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Design, build, and deploy ML/AI solutions (including GenAI) using Python/R, Spark, and Docker/Kubernetes to solve complex business problems and advise clients.
Build AI-powered systems that turn operational data into trusted insights for manufacturing and avionics, using LLMs, RAG, and MLOps pipelines in a secure, Agile environment.
Build and deploy agentic AI systems for dining discovery and reservations using LLMs, RAG, and orchestration tools in a production environment at American Express Global Dining.
Lead the design, development, and deployment of predictive and prescriptive AI/ML models to drive business outcomes like conversion and engagement for a hospitality partnership.
ML Operations Engineer owning production ML/LLM model serving, deployment, and operations in Mercari's cloud-native environment using Kubernetes, Terraform, Python, and NVIDIA/TPU stacks (Triton, TensorRT-LLM, JAX).
The Embedded Software Engineer will develop and optimize high-performance video analytics software for edge devices using C++, Linux, and computer vision frameworks. The role involves integrating deep learning models into real-time video pipelines and optimizing performance for embedded hardware platforms.
Cloud AI/ML Engineer at Evernorth (Cigna Group) in Hyderabad, operationalizing ML models into production-ready batch jobs using Python, PySpark, and AWS within an agile team.
This Machine Learning Engineer role at an AI startup focuses on building and maintaining infrastructure for training, deploying, and scaling AI models. The engineer will develop data pipelines, monitoring frameworks, and optimize systems for performance and reliability.
Cloud AI/ML Engineer operationalizing machine learning models into production batch jobs using Python, PySpark, and AWS within an agile team at a large healthcare services organization.
Senior Data Scientist collaborating with R&D scientists at Qnity Electronics in Cleveland, applying statistical modeling, machine learning, deep learning, computer vision, and generative AI/LLMs to solve scientific and engineering problems in the semiconductor and advanced electronics space.
Build and maintain scalable ML pipelines for training, inference, and analytics in a healthcare platform, using Python, Snowflake, and Azure/AWS while ensuring reliability and observability.
Develops and deploys AI/ML models (predictive and generative) for TD Bank’s Business Banking division, solving problems like agentic AI, LLM applications, pricing, and anomaly detection to drive data-driven decision-making.
Build and standardize ML Ops services, data pipelines, and automation in Python and Java on AWS/Databricks to support model deployment, monitoring, and AI/ML lifecycle governance at a financial services firm.
The Senior Machine Learning Engineer will design, develop, and deploy machine learning and generative AI models into production environments. The role involves building scalable pipelines, fine-tuning LLMs, and collaborating with cross-functional teams to integrate AI solutions using technologies like Python, PyTorch, and Azure.
The Machine Learning & Data Operations Engineer will build and maintain ML/AI infrastructure to support drug discovery, focusing on model deployment, scalable inference, and robust data pipelines. The role involves managing the full lifecycle of models and data quality using technologies like Kubernetes, Python, Go, and various cloud-native tools.
The Machine Learning Engineer will build and deploy scalable ML models for ad targeting, identity resolution, and audience signals within Netflix's ad-supported tier. The role involves working with low-latency real-time systems, big data tools like Spark, and cross-functional teams to optimize advertising performance.
The Senior Data Analyst will lead the design, development, and management of the enterprise data platform, focusing on data integration pipelines using Azure Data Factory and Informatica. The role involves managing cloud data warehouses, driving data modeling strategies, and ensuring data governance and quality standards across the organization.
Architects enterprise-level AI systems and pipelines, focusing on cloud ML tools, MLOps, model deployment, and distributed systems to ensure scalability, security, and cost efficiency.
Develop and deploy machine learning and deep learning models for OCT-based intravascular imaging systems, including semantic segmentation, feature detection, and quantitative analysis, using Python and frameworks like PyTorch/TensorFlow in a regulated medical device environment.
Develop and deploy machine learning and generative AI applications—including LLMs, RAG pipelines, and GenAI services—using Python, PyTorch, Azure, and vector databases in an on-site role at HP.
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