Python ML Lead

We are seeking an experienced

Python ML Lead to lead the design, development, and deployment of scalable Machine Learning and Generative AI solutions. The ideal candidate will have extensive experience in Python, production-grade ML systems, Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and Google Cloud Platform (GCP). This role requires strong technical leadership, hands-on development expertise, and the ability to collaborate with cross-functional teams and customers to deliver secure, scalable, and high-performance AI solutions. Key Responsibilities

• Lead the end-to-end development lifecycle of Machine Learning solutions, from data preparation to model deployment and monitoring.
• Design, train, fine-tune, evaluate, and operationalize ML models for real-world business applications.
• Develop and optimize production-grade Retrieval-Augmented Generation (RAG) pipelines and Large Language Model (LLM) applications.
• Engineer, evaluate, and continuously refine prompts to improve LLM accuracy and performance.
• Analyze, clean, preprocess, and transform structured and unstructured datasets into high-quality features.
• Build scalable ML pipelines and deployment workflows on Google Cloud Platform (GCP).
• Implement MLOps best practices, including CI/CD, model versioning, monitoring, performance tracking, and data drift detection.
• Collaborate with data engineers, software developers, and business stakeholders to deliver production-ready AI solutions.
• Translate customer requirements into secure, scalable, and maintainable ML architectures.
• Provide technical leadership, mentor team members, and drive engineering best practices. Required Skills & ExperienceExperience
• 10+ years of overall software engineering experience.
• Minimum 5+ years of experience building secure, scalable, and high-performance software applications.
• Minimum 3+ years of hands-on experience designing, developing, and deploying production-grade Machine Learning applications. Machine Learning & AI
• Strong expertise in Machine Learning, Deep Learning, and Artificial Intelligence.
• Hands-on experience with Natural Language Processing (NLP), Computer Vision, or related AI domains.
• Proven experience designing and deploying Retrieval-Augmented Generation (RAG) architectures.
• Strong understanding of Large Language Models (LLMs), prompt engineering, model evaluation, and optimization. Programming & Frameworks
• Expert-level proficiency in Python.
• Strong experience with NumPy, Pandas, Scikit-learn.
• Hands-on experience with TensorFlow, PyTorch, XGBoost, or similar ML frameworks.
• Experience with LangChain or equivalent GenAI orchestration frameworks. Cloud & MLOps
• Hands-on experience with Google Cloud Platform (GCP).
• Experience with Vertex AI, BigQuery, Cloud Storage, and related GCP services.
• Strong understanding of MLOps practices including model deployment, monitoring, CI/CD, and pipeline automation. Soft Skills
• Excellent analytical and problem-solving skills.
• Strong communication and stakeholder management abilities.
• Experience working in customer-facing environments.
• Ability to lead technical discussions and mentor engineering teams. Preferred Qualifications
• Google Cloud Professional Machine Learning Engineer Certification.
• Google Cloud Generative AI Engineer Certification.
• TensorFlow Certified Developer Certification.
• Experience integrating ML pipelines with large-scale data engineering workflows.
• Familiarity with distributed data processing and modern AI deployment architectures.