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Designs and maintains data pipelines and integrations for AI, analytics, and automation using Databricks and Microsoft Fabric, ensuring data reliability and governance for marine geodata solutions.
Build and deploy ML/LLM solutions end-to-end for diverse clients, from data prep to production APIs, while collaborating in a team of ML engineers.
Hands-on AI/ML analyst building and testing data science, machine learning, and GenAI solution components for a large U.S. bank's India GCC, using Python, SQL, and LLM/RAG techniques.
Lead Data Scientist designing and deploying ML, NLP, and GenAI models (including RAG systems) using Python, cloud platforms (Azure preferred), and frameworks like TensorFlow, PyTorch, and LangChain for an executive search firm's Digital-IT team.
The Generative AI Engineer will design, develop, and deploy scalable AI solutions using LLMs and transformer architectures. The role involves orchestrating model workflows, integrating GenAI into enterprise systems, and collaborating with MLOps teams on cloud platforms.
Develops AI/ML models and advanced analytics for DoD mission support, ensuring secure deployment and compliance with federal standards while collaborating with cross-functional teams.
Designs, builds, and deploys enterprise-grade ML models and data science solutions to solve complex business problems using Python, SQL, and cloud platforms.
Build and deploy AI/ML models and analytics tools to optimize Caterpillar’s remanufacturing operations using Python, Snowflake, and Power BI.
Build and productionize ML models for semiconductor manufacturing yield/quality, develop agentic AI and RAG-based LLM solutions, and create analytical pipelines using Python and SQL in a high-volume fab environment.
Build and deploy scalable ML and GenAI solutions at Amgen, turning prototypes into production-ready services using Python, cloud platforms, MLOps and containerization.
Data Scientist II building ML, NLP, and generative AI systems for clinical and scientific knowledge discovery and evidence extraction at Elsevier, using Python, LLMs, and standard ML/data science libraries.
Develops and deploys AI-powered legal tools by designing experiments, evaluating LLM/ML models, and prototyping agentic systems for legal research, drafting, and decision-making.
Data Analyst co-op student analyzing data, building pipelines, and developing ML models for RBC's Personal Banking team using SQL, Python, R, Tableau, and Power BI.
Develops and deploys advanced statistical models and machine learning solutions to solve HR-related business challenges for SMB clients, mentors team members, and collaborates with cross-functional teams to drive data-driven decisions.
Leads AI/ML model development and MLOps for predictive, prescriptive, and generative solutions while managing client engagements and program governance.
Hands-on Staff Data Engineer (50%+ coding) at Early Warning (Zelle), architecting and building scalable data platforms, lakehouses, and ML pipelines using Snowflake, Databricks, Python/PySpark on AWS.
Senior Data Scientist leading AI/ML and physics-based model development for a DTRA/DIA national security contract, using Python/R in classified JWICS environments to characterize hardened facilities and WMD processes.
Builds and owns data pipelines, models, and AI infrastructure for clinical research data across 80+ sites, ensuring quality, observability, and integration with ML workflows.
Build and deploy AI/ML models and GenAI features for federal applications, integrating them into production systems and collaborating with cross-functional teams.
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