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Build and fine-tune AI models using Python, PyTorch, and Hugging Face; develop NLP and computer vision applications in a startup environment.
AI/ML Engineer building and deploying generative AI, NLP, and computer vision models using Python, PyTorch, Keras, and Hugging Face, with RESTful API development for model integration.
AI/ML Intern building and fine-tuning LLMs and other models using Python, PyTorch, and Hugging Face, with exposure to NLP, computer vision, and API development in Pune, India.
Design and deploy ML systems (CNN, RNN, LSTM), optimize MLOps pipelines, and run distributed training using Spark and Kubernetes in a fully remote, short-term contract role.
Design and deploy advanced ML models (CNNs, RNNs, LSTMs) using Kubernetes and MLOps pipelines; optimize models for scale with distributed training and Apache Spark.
Design, optimize, and deploy deep learning models using Python, PyTorch, and TensorFlow on AWS/GCP in a fully remote, hourly contract role.
Machine Learning Engineer designing, developing, and implementing ML models and optimizing pipelines in a fully remote role using Python, Java, cloud ML services, and frameworks like TensorFlow/PyTorch.
The ML Engineer integrates AI/ML models into production, optimizes inference pipelines, manages CI/CD workflows, and builds Agentic/multimodal AI systems using Python, PyTorch/TensorFlow, Docker, Kubernetes, and cloud platforms.
Machine Learning Engineer implementing ML solutions on a Procure to Pay project in a hybrid Pune setting, writing clean Python/ML code under senior mentorship with a focus on data preprocessing, model building, and team collaboration.
Lead applied AI/ML engineer architecting and delivering autonomous agent systems and generative AI solutions for JPMorgan Chase's Commercial and Investment Banking division, bridging research and enterprise-grade production deployment.
Lead a team of data scientists and AI engineers to build and deploy AI models that accelerate biologic drug development, including LLMs for knowledge retrieval, digital twins for process optimization, and agentic systems for regulatory authoring.
Build low-latency, cloud-native trading systems in Java and integrate AI coding agents to accelerate development and modernize legacy codebases for Goldman Sachs' Global Banking & Markets division.
Builds and maintains AI/ML systems and infrastructure for a large bank, using Python, ML frameworks, and cloud platforms while integrating enterprise-approved AI-assisted development tools.
Hands-on technical leadership role designing, developing, and deploying advanced AI/ML solutions—including LLM applications, RAG, and agentic workflows—for scientific products at a major life sciences company. Core stack: Python, PyTorch, LangChain, LangGraph, Azure OpenAI, and vector search.
Develops statistical models for quantitative trading strategies in equities and commodities, collaborating with business partners to deliver high-performance solutions and outperform competitors using advanced ML techniques.
Hands-on senior AI/ML engineer leading the design, development, and production deployment of LLM, RAG, and agentic AI solutions for life sciences and healthcare applications using Python, PyTorch, LangChain, and Azure OpenAI.
Leads end-to-end AI/ML development for scientific workflows, deploying LLMs, RAG, and agentic systems in healthcare/genomics to improve customer outcomes and innovation.
Machine Learning Engineer building backend components and tooling for scientific LLM agents in Roche's drug discovery team, using Python, FastAPI/Flask, Docker, and CI/CD to connect models to internal scientific capabilities.
The Staff AI/ML Robotics Engineer will develop physics-informed machine learning models and sensor simulation workflows to bridge the gap between simulation and real-world performance for robotics. The role involves collaborating with hardware and AI teams using tools like NVIDIA Isaac Sim, ROS2, and Python/C++ to enhance perception systems.
The Senior Machine Learning Engineer will design, build, and operate production-grade AI systems, specifically RAG applications and Intelligent Document Processing pipelines, for federal clients using AWS GovCloud. The role requires deep expertise in LLMs, vector databases, and secure, compliant software engineering practices.
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