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The Senior ML Engineer will design and operate production-grade AI and LLM systems for equity research, working within a hybrid team at CNBC to build scalable financial data products. The role involves end-to-end ownership of ML pipelines, model training, and inference infrastructure.
Designs and leads AI/ML solutions for an energy client using Microsoft AI Foundry, Azure AI, and Databricks, translating business needs into scalable, secure architectures and guiding implementation from data to deployment.
The Data Engineer will design, develop, and maintain Snowflake data pipelines and AI/ML solutions while collaborating with cross-functional teams. The role involves optimizing data models, ensuring data integrity, and managing migrations from on-premise systems to the cloud.
Job Description: The successful candidate will join a specialised team focused on developing machine learning and AI-driven capabilities that deliver valuable insights from large-scale, real-time distributed systems…
Research-focused role at an AI startup (Abundant) designing next-gen model reasoning/data strategies; bridges frontier AI research and production systems for AGI/ASI applications.
The C-BRAIN Data Engineer role at Washington University in St. Louis involves managing and processing data for research initiatives. This is a remote position based in the United States.
The Senior Data Engineer will design and maintain scalable data ingestion and AI-driven extraction pipelines using Python, Spark, and AWS. This role involves collaborating with data scientists to integrate LLMs and AI agents into production systems for retail and field operations data.
Build and maintain AI/ML pipelines and data infrastructure for Roamler’s OOH Location Database and product suite, enabling ML/NLP enrichment and embeddings for European brands.
Working with Us Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens…
Builds and deploys GenAI and agentic AI systems for pharma clients, integrating RAG pipelines, multi-agent frameworks, and medallion data architectures across Microsoft, OpenAI, and AWS ecosystems.
Lead Software Engineer on the Corporate Technology-Digital Workflows team at JPMorgan Chase, building and maintaining secure, scalable data pipelines and architectures on AWS using Python, Spark, and Terraform.
The Associate Data Scientist will build AI-powered solutions, including LLM-based agents and recommendation systems, to improve sales and marketing productivity at Gartner. The role involves prototyping, model development, and collaborating with cross-functional teams to drive business outcomes.
To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Operations Job Details About Salesforce Salesforce is the…
Builds and deploys AI models for pricing, search, and payment optimization at a global fintech firm using Python/C++ and advanced ML techniques.
Build and deploy AI solutions using NLP, LLMs, and knowledge graphs for financial workplace investing products, focusing on document processing, assistants, and anomaly detection.
Researches, designs, and implements statistical, ML, and econometric models for market risk metrics like VaR and stress tests, using C++ and Python, and collaborates with engineering and product teams to deploy solutions for Bloomberg’s financial data platforms.
Build and deploy generative AI solutions using LLMs, RAG, and agentic workflows for legal-tech products, contributing directly to production code.
Provide tier-2/3 support for Citi’s global financial applications, troubleshoot middleware and cloud issues, and apply SRE practices to improve system reliability and performance.
Designs and builds enterprise-grade agentic AI systems using Java microservices, cloud-native architecture, and frameworks like LangChain/Autogen to create autonomous agents, RAG pipelines, and LLM-based solutions for clients in advisory services.
Lead a data science team to build predictive models and insights for media brands, focusing on customer lifetime value, engagement, and personalization across apps and newsletters using Python, SQL, and ML.
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