iTradeNetwork

Machine Learning Full Stack Developer

Denver, CO, US

Remote
Full-time
about 2 months ago
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Summary

Job Summary Are you a machine learning enthusiast who thrives on transforming data into impactful insights? Do you dream in algorithms, data pipelines, and model architectures? We're looking for a Machine Learning Full Stack Developer who is a true builder-someone who can roll up their sleeves, design, develop, and deploy scalable ML solutions. This isn't just another job; it's an opportunity to be part of a team that is shaping the next generation of AI-driven products that will directly drive growth. Key Responsibilities: * Build the Future: Design, develop, and deploy end-to-end machine learning systems optimized for performance, scalability, and rapid deployment. * AI-First Development: Leverage AI tools (GitHub Copilot, Cursor AI, ChatGPT, Otter AI) to enhance code efficiency, refactoring, debugging, and documentation. * Rapid Prototyping: Rapidly prototype and deploy ML models and full-stack applications using AI-assisted development tools. * ML & Data Pipelines: Build and optimize data pipelines for efficient ingestion, transformation, and analysis. * LLM Integration: Implement and fine-tune large language models (LLMs) like GPT, BERT, and integrate them seamlessly into production systems. * MLOps Excellence: Design, develop, and implement CI/CD pipelines for continuous deployment and monitoring of machine learning models. * Cloud-Native Development: Build and maintain cloud-native ML applications on platforms like GCP, AWS, or Azure. * Collaboration: Work closely with product managers, data scientists, and engineers to translate business requirements into scalable ML solutions. * Solve Complex Problems: Tackle technical challenges, from optimizing algorithms to deploying real-time machine learning systems. Tech Stack: * Languages: Python, Java * ML Frameworks: TensorFlow, PyTorch, Scikit-learn * Databases: BigQuery, PostgreSQL, Redis, MongoDB * Cloud & DevOps: Kubernetes, Docker, Terraform, GCP, AWS * MLOps Tools: MLflow, Kubeflow, Airflow * AI Tools: GitHub Copilot, Cursor AI, Otter AI, ChatGPT * NLP & LLMs: GPT, BERT, Transformer architectures * CI/CD & Automation: GitHub Actions, Jenkins What You Bring: * Bachelor's degree in Computer Science, Engineering, or just equivalent hands-on experience with no degree! * 5+ years of hands-on experience in machine learning and full stack development, with at least 3+ years in data science and 3+ years in ML engineering. * Proven ability to develop and deploy ML models with minimal requirements. * Strong coding ability demonstrated via a HackerRank assessment (preferred HackerRank Gold Badge). * Expertise in Python and Java for building production-grade ML systems. * Strong experience with cloud platforms like GCP, AWS, or Azure. * Deep understanding of MLOps best practices, including CI/CD pipelines and model monitoring. * Ability to quickly understand and implement complex data models and algorithms. * Strong problem-solving, analytical thinking, and debugging skills. * Excellent communication and collaboration abilities.

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