Description

Lead the design, development, and production deployment of scalable Generative AI and ML solutions.

This role is hybrid.

Responsibilities

• Architect end-to-end Generative AI solutions, including RAG pipelines, agentic workflows, and model fine-tuning strategies.
• Design, develop, and operationalize ML models using prompt engineering, vector search, and data processing techniques.
• Build and deploy scalable machine learning pipelines on GCP or equivalent cloud platforms, covering data warehousing and dashboarding.
• Lead and mentor ML/data science teams, acting as the senior-most developer for clean, scalable code.
• Evaluate LLM responses and iteratively modify prompts to improve performance and accuracy.

Required Skills

• 8+ years of software engineering experience building secure, scalable applications.
• 5+ years of experience designing and deploying ML/AI applications.
• 2+ years leading and mentoring ML or data science teams.
• Expertise in Python, Numpy, Pandas, and ML libraries (XGBoost, TensorFlow, PyTorch, Scikit-learn, LangChain).
• Hands-on experience with Document extraction, Conversational AI, Vision AI, or NLP.
• Strong understanding of data cleaning, feature selection, model training, and deployment.
• Familiarity with Google Cloud (GCP) or AWS machine learning services.

Preferred Skills

• Google Cloud Certified Professional Machine Learning or TensorFlow Certified Developer certification.
• Experience with AutoML and computer vision technologies.

Key Skills

Education

Master's degree