Hire Top Freelance Deep Learning DevelopersFind top freelance Deep Learning developers quickly and easily on Codementor. Work with our vetted developers who have the proven skills and experience to get the job done. Get help with projects by-the-hour or long-term. Hire a trusted Deep Learning freelancer on Codementor today.
**📝 Profile Context / Summary** With 10+ years across enterprise IT and global freelancing, I am an AI-Stack Architect—not just a full-stack developer. In 2026, the industry has shifted decisively: software is no longer just written; it is architected, governed, and continuously learned. The most valuable engineers are no longer those who simply write code, but those who can turn code into cognition—engineers fluent in the AI-stack. I am that engineer. I design and build agentic platforms—systems where AI doesn't just assist but actively plans, builds, tests, and releases software. I have successfully delivered complex solutions across Medical, Fintech, Employee Management, and SaaS industries, handling everything from AI-native frontends to hyper-scalable microservices with autonomous agent orchestration. **🤖 AGENTIC AI & MACHINE LEARNING** 2026 is the breakout year of AI inferencing—where trained models generate predictions and outputs from new data. Most AI computing is now spent on inference rather than training. I specialize in: Agentic AI & Orchestration: LangChain, LlamaIndex, AutoGen, CrewAI—building multi-agent systems that plan, act, and adapt in real time. Full-stack agent platforms combining proprietary training data, planning models, and custom actuation layers. Generative AI & LLMs: OpenAI GPT-4/API, Google Gemini, Anthropic Claude, HuggingFace Transformers. Retrieval-Augmented Generation (RAG) with vector databases (Pinecone, Chroma, Weaviate, FAISS). AI-Native Development: 42% of committed code is now AI-generated, projected to reach 65% by 2027. I don't just use AI tools—I orchestrate AI agents across the entire SDLC: planning, design, build, test, deployment, and maintenance. Deep Learning & Classical ML: TensorFlow, PyTorch, CNNs (Computer Vision), RNNs/LSTMs (Time-Series/NLP), Scikit-learn, Pandas, NumPy. Model Deployment & Optimization: Model compression, quantization, edge computing, cost-per-prediction optimization. AI Governance & Security: AI-generated code carries roughly double the security risk violations of human-written code. I implement robust governance, testing, and security controls for AI systems. **⚛️ MODERN FRONTEND** React remains the most widely used UI library, with 67% of new enterprise React projects now built on Next.js—a 300% increase since 2023. React Server Components are now the default: Core: React 19, Next.js 16 (App Router, Server Components, Turbopack), Remix, Svelte 5 (runes), Astro. Styling: Tailwind CSS, shadcn/ui (1.87M weekly downloads), Framer Motion, Material-UI. State: Zustand (35% adoption, 35ms updates) vs Redux (38% adoption, 65ms), TanStack Query, Jotai. Build Tooling: Vite 8 with Rolldown (Rust-based, 10-30x faster builds), Turbopack. TypeScript: Used by 38% of professional developers, required in 72% of frontend job postings. **📱 MODERN MOBILE** React Native's New Architecture (stable since 2024) delivers significant performance improvements through synchronous native module calls: Frameworks: React Native (Expo), NativeScript, Flutter. Native: iOS (Swift/SwiftUI), Android (Kotlin & Jetpack Compose). Emerging: GPU-powered rendering for consumer and enterprise apps. **⚙️ MODERN BACKEND & API** Runtimes: Node.js (NestJS, Express), Bun, Deno, Python (FastAPI—57.9% developer usage, up 7% from 2024), Java (Spring Boot 4.0—modularized, Java 25 LTS support). Spring AI 1.0: Built-in support for integrating LLMs and AI services into enterprise Java applications. API Design: RESTful, GraphQL (Federation), gRPC, Webhooks, WebSockets. Event-Driven: Apache Kafka, RabbitMQ, AWS SNS/SQS. **☁️ DEVOPS & CLOUD (2026 Standard)** Cloud-native and Serverless adoption has surpassed 70% penetration in enterprise IT. Multi-cloud is now the standard—Gartner projects over 75% of cloud customers will adopt this model: Cloud: AWS, GCP, Azure (multi-cloud architecture). Containerization & Orchestration: Docker, Kubernetes (K8s), Helm. Serverless: AWS Fargate, Lambda, Cloudflare Workers—extending to data pipelines, real-time streaming, and event-driven microservices. IaC: Terraform, AWS CDK, Pulumi. CI/CD: GitHub Actions, GitLab CI, ArgoCD, Jenkins. **🗄️ DATABASES & SEARCH** Relational: PostgreSQL (PostGIS), MySQL, SQLite. NoSQL: MongoDB, DynamoDB, Firebase. Vector (AI): Pinecone, Chroma, Weaviate (for RAG and semantic search). Search: Elasticsearch, Algolia, Meilisearch. Caching: Redis, Memcached. **🔗 CRM, AUTOMATION & INTEGRATION** In 2026, the CRM market is consolidating around Salesforce, Microsoft, ServiceNow, and HubSpot as a durable challenger. Both platforms have invested heavily in agentic AI, predictive intelligence, and conversational AI: CRMs: Salesforce (Apex), HubSpot (Agentic Engagement Object), Zoho. Low-Code/No-Code: Gartner forecasts the low-code market at $44.5 billion in 2026, with 75% of new enterprise apps built on low-code platforms. Automation: VBA, Excel Macros, Google App Script, Bubble.io, n8n, Make, Zapier. Citizen Development: 80% of low-code users are now "citizen developers". **🚀 Why Partner With Me in 2026?** The software industry has crossed a clear threshold in 2026. Generative AI is no longer just helping developers write code faster—it is reshaping how software is planned, built, tested, and delivered. The role of the developer has evolved from coder to curator of intent, constraints, and outcomes. **I bring:** 10+ years of battle-tested engineering across the full spectrum. Agentic AI fluency—the ability to orchestrate AI agents across the entire SDLC. Systems thinking and architectural judgment—skills that AI cannot replace. Security-first mindset—AI amplifies what's already there; where code quality is managed, AI accelerates delivery; where it isn't, it accelerates technical debt and security exposure. Whether you need an AI-native application, a microservices overhaul, an agentic workflow orchestration, or an intelligent CRM integration—I deliver professional, scalable, and governable solutions. Let's architect intelligence together. **Contact me today.**
I love to teach what I know. I think I can explain things easily with examples. I have been working as a Software Engineer for the last 5 years and have worked with some of the world's most reputed companies like **Open AI, Scale AI, Doloras Lab**, etc as a freelancer.
Senior Data Scientist with expertise in machine learning, natural language processing, information retrieval, and data engineering. Extensive experience in developing advanced algorithms and solutions across various industries. And, years of tutoring experience!
Embark on a transformative coding journey with me, a visionary computer science expert and a passionate mentor, bringing over two decades of rich expertise in the dynamic realms of programming, data science, and software architecture. My technical skills span across a broad spectrum, including mastery in programming languages like Python, Java, C++, C, and Scala, along with a profound understanding of algorithms, data structures, and the complex art of software design. My research interests include big data analysis, semi-stream join algorithms, and real-time data warehousing. As a mentor, I've illuminated the path for students globally, from prestigious universities in the USA, Australia, Canada, and the UK, in a vast array of subjects from Big Data Analytics to Cyber Security, and advanced programming languages. Currently, I am a lecturer of Computer Science at a Higher Education Institute. My academic prowess is underscored by a **PhD** in Computer Science, with my doctoral thesis titled: "Integrated Real-Time Distributed Stream-Disk Processing Architecture for Unstructured Big Data". Join me on codementor, where together, we'll navigate the intricacies of technology, unleashing the potential to innovate, solve real-world problems, and excel in your programming career.
My strengths lie in designing and implementing innovative solutions, leveraging advanced algorithms and techniques to extract valuable insights from data with extensive expertise in Data Science, Machine Learning, Deep Learning, Python, R... I have successfully collaborated with diverse clients, ranging from startups to large enterprises, across various industries. With a track record of delivering impactful projects, I'm passionate about empowering businesses with data-driven strategies
8 years of experience in building and managing AI Systems. * I develop end-to-end AI systems from requirements analysis, and data gathering to deployment, implementing new methods/research papers, and turning projects into research outcomes. I have achieved substantial performance in DL/ML/RL models for CV and NLP domain problems. * Implementing and deploying projects handling and maintaining scalability, research papers as well as POCs. * Project planning, requirements gathering, and analysing requirements to define the system's architecture, and implementation timeline. * Provide mentoring to junior developers for ML projects. Website: [roshantanisha.github.io/?ref=codementor](http://roshantanisha.github.io/?ref=codementor) Summary: I like to work on technology that is smart, simple and sophisticated. This sums up the vast knowledge required to work on projects to excel in a working product. I like to train Deep Neural Networks and understand them well. I have mentored many students for their AI careers, teaching them Machine Learning and Mathematics. I am a mentor for the RFS (Reach for the Stars) Programme by the Aga Khan Education Board for India. I am an alumnus of this program as well. I have a cumulative experience of 8 years working in the product and service-based industry for creating Machine Learning projects. I have done some innovative work that I am proud of and am continuing to do so. I try my best to contribute my expertise to the project I am working on. Highly Experienced in Machine Learning, Deep Learning, Advanced Deep Learning, Artificial Intelligence, and Algorithms, including models in the production environment, and deploying ML models. Working with top Indian colleges like BITS, niche NLP and CV, real-estate startups, MNCs, and Fortune top 20 companies, working with sensitive anonymized datasets, and creating state-of-the-art models are some of my achievements. I have strong and correct knowledge of Deep Learning concepts from the above experiences. \- Hands-on experience across several advanced AI and graphics-related domains, including: * **3D graphics and reinforcement learning pathfinding** for autonomous driving systems, including work related to the **NASA Rover Challenge**. * **Brain tumor segmentation and classification** using computer vision and deep learning techniques. * **Video analytics and video classification**, including in-video action recognition and classification workflows.
Hi! I love Java, Python, Javascript, distributed systems, large scale systems, machine learning, natural language processing and image processing. My work has been featured on the AWS blog (https://tinyurl.com/chaosrunner), The Guardian (https://tinyurl.com/topvocab) , Billboard.com (https://tinyurl.com/topprofane) and other print/digital publications. I also own Amazon's chaos testing framework called AWSSSMChaosRunner (https://github.com/amzn/awsssmchaosrunner). I am a Senior Engineer at Amazon's Prime Video and have worked on scaling backend systems to millions of transactions-per-second, utilising various cloud technologies and primarily working with Java, Kotlin and Javascript. This involves image/audio/text processing systems, creating & managing databases/APIs for mobile/web applications and everything in between. I have 15yrs+ experience with backend engineering, cloud tech, nlp, signal processing and image processing. I can help you with any of these topics. I also love hackdays and have attended 20 hackdays in Europe in the last couple of years and collaborated with beginners/experienced developers on different kinds of projects. Thanks for reading and hope to talk to you soon!
I’m an experienced software engineer with many years in the industry, including time at Google. I have strong expertise in Java, Python, and AWS, and I enjoy solving complex problems. I focus on building the right solutions, simplifying systems, and reducing complexity and cost. I’m looking to work on projects where I can use my skills and problem-solving mindset to create efficient and scalable software.
Technical cofounder, board member, and seasoned operator with experience building and growing early stage companies (pre-seed to late Series), large scale government and commercial projects, and nonprofits.
I have experience in research, data science, and machine learning. I have worked on projects related to deep learning, renewable energy, and dynamic discount algorithms. My education includes a PhD in Mathematical Modelling and a MicroMasters in Statistics and Data Science.
We'll share your request with freelancers with relevant Deep Learning skills and expertise.
Use our messaging feature to instantly chat with freelance Deep Learning developers around the world.
Choose the best freelance Deep Learning developer that meets your needs.
The length of a project depends on many factors, including the scope of your project and the technical complexity of it. When you post a freelance Deep Learning project request on Codementor, you’ll have the option to indicate when you’d expect the project to be completed. We suggest chatting with the interested developers to ensure both sides are on the same page. For more information on how to post a freelance Deep Learning request on Codementor, check out our article.
We don’t charge anything when you post a freelance hiring request for Deep Learning developers! You’ll have the chance to determine what the budget for your project is when you post the request. You’ll only need to pay the developer if you’re 100% satisfied with their work. Please know that Codementor charges a small service fee when a developer completes the job.
We do a comprehensive technical and communications screen of all Deep Learning developers at Codementor. Our network includes book authors, popular open source contributors, top Stack Overflow users and engineers at top tech companies. In addition, to continually ensure the quality of our freelancers, we regularly check in on existing Deep Learning developers’ user satisfaction rates.
For more answers to frequently asked questions, see here.