Hire the Best TensorFlow Developers
in the United States

* Expert Vetted talent in Upwork with 100% job success rate. * I am looking for long term work in solving problems with Machine Learning solution. * I have been working on Machine Learning for over 5 years. * My area of expertise in Machine Learning area are: Computer Vision and NLP. * My live projects include: 'Detect Products of Super-market shelves', 'Detect sharp objects from x-ray image', various Image classification models like to classify inside/outside House, Shoes(of different materiel), 'Text classification' of various articles. * I have also worked on stock forecasting LSTM model using stock data and sentiment data. * I have a certification from Udacity in "Self Driving Car Engineer" Nano Degree

I'm a certified Python professional and certified DeepLearning(.)ai Tensorflow Developer. I've completed my Masters in Computer Science. . 1. My skills include: - Data Science and Data Analysis - Machine Learning (KNN, Random Forest, XG Boost, Linear and Logistic Regression, K-means Clustering) - Deep Learning(CNN, ANN, RNN, LSTM) - Model Tuning and Optimisation (GridSearchCV) - Natural Language Processing NLP (Sentiment Analysis, Chatbot Development, Text classification) - Transfer Learning (Xception, Inception, ResNet, VGG16, InceptionResnt, MobileNet) - Object Detection (R-CNN, SSD, YOLO, Faster R-CNN) - Image Segmentation (Mask R-CNN) - Interactive Visualizations and Animations (Matplotlib, Seaborn) - Database Management(MySQL, Sqlite) - Audio Processing(pydub, pyaudio) - Image processing(PIL,Opencv, FFMPEG) - Graphical User Interface GUI (Tkinter, PyQT) - Optical Character RecognitionOCR (Tesseract) - Desktop Application Development and Automation (Pyautogui, PyInstaller) 2. Libraries: - Pandas, Numpy, Scipy, Tkinter, Matplotlib, PyautoGUI, OpenCV, PIL, Sklearn, SQL, Regex, Tesseract 3. Deep Learning Frameworks: - Keras, Tensorflow, PyTorch, Scikit-learn

I am a senior machine learning engineer at an AI real estate startup. I have had the pleasure of working in the machine learning space all 8 years of my professional career. I am passionate about building solutions that provide tangible value to the end customer. I began my AI career as a researcher at MIT Lincoln Laboratory. While at MIT LL, I worked on projects revolving around computer vision, NLP, and graph analytics. After MIT LL, I joined Avitas, GE venture as a computer vision engineer. Avitas flew drones around well pads and captured IR/RGB video and LiDAR data. My role was to develop solutions, mainly deep learning, to input the video/lidar data and facilitate inspection of the well pads. Baker Hughes bought Avitas. Shortly after, I joined FoxyAI as their first full time hire. Currently at FoxyAI, I oversee all AI development. Programming: Python, JavaScript/HTML/CSS, Java, Matlab Machine Learning: PyTorch, TensorFlow, Keras, Scikit-learn, Caffe Computer Vision: OpenCV, Pillow, Image Generation (CLIP, DALLE, Dreambooth), YOLO, Mask-RCNN, LiDAR, 3D Reconstruction, SWIN-Transformer, OCR, UNET Data Science: Numpy, Pandas, Scipy, Matplotlib, Seaborn Misc: various AWS tools, Docker, MongoDB, FastAPI, Django, Flask, Git, Jira, UNIX tools/admin

I am a software engineer specializing in cloud computing, AI/machine learning, and CUDA development. My focus is on building scalable, efficient, and high-performance solutions that optimize workflows and improve system capabilities. I design and deploy cloud applications using Azure, microservices, and serverless architectures. My AI expertise includes Python, TensorFlow, PyTorch, Scikit-learn, and data analysis with NumPy and Pandas. For high-performance computing, I develop and optimize CUDA-based applications, accelerating computationally intensive tasks. With a structured approach to problem-solving, I ensure that every project is efficient, scalable, and aligned with business goals. Whether it's optimizing cloud infrastructure, developing AI models, or enhancing GPU performance, I deliver results-driven solutions. My tech stack includes Azure Functions, Knative, Python, CUDA, Unity (C#), C++ (wxWidgets, MFC), VS Code, Linux, and Git. Let's discuss how I can contribute to your project.

I help businesses turn AI ideas into working systems that support real operations - not just polished demos. I start with a quick discovery call to make sure we are aligned and to confirm the right scope before any work begins. That usually makes the process smoother for both sides. What I build • AI agents and LLM integrations using OpenAI, Claude, LangChain, and RAG pipelines • Workflow automation with n8n, Zapier, Makecom, and custom API bridges • Internal tools and no-code/low-code solutions that reduce manual work • Secure architectures for teams that need reliability in regulated or compliance-sensitive environments What I’ve Delivered • Reduced manual operational workload by 40–70% through AI automation • Built AI workflows processing 10,000+ tasks and requests per month • Cut response and processing times from hours to minutes using automated pipelines • Integrated AI systems with CRMs, internal dashboards, Slack, and third-party APIs • Delivered MVPs and internal AI tools in as little as 2–6 weeks • Helped teams scale workflows without expanding operational headcount How I Work • Async-friendly and easy to work with • Clear scoping before any code is written • I document what I build, so you own it after delivery • I flag scope creep early, not after billing it If you need someone who can connect AI, automation, and internal tools into one practical system, I can help from strategy and architecture through implementation.

I'm a data science freelancer with 4+ years of experience driving results through data analysis, machine learning (ML), and artificial intelligence (AI). My expertise lies in: Unveiling Insights, I leverage strong data analysis, ML, deep learning, and statistical modeling skills to extract meaningful insights from complex datasets, empowering informed decision-making. Building Powerful Solutions: I implement these insights into scalable and efficient solutions using Python, R, and SQL. Focus on Generative Models: I have a particular interest in utilizing large generative models to push the boundaries of AI. Proven Industry Experience: I've collaborated with startups and corporations alike, helping them leverage data to optimize operations, achieve strategic goals, and unlock business value. Beyond the Technical: Self-Starter & Driven: I thrive independently and excel in collaborative environments. Effective Communicator: I bridge the gap between technical expertise and clear communication, ensuring alignment with stakeholders at all levels. Ready to harness the power of data for your success? Let's connect! I am a self-starter and have a strong work ethic. I am able to work independently or as part of a team and I have excellent communication skills, which allow me to effectively collaborate with stakeholders at all levels of an organization. Skills and Expertise -Image Segmentation & Object Detection - Natural Language Processing (NLP) - Multimodal AI (vision and text) - Model Development and Optimization - Custom Model Architectures - Proprietary AI APIs - Genarative AI Technologies and Tools: - Model Development and Optimization: Huggingface, PyTorch, ONNX, Datasets, Pandas, Numpy, Scipy, SciKit-Learn, Sentence Transformers, PEFT, Accelerate, Loralib, TensorRT, Fairseq, LAVIS, TIMM, OpenNMT, TensorFlow, Jax - Visualization: Matplotlib, tSNE, UMAP - LLM Tools: OpenAI API (GPT-4, GPT-3.5 turbo, Ada through Davinci, etc.), Langchain, LLaMaIndex, Weaviate, Pinecone, Faiss, ScaNN I have worked on various engagements across multiple domains for solving numerous problem statements including: -Medical Bill Reimbursement System: Created a system to process medical bills, compare them to reimbursable procedures, and automate payments. - Fine-tuning Multimodal Models: Added fine-tuning capabilities to MiniGPT-4 and other multimodal large language models (LLMs). -E-commerce Data Adaptation: Adapted CLIP for e-commerce data, significantly improving zero-shot classification accuracy. -Custom Training Framework: Developed a framework to train encoder-based language models using the replaced token detection (RTD) objective. - Multimodal Model Architecture: Built a custom model using linear attention. - Model Optimization: Reduced the size of intent classification and NER models for an automotive virtual assistant while improving accuracy. - Siamese Network: I I am committed to delivering high-quality AI solutions tailored to your specific needs. Let’s work together to push the boundaries of AI and create innovative solutions for your business.