Machine Learning Full Stack Developer

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.