operate intelligent systems.
As an ML Platform Engineer, your mission is to design, build, and enhance the infrastructure and tooling that accelerates the development, deployment, and monitoring of traditional ML and genAI models at scale. You&rsquo;ll collaborate closely with data scientists, ML engineers, genAI specialists, and product teams to deliver seamless ML workflows&mdash;from experimentation to production serving&mdash;ensuring operational excellence across our ML and genAI systems. 
Qualifications 
Responsibilities<ul><li>
Design, build, and maintain scalable, reusable, and reliable ML platforms and tooling that support the entire ML lifecycle, including data ingestion, model training, evaluation, deployment, and monitoring for both traditional and generative AI models. 
</li><li>Develop standardized ML workflows and templates using MLflow and other platforms, enabling rapid experimentation and deployment cycles. 
</li><li>Implement robust CI/CD pipelines, Docker containerization, model registries, and experiment tracking to support reproducibility, scalability, and governance in ML and genAI. 
</li><li>Collaborate closely with genAI experts to integrate and optimize genAI technologies, including transformers, embeddings, vector databases (e.g., Pinecone, Redis, Weaviate), and real-time retrieval-augmented generation (RAG) systems. 
</li><li>Automate and streamline ML and genAI model training, inference, deployment, and versioning workflows, ensuring consistency, reliability, and adherence to industry best practices. 
</li><li>Ensure reliability, observability, and scalability of production ML and genAI workloads by implementing comprehensive monitoring, alerting, and continuous performance evaluation. 
</li><li>Integrate infrastructure components such as real-time model serving frameworks (e.g., TensorFlow Serving, NVIDIA Triton, Seldon), Kubernetes orchestration, and cloud solutions (AWS/GCP) for robust production environments. 
</li><li>Drive infrastructure optimization for generative AI use-cases, including efficient inference techniques (batching, caching, quantization), fine-tuning, prompt management, and model updates at scale. 
</li><li>Partner with data engineering, product, infrastructure, and genAI teams to align ML platform initiatives with broader company goals, infrastructure strategy, and innovation roadmap. 
</li><li>Contribute actively to internal documentation, onboarding, and training programs, promoting platform adoption and continuous improvement.</li></ul>
Requirements
Technical Experience<ul><li>
Strong software engineering background with experience in building distributed systems or platforms designed for machine learning and AI workloads. 
</li><li>Expert-level proficiency in Python and familiarity with ML frameworks (TensorFlow, PyTorch), infrastructure tooling (MLflow, Kubeflow, Ray), and popular APIs (Hugging Face, OpenAI, LangChain). 
</li><li>Experience implementing modern MLOps practices, including model lifecycle management, CI/CD, Docker, Kubernetes, model registries, and infrastructure-as-code tools (Terraform, Helm). 
</li><li>Demonstrated experience working with cloud infrastructure, ideally AWS or GCP, including Kubernetes clusters (GKE/EKS), serverless architectures, and managed ML services (e.g., Vertex AI, SageMaker). 
</li><li>Proven experience with generative AI technologies: transformers, embeddings, prompt engineering strategies, fine-tuning vs. prompt-tuning, vector databases, and retrieval-augmented generation (RAG) systems. 
</li><li>Experience designing and maintaining real-time inference pipelines, including integrations with feature stores, streaming data platforms (Kafka, Kinesis), and observability platforms. 
</li><li>Familiarity with SQL and data warehouse modeling; capable of managing complex data queries, joins, aggregations, and transformations. 
</li><li>Solid understanding of ML monitoring, including identifying model drift, decay, latency optimization, cost management, and scaling API-based genAI applications efficiently.</li></ul>
Qualifications<ul><li>
Bachelor&rsquo;s degree in Computer Science, Engineering, or a related field; advanced degree is a plus. 
</li><li>2+ years in a tech lead role, 5+ years of experience in ML platform engineering, ML infrastructure, generative AI, or closely related roles.</li><li>
Proven track record of successfully building and operating ML infrastructure at scale, ideally supporting generative AI use-cases and complex inference scenarios. 
</li><li>Strategic mindset with strong problem-solving skills and effective technical decision-making abilities. 
</li><li>Excellent communication and collaboration skills, comfortable working cross-functionally across diverse teams and stakeholders. 
</li><li>Strong sense of ownership, accountability, pragmatism, and proactive bias for action.</li></ul></div>

Staff Engineer - ML Platform

EPAM Systems

<div>We are seeking a Senior Data DevOps Engineer to support and optimize our data platform within Azure environments.
You will play a key role in deploying and maintaining scalable, secure data infrastructures while collaborating with various teams to enhance data workflows and CI/CD pipelines. Your expertise with Databricks and Azure tools will be essential to ensure smooth operations and continuous improvement of our data systems. Join us to contribute your skills in a dynamic environment focused on advanced data solutions.
Responsibilities<ul><li>
Deploy and configure data platforms in Databricks according to approved architecture and solutions ensuring production readiness and scalability</li><li>
Collaborate with cross-functional teams including data engineering, machine learning, platform, and quality assurance to design and maintain CI/CD pipelines and supporting tools for data workflows</li><li>
Diagnose and resolve issues related to build and deployment pipelines, data workflows, and production workloads including performing root cause analysis and implementing preventive solutions</li><li>
Develop and standardize configuration management practices covering infrastructure configuration, environment parameters, secrets management, and cluster policies to maintain consistency</li><li>
Produce and update technical documentation such as deployment guides, operational runbooks, pipeline logic, and platform configurations</li><li>
Implement governance and security best practices for data platform environments</li><li>
Support automation efforts to promote efficient environment deployment and pipeline operations</li><li>
Participate in continuous improvement initiatives for data platform infrastructure and workflows</li></ul>
Requirements<ul><li>
Experience of 3 or more years in roles such as Build Engineer, DevOps Engineer, or Platform Engineer supporting delivery and operations</li><li>
Proficiency in Databricks, Azure Data Factory, Azure DevOps, and general Microsoft Azure environment management</li><li>
Knowledge of DataOps practices, including automated deployment of data pipelines, environment promotion, and governance</li><li>
Experience in troubleshooting and resolving pipeline and production data workflow issues</li><li>
Strong communication and collaboration capabilities to work effectively with engineering, data, and operations teams</li><li>
English language proficiency at the B2 level or higher for participation in technical discussions and documentation preparation</li><li>
Ability to produce and maintain clear technical documentation and runbooks</li></ul>
Nice to have<ul><li>
Experience with MLOps including model deployment, monitoring, and lifecycle automation for machine learning workloads</li></ul>
We offer<ul><li>
CONTINUOUS UPSKILLING, LEARNING &amp; DEVELOPMENT<ul><li>
Diversity of tasks and projects</li><li>
Assessment center for objective review of competency level</li><li>
Personal development plan</li><li>
Mentoring programs and leadership development</li><li>
Certification and professional development support</li><li>
Access to learning platforms including more than 2,500 internal courses and the LinkedIn Learning library with 20,000+ courses</li><li>
English courses taught by certified teachers</li></ul></li><li>
CORPORATE BENEFITS<ul><li>
Extra leave days</li><li>
Referral bonuses</li></ul></li><li>
COMPENSATION PACKAGE<ul><li>
Competitive compensation paid in USD</li><li>
Regular salary and performance reviews</li></ul></li><li>
MEDICAL &amp; HEALTHCARE<ul><li>
Private health insurance</li><li>
Well-being events</li></ul></li><li>
WORKING ENVIRONMENT<ul><li>
Recreation areas and kitchens</li><li>
Tea, coffee, and snacks</li><li>
Well-being events</li><li>
Sports equipment and game consoles</li><li>
IT Equipment</li><li>
Microsoft's Software Assurance Home Use Program (HUP)</li></ul></li></ul>
EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.</div>

Senior Data DevOps Engineer with Azure

Search 10000+ Machine learning platform engineer jobs near you this November. New roles added regularly across leading industries. Apply today.

10000 machine learning platform engineer jobs NEAR_ME

ML Platform Engineer

ML Platform Engineer

ML Platform Engineer Generative AI & Machine Learning Infrastructure

ML Platform Engineer Generative AI & Machine Learning

Cloud Platform Engineer Consultant II

Staff Engineer - ML Platform

Senior Data DevOps Engineer with Azure