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Senior Data Scientist builds and deploys AI models—including LLMs and computer vision—to optimize oil production workflows using Python, PyTorch, and cloud GPUs.
Senior back-end engineer building scalable RegTech and compliance automation using Python/Django, ElasticSearch, and AI-driven tools to streamline maritime trade counterparty onboarding and risk assessment.
Internship in AI/ML and quantum computing with a path to full-time work; build models in Python and libraries like TensorFlow/PyTorch.
Design and build ML models for agricultural technology products, collaborating with data scientists and engineers to deploy solutions.
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 and deploy ML models for financial forecasting, risk analysis, and strategic decision-making using Python, time-series techniques, and cloud platforms.
Build and deploy ML models for translation and language tasks using Python, TensorFlow, and scikit-learn in a product-focused team.
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 production-grade ML models and RAG pipelines to replace rule-based systems, focusing on model quality, evaluation, and self-hosted LLM inference.
Build, optimize, and deploy AI/ML models (including LLMs) using Python, TensorFlow/PyTorch, and cloud platforms in a product-focused team.
Senior AI Engineer designs and deploys production-ready ML/LLM models, builds data pipelines, and mentors junior engineers for Devsinc’s client projects.
Builds scalable data pipelines and AI/ML models in Python/SQL, deploys them via MLOps, and maintains cloud-based data infrastructure for intelligent applications.
Build and optimize Python-based speech-to-text models using frameworks like Whisper or Wav2Vec2, deploy them via APIs/Docker, and integrate into real-time applications.
Build backend services integrating AI APIs and trading systems using Python, FastAPI, and SQL.
Build and deploy AI-powered Python applications, REST APIs, and ML pipelines using TensorFlow/PyTorch, Docker, and cloud AI services.
Build and optimize Python-based speech-to-text models using frameworks like Whisper or Wav2Vec2, deploy them via APIs, and integrate into products.
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