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Tasks Role purpose Lead AI Engineer responsible for taking AI and Generative AI solution designs from architecture into working, production-ready software. The role leads technical implementation, guides developers,…
What You would do at KPMG: collaborating on the design and development of ML‑based applications and their backend components helping to select the most applicable solutions for a given business problem writing clean,…
Design, development, and optimization of core ML models, especially in Computer Vision and Deep Learning Development of efficient, scalable training and inference pipelines Mentoring junior ML engineers, reviewing code…
Architect and lead the development of large-scale ML systems and model pipelines Introduce new ML systems such as traffic sign detection, building facade detection, and other computer vision-based solutions Define and…
Principal Data Scientist leading the technical direction and delivery of analytical products supporting Corporate and One Supply functions at Grupo Modelo (AB-InBev), using Python, SQL, machine learning, optimization, and statistical modeling.
About Themis Themis is a collaborative governance, risk, and compliance platform helping banks, credit unions, and fintechs streamline oversight, strengthen compliance programs, and move faster with confidence. Our…
The AI Solution Architect will design and lead the implementation of scalable, secure enterprise AI/ML architectures on Microsoft Azure. The role involves managing RAG architectures, MLOps pipelines, and coordinating interdisciplinary teams to deliver innovative AI solutions for the public sector.
The Data Engineering Lead will design and govern the data architecture for AI and machine learning initiatives, focusing on building production-ready pipelines between AWS and Azure. This hands-on leadership role involves managing engineering resources to support data science teams while ensuring compliance with security and governance standards.
The Senior Backend & AI Engineer will build scalable microservices and integrate AI capabilities, including LLM orchestration, RAG, and fine-tuning, into newsroom platforms. The role requires expertise in Node.js, TypeScript, and LangChain to develop AI-powered solutions within a distributed, asynchronous global team.
This role involves building and maintaining data pipelines and production-grade applied AI components for a building decarbonization SaaS platform. The engineer will focus on data ingestion, modeling, and scaling AI features while ensuring data quality and observability.
The Lead Full Stack Developer will lead a team in building and architecting secure digital banking platforms using Angular, Node.js, and AWS serverless technologies. The role involves integrating Generative AI and LLM capabilities into enterprise workflows while ensuring compliance with financial regulations.
The Senior Data Engineer will design scalable data solutions in Snowflake, build robust data models, and lead complex pipelines from ingestion to presentation. The role involves modernizing data platforms, migrating legacy workloads, and focusing on data governance and MLOps.
The Data Infrastructure & MLOps Engineer will design, build, and operate platforms to support data engineering, analytics, and machine learning workflows. The role involves collaborating with cross-functional teams to improve data accessibility and streamline model deployment using Python, SQL, and cloud infrastructure.
This role involves developing machine learning models and managing MLOps pipelines for production deployment. The position requires experience with Spark, SQL, and FastAPI to facilitate rapid iteration between experimentation and deployment.
Design and operate end-to-end data and ML pipelines at Insud Pharma's AI Labs, collaborating with data scientists and developers to ship models to production using Python, Docker, Git, and MLOps practices.
Builds the data flywheel platform and foundation-model infrastructure at Wayve, focusing on data curation pipelines, model evaluation/training systems, and distributed data processing using Python, Ray, Spark, and lakehouse technologies.
This role involves leading a data engineering team to design and optimize Spark on AWS EMR pipelines for batch and streaming data. The position requires hands-on technical leadership, MLOps support, and the ability to build service components using React and Node.js.
This entry-level AI Engineer role involves training and deploying deep learning models for industrial robotics applications. The position requires hands-on experience with Python, PyTorch, and Docker to improve model performance and support edge deployments.
Senior DevOps Engineer specialized in AWS, responsible for designing scalable cloud environments, migrating workloads across AWS accounts, and building CI/CD pipelines and infrastructure automation using Terraform, CloudFormation, and container services like ECS/EKS.
The Machine Learning Engineer will build data pipelines and MLOps infrastructure to support the deployment and maintenance of AI models for an insurance group. The role involves collaborating with data scientists to transition experimental models into production-ready solutions using cloud technologies.
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