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Design and deploy machine-learning models to power business innovation, using Python and frameworks like TensorFlow or PyTorch.
Build, test, and deploy AI/ML models; preprocess data and help fine-tune models for Translation Empire’s AI-driven applications.
Build and deploy production-grade AI/ML models using Python, TensorFlow, PyTorch, and MLOps tooling for scalable, real-world applications.
Build Python/C++ frameworks and APIs to run Vision and Generative AI models efficiently on custom AI accelerators, profiling and optimizing performance-critical code.
Develop and implement deep learning algorithms for AI projects using Python, TensorFlow, and Keras, with a focus on computer vision and NLP.
Design and build ML models, optimize them for performance, and collaborate with data scientists and engineers to solve business problems using Python or R.
Build and deploy generative AI chatbots, predictive models, and analytics dashboards using Python, LLMs, and tools like Streamlit and Power BI.
Build and deploy ML models for translation and language tasks using Python, TensorFlow, and scikit-learn in a product-focused team.
Build and deploy ML models to drive data-driven decisions, collaborating with a data science team using Python/R and frameworks like TensorFlow.
Builds and tests AI/ML models, preprocesses data, and helps deploy AI-driven features using Python and libraries like scikit-learn.
Build and deploy AI systems including LLMs, computer vision, and autonomous agents using Python, PyTorch, and LangChain, then productionize them with MLOps on cloud platforms.
Build and scale AI agents and ML pipelines using Python, PyTorch/TensorFlow, and frameworks like LangChain; integrate LLMs, vector DBs, and cloud-native systems.
Build and maintain AI-driven test automation frameworks for mobile apps, using ML to predict defects and self-heal scripts while integrating with CI/CD pipelines.
Build and deploy LLM/NLP models using Hugging Face, LangChain, and cloud AI services; implement RAG pipelines and vector search for AI-driven chatbots and Q&A systems.
Design and deploy AI/ML models, including LLMs and GenAI, to solve healthcare data challenges using Python, cloud platforms, and MLOps.
Build and optimize AI/ML models using Python, TensorFlow, and PyTorch, focusing on RAG, LangChain, and locally run AI with Ollama for production deployment.
Designs and integrates AI/ML solutions into a data lakehouse using Spark, Kafka, and Jupyter Enterprise Gateway for batch and real-time inference.
Build, optimize, and deploy AI/ML models (including LLMs) using Python, TensorFlow/PyTorch, and cloud platforms in a product-focused team.
Designs and architects AI/ML solutions integrating batch and real-time inference using Spark, Kafka, and Jupyter Enterprise Gateway within a data lakehouse.
Senior AI Engineer designs and deploys production-ready ML/LLM models, builds data pipelines, and mentors junior engineers for Devsinc’s client projects.
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