ml platform engineer

DeepSource Technologies

<div>We are looking for a highly capable Senior AI Engineer / MLOps Engineer to join our team and lead the design, development, deployment, and optimization of scalable, production-grade AI and machine learning solutions. The ideal candidate will have strong hands-on experience across AI engineering, machine learning, MLOps, cloud-native architecture, and data engineering, with the ability to transform experimentation into reliable, business-ready systems.
This role requires deep expertise in LLMs, RAG, agentic AI workflows, CI/CD automation, production ML lifecycle management, and modern data platforms. The selected candidate will be expected to lead end-to-end AI initiatives, work across multiple projects, collaborate with technical and business stakeholders, and ensure operational excellence across AI platforms.
Key Responsibilities<ul><li>Design, develop, deploy, and maintain production-grade AI and machine learning systems end to end.</li><li>Build and optimize LLM-powered applications, including RAG pipelines, prompt workflows, agent-based systems, and multimodal AI use cases.</li><li>Develop intelligent workflows using tool-calling, orchestration frameworks, and contextual reasoning patterns.</li><li>Fine-tune, evaluate, and operationalize machine learning and foundation models for enterprise use cases.</li><li>Build and manage MLOps pipelines covering training, evaluation, model registration, deployment, monitoring, and retraining.</li><li>Implement CI/CD pipelines for ML and AI workflows to support automated testing, release management, and controlled deployments.</li><li>Establish model monitoring frameworks for drift detection, feature attribution, inference quality, and performance tracking.</li><li>Ensure reproducibility, reliability, and version control across AI/ML environments.</li><li>Architect scalable AI/ML platforms using modern compute, storage, orchestration, monitoring, and search services.</li><li>Build repeatable environments using Infrastructure as Code.</li><li>Support secure, high-availability, and cost-efficient deployment models across development, staging, and production environments.</li><li>Design scalable inference and serving patterns for variable workloads.</li><li>Build and maintain automated data pipelines, ETL/ELT workflows, and data processing frameworks for AI/ML consumption.</li><li>Ensure data quality, lineage, governance, and versioning to support dependable model training and inference.</li><li>Work with structured and unstructured datasets across data lakes, data warehouses, and operational systems.</li><li>Deliver analytics-ready datasets to downstream systems and applications.</li><li>Lead multiple AI initiatives in parallel, including planning, execution, and coordination with internal teams and stakeholders.</li><li>Work closely with product, engineering, data, and business teams to deliver production-ready AI capabilities.</li><li>Contribute to architecture decisions, technical documentation, best practices, and engineering standards.</li><li>Support knowledge sharing, technical leadership, and continuous improvement across the AI function. 
</li></ul> 
 
Requirements<ul><li> 
Bachelor&rsquo;s degree in Computer Engineering, Computer Science, Artificial Intelligence, Data Science, or a related field.</li><li>5+ years of hands-on experience in AI engineering, machine learning engineering, MLOps, or data/ML platform engineering.</li><li>Proven experience deploying production AI/ML solutions in enterprise environments.</li><li>Strong programming experience in Python and SQL.</li><li>Strong experience with enterprise AI/ML architecture and delivery.</li></ul></div>

AI Architect - Riyadh,KSA

Openkyber

<div>Job Title: AI / ML Engineer 
Location: Dallas, TX or Memphis, TN Hybrid 
Duration: 6+ Months
Project Role : AI / ML Engineer
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution and developing AI applications using LLMs, RAG (Retrieval-Augmented Generation), and particularly agentic AI solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills :
<ul><li>Advanced knowledge of Python specifically for machine learning and data science.</li>
<li>Experience with LLM frameworks such as LangChain, LlamaIndex, Semantic Kernel, or AutoGen.</li>
<li>Proficiency in cloud services related to ML/AI (e.g., Azure, OpenAI, Hugging Face, AWS, Google Cloud Platform).</li>
<li>Extensive experience in AI/ML development, particularly in NLP, and machine learning domains.</li>
<li>Hands-on experience in developing AI applications using LLMs, RAG (Retrieval-Augmented Generation), and particularly agentic AI solutions is essential</li>
<li>Proficiency in designing and maintaining AI/ML solutions that are cost-effective, accurate, and scalable.</li>
<li>Exceptional problem-solving skills and the ability to think analytically.</li>
<li>Strong communication and interpersonal skills, with the aptitude to navigate complex project requirements with clients and stakeholders.</li>
</ul>Nice to have: Certification as an Azure AI Engineer Associate or equivalent credentials is highly advantageous.
Experience with ML/DL frameworks like TensorFlow, Keras, PyTorch, and scikit-learn.
Experience with C# or Java, node.js.
With Regards, OpenKyber 
7525 Mitchell Road, Suite 106, Eden Prairie, MN 55344 
Email ID - hirings@openkyber.com
For applications and inquiries, contact: hirings@openkyber.com</div>

OCI AI Services Engineer

SARJ

<div>Sarj.ai is hiring an AI/ML Engineer to train and deploy speech models that power our voice communications platform. We work in Python and PyTorch on GCP. Strong deep learning fundamentals highly appreciated.<h3 class="jobSectionHeader">
What you'll do</h3><ul><li>
Train large-scale speech models (STT/TTS)</li><li>
Work with modern speech architectures and push them to production</li><li>
Build and maintain ML training pipelines for real-time voice processing</li><li>
Develop evaluation frameworks and improve model performance</li><li>
Collaborate with product and engineering to ship AI-powered features</li></ul><h3 class="jobSectionHeader">
What we're looking for</h3><ul><li>
2+ years working with ML in production</li><li>
Strong Python + PyTorch/PyTorch Lightning</li><li>
Understanding of deep learning fundamentals</li><li>
Experience with speech/audio ML is a strong plus</li><li>
Experience with large-scale or distributed training</li><li>
Familiarity with GCP (Vertex AI, Cloud Run, BigQuery)</li></ul></div>

AI Research Engineer

Faze 3 Consulting

AI/ML/DevOps EngineerOwn the MLOps platform that powers enterprise AI at scale.A leading Abu Dhabi-based holding group is hiring an AI/ML/DevOps Engineer to architect, operate, and continuously improve the end-to-end MLOps and LLMOps platform for a flagship enterprise AI programme. You'll be the technical authority reviewing, governing, and signing off CI/CD, data and model pipelines, infrastructure, deployment, security, and observability &mdash; ensuring secure, scalable, and compliant delivery across environments. Reports to the AI Product Manager within the AI Excellence Centre.What you'll own:<ul><li>Own the end-to-end MLOps/LLMOps reference architecture: ingestion &rarr; validation &rarr; feature and embedding pipelines &rarr; training and fine-tuning &rarr; evaluation &rarr; registry &rarr; deployment &rarr; monitoring &mdash; including RAG and agentic workflows.</li><li>Architect, review, and approve CI/CD for ML and LLM systems: code, data, prompt, and model artifact versioning; build and release pipelines (Azure DevOps / GitHub Actions); automated unit, integration, and contract testing; and promotion/rollback (blue-green / canary) across dev, test, and production.</li><li>Define and govern AI platform foundations on Azure: IaC (Bicep/Terraform), AML workspaces, AKS GPU node pools and scheduling, private networking (VNet integration / Private Link), identity (Managed Identities / PIM), secrets (Key Vault), and encryption and data residency controls.</li><li>Review and approve production deployment patterns for model and LLM serving (AKS / KServe / AML online endpoints), including containerization, inference optimization (batching, quantization where applicable), API management, autoscaling, resiliency, and RAG runtime components (vector store, retriever, re-ranker, cache).</li><li>Own observability and reliability for AI services: OpenTelemetry tracing, prompt and inference logs (with PII controls), latency/throughput/cost metrics, SLOs/SLIs, model performance monitoring, data and model drift detection, and LLM evaluations (quality, hallucination checks, toxicity and safety guardrails) with incident playbooks.</li><li>Establish and enforce MLOps/LLMOps governance: dataset lineage, data quality validation (schema and tests), feature store and model registry standards, artifact provenance (SBOM/SLSA), vulnerability scanning, approval gates for model and prompt releases, and compliance-aligned documentation for model risk (intended use, limitations, evaluation results).</li><li>Enable delivery squads &mdash; including the primary delivery partner &mdash; with &quot;golden path&quot; templates (AML pipelines, RAG blueprints, evaluation harnesses), reusable IaC modules, and coding standards; run deep technical design and architecture reviews and sign off production readiness (capacity, security, observability, DR) for all AI releases.</li><li>Support the Run &amp; Operate model by enabling issue triage and minor enhancement workflows (ticket intake &rarr; fix &rarr; controlled release), ensuring changes follow the same release governance and quality gates.</li><li>Own the Operational Acceptance Gate: no production release without runbooks, monitoring dashboards, incident playbooks, access model, and DR test evidence.</li></ul>Scope clarity: you provide platform standards, review, and sign-off &mdash; you do not replace the delivery partner's engineering, but you enforce the &quot;golden path&quot; and production readiness bar.What you bring:<ul><li>8&ndash;10 years across DevOps, SRE, and/or ML Engineering with production systems on Azure.</li><li>Hands-on experience with Azure ML, AKS, Azure DevOps or GitHub Actions, IaC, and containerization.</li><li>Bachelor's in Computer Science, Engineering, or equivalent experience.</li></ul>Core skills required:<ul><li>Python, YAML, Docker, Helm, KQL; GitOps (Argo/Flux) awareness.</li><li>Security in CI/CD: SAST/DAST, supply-chain security (Sigstore), secrets management (Key Vault).</li><li>Performance testing (k6 / JMeter), contract testing, and E2E testing.</li><li>Cost optimization and capacity planning for GPU and CPU workloads.</li><li>Strong grasp of model serving, inference optimization, and observability tooling.</li></ul>Required certification:<ul><li>Microsoft Certified: DevOps Engineer Expert (AZ-400)</li></ul>Preferred certifications:<ul><li>Microsoft Certified: Azure Administrator (AZ-104) or Solutions Architect (AZ-305)</li><li>CKA or CKAD (Kubernetes)</li></ul>Location: Abu Dhabi, UAEEmployment Type: Permanent, Full-timeExperience: 8&ndash;10 yearsSalary Range: 25,000 - 33,000 (AED per month)Pay: AED25,000.00 - AED33,000.00 per monthWork Location: In person

AI/ML/DevOps Engineer

EverFi

<div>Everfi is a leading education technology company founded in 2008 that delivers digital learning solutions focused on real-world skills. The company provides scalable education in areas such as financial literacy, health and wellness, and workplace readiness.
We are seeking a Cloud Architecture Engineer, Senior Principal to support the reliability, scalability, security, and strategic evolution of EVERFI's PaaS systems, while acting as a force multiplier for the broader engineering organization. The Cloud Architecture Engineer, Senior Principal is expected to operate with a high degree of autonomy, make consequential architectural decisions, and represent cloud infrastructure to senior leadership as needed. 
Cloud Architecture Engineer, Senior Principal Compensation and Benefits
$170,000-$185,000 annual base salary depending on experience and education. Everfi may pay more or less based on employee qualifications, market value, Company finances, and other operational considerations.
This role is eligible to participate in the Corporate Bonus Plan
100% Remote position
Health, Dental, and Vision insurance
401(K) with matching contribution
Generous Paid Time Off (PTO) 
Cloud Architecture Engineer, Senior Principal Responsibilities
Strategic Architecture &amp; Technical Vision<ul><li>
Shape and execute the multi-year cloud architecture strategy for EVERFI's platform, aligning infrastructure direction with business growth, product roadmap, and organizational scalability goals</li></ul><ul><li>
Lead enterprise-wide architecture reviews and establish cloud governance standards, guardrails, and best practices adopted across all engineering teams</li></ul><ul><li>
Identify and evaluate emerging technologies (e.g., AI/ML infrastructure, FinOps, platform engineering tooling) and make forward-looking recommendations to VP and CTO leadership</li></ul><ul><li>
Serve as a technical decision-maker and escalation point for complex, cross-functional cloud architecture challenges</li></ul><ul><li>
Drive the evolution of EVERFI's platform from reactive infrastructure management to proactive, resilience-first platform engineering</li></ul>
Platform Engineering &amp; Infrastructure<ul><li>
Design, build, maintain, and monitor internal PaaS systems in the cloud at enterprise scale &mdash; with a focus on high availability, fault tolerance, and cost efficiency</li></ul><ul><li>
Lead the implementation of geographically redundant, multi-region, and highly available architectures capable of supporting EVERFI's growth trajectory</li></ul><ul><li>
Architect and oversee the full lifecycle of cloud deployment tooling, ensuring CI/CD systems are continuously optimized for speed, safety, and developer experience</li></ul><ul><li>
Design reliable, interoperable components and utility libraries that underpin EVERFI's applications across engineering teams</li></ul><ul><li>
Architect and own a comprehensive metrics, monitoring, and observability system enabling full-stack visibility, proactive incident response, and SLA enforcement</li></ul>
Security, Compliance &amp; Risk<ul><li>
Ensure all cloud environments are designed and administered in accordance with company security guidelines, SOC 2 compliance requirements, FERPA, and applicable data privacy regulations</li></ul><ul><li>
Architect zero-trust networking, identity and access management (IAM), and data encryption frameworks across EVERFI's cloud environments</li></ul><ul><li>
Partner with Security and Legal teams to lead cloud risk assessments and drive remediation of architectural vulnerabilities at the platform level</li></ul>
Cross-Functional Leadership &amp; Influence<ul><li>
Act as a senior technical advisor to Engineering, Product, and Executive leadership on all cloud infrastructure decisions &mdash; translating complex technical tradeoffs into clear business impact</li></ul><ul><li>
Champion engineering culture: establish and promote best practices for reliability, performance, and operational excellence across all teams consuming cloud infrastructure</li></ul><ul><li>
Build training programs, playbooks, and knowledge resources that upskill engineering teams on cloud operations, architecture patterns, and performance optimization</li></ul><ul><li>
Represent the Cloud Architecture function in cross-functional planning, capacity modeling, and strategic workforce design discussions</li></ul>
Mentorship &amp; Talent Development<ul><li>
Provide mentorship, technical guidance, and career development support to Principal, Staff, and Senior Engineers on the Cloud Architecture team and adjacent teams</li></ul><ul><li>
Participate in hiring, technical interviews, and calibration discussions as needed</li></ul><ul><li>
Participate in an on-call rotation to provide emergency incident support as needed, modeling expected standards of operational excellence for the team</li></ul> 
Cloud Architecture Engineer, Senior Principal Qualifications<ul><li>
Bachelor's Degree in Computer Science, Engineering, or equivalent combination of education and experience required; Master's degree strongly preferred</li></ul><ul><li>
10+ years of progressive professional experience in cloud infrastructure, platform engineering, or systems architecture</li></ul><ul><li>
Minimum 3&ndash;5 years of experience operating at the Principal or Staff Engineer level, with demonstrated ownership of enterprise-wide architectural decisions</li></ul><ul><li>
Proven track record of leading large-scale cloud transformations, platform modernizations, or migrations in high-growth SaaS environments</li></ul><ul><li>
Experience in EdTech, FinTech, or compliance-heavy industries strongly preferred</li></ul>
Certifications (Preferred)<ul><li>
AWS Solutions Architect &ndash; Professional (or equivalent Azure/GCP professional-level certification)</li></ul><ul><li>
AWS Security Specialty or Certified Cloud Security Professional (CCSP)</li></ul><ul><li>
Kubernetes Administrator (CKA) or equivalent</li></ul>
Technical Skills<ul><li>
Cloud Platforms: Deep expertise in AWS (required); hands-on experience with Azure and/or GCP preferred</li></ul><ul><li>
Infrastructure as Code: Terraform, AWS CloudFormation, Pulumi, or CDK at enterprise scale</li></ul><ul><li>
Containerization &amp; Orchestration: Docker, Kubernetes (EKS/AKS/GKE), Kafka</li></ul><ul><li>
CI/CD &amp; DevOps: Advanced pipeline design with Jenkins, GitHub Actions, ArgoCD, or equivalent</li></ul><ul><li>
Networking &amp; Security: TCP/IP, DNS, SMTP, HTTP, VPCs, zero-trust architecture, WAF, distributed networks</li></ul><ul><li>
Programming &amp; Scripting: Python, Go, Ruby on Rails, or Bash (proficiency in at least two)</li></ul><ul><li>
Data &amp; Storage: SQL and NoSQL (Postgres and equivalents); familiarity with data lake and lakehouse architectures</li></ul><ul><li>
Observability: Datadog, New Relic, Prometheus/Grafana, or equivalent full-stack observability platforms</li></ul><ul><li>
AI/ML Infrastructure: Familiarity with cloud-native AI/ML infrastructure (SageMaker, Vertex AI, or equivalent) preferred</li></ul><ul><li>
Open-Source Ecosystem: Extensive experience contributing to and consuming open-source tooling in production environments</li></ul><ul><li>
Web Services &amp; APIs: Expert-level knowledge of REST, RPC, SOA, and API design principles</li></ul></div>

Cloud Architecture Engineer, Senior Principal

Orange Business

<div>
 
 About Us
 
 
 
 Join us at Orange Business!
 
 
 We are a network and digital integrator that understands the entire value chain of the digital world, freeing our customers to focus on the strategic initiatives that shape their business.
 
 
 Every day, you will collaborate with a team dedicated to providing consistent, sustainable global solutions, no matter where our customers operate. With over 30,000 employees across Asia, the Americas, Africa, and Europe, we offer a dynamic environment to develop and perfect your skills in a field filled with exciting challenges and opportunities.
 
 
 
 About The Role
 
 
 
 <ul>
 <li>
 Your day-to-day missions
 </li>
 <li>
 You contribute to the design, deployment and operation of AI platforms, ensuring reliability, scalability and security in production environments.
 </li>
 <li>
 You work closely with data scientists, data engineers and infrastructure teams to industrialize AI use cases on cloud and hybrid platforms.
 </li>
 <li>
 You implement and maintain the tooling and pipelines required for model training, evaluation, deployment and monitoring (MLOps).
 </li>
 <li>
 You help automate and standardize platform services (templates, CI/CD, infrastructure as code) to accelerate delivery while keeping quality high.
 </li>
 <li>
 You participate in incident analysis and continuous improvement of the AI platform, contributing to a strong reliability and performance culture.
 </li>
 <li>
 Occasional missions and example projects
 </li>
 <li>
 You may contribute to the rollout of new AI platform features (for example, GPU-based training environments, feature stores or model registries).
 </li>
 <li>
 You can be involved in migration projects to new cloud services or new AI frameworks, in collaboration with architecture and security teams.
 </li>
 <li>
 You may participate in internal communities of practice, tech talks or proof-of-concept projects around emerging AI technologies.
 </li>
 <li>
 Skills you will develop This position offers you the opportunity to deepen your expertise in AI platform engineering, from build to run. You will strengthen your skills in cloud environments, containerization, MLOps and observability, while gaining experience on real-life, large-scale AI use cases. You will also develop your ability to collaborate with cross-functional teams, translate data science needs into robust platform services, and grow your autonomy and technical leadership in an international and agile environment.
 </li>
 <li>
 Benefits of the role You will work at the heart of Orange Business&rsquo; AI platforms, contributing directly to projects that matter for our customers and internal stakeholders. You will evolve in a modern, cloud-centric environment, with access to cutting-edge AI and platform technologies. You will benefit from a flexible working environment and a culture that values continuous learning, knowledge sharing and innovation.
 </li>
 <li>
 Career perspectives In the medium term, this role can open up opportunities towards more senior positions such as Senior AI Platform Engineer, MLOps Lead or Platform Tech Lead. You will also be able to move towards roles focused on architecture or technical leadership on AI and data platforms, depending on your aspirations and strengths.
 </li>
 <li>
 The team You will join an international team combining diverse expertise in data, AI, cloud and platform engineering. You will work on visible and impactful projects, in an environment that encourages collaboration, technical excellence and mutual support. You will be surrounded by colleagues who are keen to share knowledge and help you grow.
 
 
 </li>
 </ul>
 
 About You
 
 
 
 <ul>
 <li>
 Experience and education |You have between 3 and 5 years of professional experience in a relevant technical role (for example: platform engineer, DevOps engineer, data/ML engineer, software engineer) and hold at least a Bachelor&rsquo;s or Master&rsquo;s degree (or equivalent) in computer science, engineering or a related field.
 </li>
 <li>
 Your hard skills
 </li>
 <li>
 Good knowledge of cloud environments (AWS, Azure or GCP) and their managed services for data and AI.
 </li>
 <li>
 Solid experience with containers and orchestration (Docker, Kubernetes) in production contexts.
 </li>
 <li>
 Hands-on experience with CI/CD and DevOps practices (Git, pipelines, infrastructure as code such as Terraform/Ansible, monitoring/logging tools).
 </li>
 <li>
 Familiarity with AI and ML concepts and tools (for example Python-based ML stacks, model serving frameworks, MLOps tools) and a strong motivation to grow further in this area.
 </li>
 <li>
 Understanding of security, reliability and performance considerations for production platforms.
 </li>
 <li>
 Your soft skills You are a team player with good communication skills, able to collaborate smoothly with data scientists, engineers and operations teams. You show rigor, curiosity and a strong willingness to learn, especially in a fast-evolving AI and cloud ecosystem. You are comfortable taking ownership of problems, proposing solutions and iterating in an agile way. Your mindset combines pragmatism and a desire for quality, allowing you to deliver reliable services while continuously improving them.
 
 
 </li>
 </ul>
 You bring passion, energy, taste for exploration and adaptability. You seek the opportunity to expand your knowledge and develop new skills.
 
 
 
 What We Offer
 
 
 
 <ul>
 <li>
 Global Opportunities: Work in multi-national teams with opportunity to collaborate with colleagues and customers from all over the world.
 </li>
 <li>
 Flexible Work Environment: Flexible working hours and possibility to combine work from office and home (hybrid ways of working).
 </li>
 <li>
 Professional Development: training programs and upskilling/re-skilling opportunities.
 </li>
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 Career Growth: Internal growth and mobility opportunities within Orange.
 </li>
 <li>
 Caring and Daring Culture: Health and well-being programs and benefits, diversity &amp; inclusion initiatives, CSR and employee connect events.
 </li>
 <li>
 Reward Programs: Employee Referral Program, Change Maker Awards.
 
 
 </li>
 </ul>
 
 Only Your Skills Matter
 
 
 
 Regardless of your age, gender identity, race, ethnic origin, religion/belief, sexual orientation, marital status, neurotype, disability, veteran status or appearance, we encourage diversity within our teams because it is a strength for the collective and a vector of innovation. Orange Group is a disabled-friendly company and equal opportunity employer: don't hesitate to tell us about your specific needs.
</div>

AI Platform Engineer

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8301 ml platform engineer jobs Near Me

AI Architect - Riyadh,KSA

AI Architect - Riyadh,KSA

OCI AI Services Engineer

AI Research Engineer

AI/ML/DevOps Engineer

Cloud Architecture Engineer, Senior Principal

AI Platform Engineer