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The Applications Development Intermediate Programmer Analyst is an intermediate level position responsible for participation in the establishment and implementation of new or revised application systems and programs in…
OneMagnify is an AI native, platform-enabled B2B digital agency operating at the intersection of data, technology, and creativity. We help complex organizations drive measurable business outcomes by building smarter…
Job Title: Cloud Data Scientist- SOCEUR Job Category: Science Time Type: Full time Minimum Clearance Required to Start: TS/SCI Employee Type: Regular-Long Term Assignment Percentage of Travel Required: Up to 10% Type…
Designs and deploys scalable AI/ML solutions for manufacturing operations, collaborating with cross-functional teams to integrate models, pipelines, and governance in cloud and on-prem environments.
Leads Inter's Decision Modelling team (Brazil's first digital bank) building and maintaining credit and collections models — approval/recovery scores, limit optimization, income estimators. Day to day: technical leadership, model governance and production monitoring, MLOps, and stakeholder alignment using Python, SQL, scikit-learn, MLflow/Airflow and cloud platforms.
A senior engineer who designs and runs large-scale distributed production systems powering Xero's AI features for millions of users, owning architecture, tech debt, and mentoring. Core stack is Python, SQL, Spark/Dask, AWS, and Kubernetes, with a focus on productionizing ML and LLM features alongside Applied Scientists.
Build scalable, fault-tolerant systems and APIs for core business logic like inventory and payments using Kotlin, Scala, and data technologies like Kafka and Spark.
Data engineer at consultancy PALO IT, embedded with a leading insurance client, building cloud data pipelines and lakehouse platforms (Azure, Spark, dbt, Kafka, Airflow, Snowflake) with data quality and governance. The role is explicitly AI-native: daily use of GenAI coding tools like Copilot and Cursor.
Senior Data Scientist on Asaas's Data & AI team, building and productionizing machine learning models for transactional financial fraud prevention, with a strong MLOps focus: real-time and batch model serving, monitoring, and scaling to high transaction volumes using Python, SQL, Spark, MLflow, and Databricks on AWS.
Mid-level Data Scientist on Asaas's Data & AI team, building and evolving the company's credit risk predictive intelligence end-to-end — from problem definition with Product/Ops to production deployment, monitoring (data/concept drift), and AI agents. Core stack: Python, SQL, Spark, machine learning/statistics, with remote work across Brazil.
Senior AI architect designs, documents, and governs enterprise AI/ML/GenAI standards, frameworks, and scalable solutions for a major Latin American bank, ensuring security, compliance, and alignment with business needs.
Leads DevOps capabilities for enterprise analytics, data, AI, and ML platforms at a biopharma company: building CI/CD pipelines, managing AWS cloud and Kubernetes infrastructure, implementing observability, and ensuring security and compliance in regulated environments, while combining technical leadership with team management.
MLOps-style engineer at Camtek (semiconductor inspection) in Migdal HaEmek who turns research ML models into optimized, production-ready components: integrating models, optimizing inference (TensorRT/ONNX, GPU), and building deployment/monitoring infrastructure using Python, PyTorch, and C++/C#.
Staff-level Platform Architect owning AI/ML infrastructure on Google Cloud: building model/inference serving on GKE, Terraform-based IaC, ArgoCD GitOps, ML pipelines, observability/SLOs, and cost efficiency for LLM and agentic workloads. Remote in LATAM (Brazil preferred), EST working hours, paid in USD.
Syngenta's R&D Digital data science team is hiring a Machine Learning Engineer to build and deploy production-grade computer vision and ML solutions that turn drone, satellite, and sensor imagery into digital traits for seed breeding. Day-to-day work spans the full ML lifecycle — model development, cloud data pipelines, MLOps, and monitoring — using Python, PyTorch/TensorFlow, Docker, and AWS/GCP/
Remote Senior Lead AI Engineer (hired via OutForce, a Philippines-based outsourcing firm, working US hours) serving a US engineering/consulting client. Leads end-to-end delivery of enterprise AI/ML — mentoring engineers, owning LLM/RAG architecture, and staying hands-on with Python, PyTorch/TensorFlow, cloud platforms, and MLOps.
Senior AI Engineer in EY Ireland's AI Lab in Dublin, building LLM-driven and multi-agent solutions for global clients. Day to day involves developing generative AI/RAG pipelines and agentic systems with Python, Azure OpenAI, LangChain/LangGraph and Hugging Face, deployed on cloud with MLOps tooling.
Senior Consultant Data Engineer in EY's Financial Services Technology Consulting (AI & Data) team in Dublin, designing, building and operating scalable data pipelines and ETL solutions for banking, insurance and wealth/asset management clients. Core stack is Azure data services, Snowflake, Databricks, SQL and Python.
Own ML end-to-end for a proprietary trading platform: turn loosely framed business problems into models in a high-load, low-latency environment — from feature engineering and hypothesis testing to evaluation and business-ready results. Core stack: Python (NumPy, SciPy, Pandas, Scikit-learn), PySpark/MLlib, XGBoost/GBM, survival analysis, and MLflow.
Senior Data Scientist / ML Engineer at OVENTI, a Data & AI consulting firm in Paris: design, train and deploy ML models (notably on risk/finance topics) end-to-end — from data exploration in Snowflake to industrial deployment on Azure — with rigorous MLOps practices. Core stack: Python, Scikit-Learn/XGBoost, Azure, Snowflake, GitLab CI/CD, MLflow.
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