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Essential Functions: Lead the deployment, integration, and operational support of AI platforms, tools, and services, ensuring compatibility with existing systems and enterprise processes. Design, implement, monitor,…
We are seeking a talented Senior Advanced Software Engineer to support our MLOps, LLM and agentic AI integration, Databricks administration, data lake management, and cloud platform initiatives. The ideal candidate…
You will be part of an energetic A.I./Machine Learning cross-functional team, collaborating with various business/product partners (e.g. Credit, Fraud, Risk, Web, Mobile, Marketing, Enterprise Automation, etc.) to…
ML mühəndisi Vakansiya haqqında Şirkət: Azerconnect Group Funksiya: Adtech İş qrafiki: Həftənin 5 günü saat 09:00-dan 18:00-dək. Son müraciət tarixi: 30.10.2026 Azerconnect Group NEQSOL Holding beynəlxalq şirkətlər…
We are seeking an experienced ModelOps Lead to drive enterprise-scale AI, Generative AI, and ModelOps initiatives across Machine Learning and LLM platforms. The ideal candidate will have 7+ years strong hands-on…
RELOCATION ASSISTANCE: Relocation assistance may be available CLEARANCE REQUIRED FOR START: Yes CLEARANCE TYPE: Top Secret TRAVEL: Yes, 10% of the Time Description At Northrop Grumman, our employees have incredible…
Data Engineer on Generali Italia's Data Technologies, Analytics & BI team, designing cloud-native data pipelines, lakehouse ingestion, and backend data services that power analytics, AI/ML, and GenAI products. Daily work centers on Python/SQL/Scala, Spark/PySpark, cloud platforms (AWS/Azure/GCP), and MLOps practices alongside data scientists and SREs.
Build and operate ML/LLM platforms for a Korean neobank, focusing on stable, scalable, and secure model training, deployment, and serving using tools like MLflow, Kubeflow, Triton, and vLLM.
Intermediate software engineer at Kriterion in Pretoria building full-stack features for Cerberus, a cloud-native predictive maintenance platform that turns AI insights on sensor-rich machinery into dynamic user interactions. Stack includes React/TypeScript on the frontend and Python/FastAPI/Firestore with Apache Beam, TensorFlow (TFX) and Kubeflow for AI/data workflows.
An AI Engineer who designs, develops, and deploys machine learning models for production — building training/evaluation pipelines, monitoring model performance, and integrating AI into applications alongside data scientists and product teams. Core stack is Python with TensorFlow/PyTorch/scikit-learn, cloud platforms, and ML Ops tooling.
Engineer on HTX's xCloud team building the AI platform for Singapore's public safety agency: designing ML infrastructure (Kubeflow, MLflow, RunAI), automating CI/CD and ML pipelines with DevSecOps practices, and writing infrastructure-as-code on-site in Singapore.
DevOps/Platform engineer at Kaltura who designs, builds, and operates distributed AI production systems at high scale on AWS and GCP — owning projects end-to-end from design to production, including GPU inference infrastructure, Kubernetes/Docker/Helm, CI/CD, and observability, working with Platform, AI Labs, and AI/ML researchers.
Data engineer at a Leeds-based data consultancy, deployed onto varied client projects to deliver data-focused solutions. Day-to-day work centres on SQL, Python, BigQuery, data warehousing and Docker across a cloud-agnostic, mainly Azure stack (AWS/GCP also used), with optional ML and marketing-API work.
Senior, largely self-directed AI engineer in Bangalore building and scaling Amtech's agentic AI platform: MCP-native LLM orchestration, RAG pipelines, and a governed Data Agent over customer data, deployed on AWS and reused across Amtech's enterprise software products for the packaging and manufacturing industries.
Builds and operates cloud infrastructure and MLOps pipelines for AI/ML solutions at DXC Technology: Terraform IaC, CI/CD for model deployment, Docker/Kubernetes, monitoring and DevSecOps, while supporting data scientists and keeping production AI systems reliable, scalable, and cost-efficient.
Architects and operates the cloud, big-data, and ML platform for Inceptio's overseas autonomous-driving program in Singapore, building petabyte-scale ingestion and pipelines for camera/LiDAR/radar fleet data plus MLOps (GPU training, orchestration, CI/CD). Core stack: AWS/GCP/Azure, Spark/Flink/Kafka, Kubernetes, Terraform, Python and Go/Java/Scala.
Senior Data Engineer joining Tripledot Studios' central AI team in London to build a game event data hub that ingests and monitors data from multiple mobile-game studios. Day-to-day work centers on data ingestion, quality checks, backfills and orchestration using Kubernetes, Airflow, SQL and Spark, with later rotation into productionizing ML pipelines. Hybrid, 3 office days per week.
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