Senior Data Architect

Key Skills: Machine Learning, AI Artificial intelligence, ML, Gen AI, Architect, Data Governance, GDPR, Pyspark, AWS, Azure, Pytorch, Python, MySQL, Tensorflow

Roles and Responsibilities:

• Architect and deploy scalable, secure, and efficient data platforms tailored for AI/ML workloads, including Generative AI solutions.
• Design and manage data pipelines to support model training, validation, and deployment using tools such as PySpark, Kafka, and TensorFlow.
• Integrate AI frameworks and APIs (e.g., OpenAI, Hugging Face) into cloud-native data architectures on platforms like AWS, Azure, or GCP.
• Collaborate closely with data scientists, ML engineers, and business stakeholders to align data solutions with strategic goals.
• Lead data governance, security, and compliance initiatives, ensuring alignment with regulations such as GDPR and CCPA.
• Explore and implement LLM fine-tuning, prompt engineering, and embedding-based architectures using vector databases (e.g., Pinecone, Weaviate).
• Stay current with the latest in Generative AI, MLOps, and data engineering to continually improve system design and performance.

Skills Required:

Must-Have Skills:

• Deep expertise in Data Architecture, with focus on AI/ML and Generative AI integration
• Strong experience in data governance, model lifecycle management, and compliance (GDPR, CCPA)
• Hands-on knowledge of AI/ML frameworks: TensorFlow, PyTorch, Scikit-learn
• Proficiency in Python, PySpark, SQL, and data pipeline frameworks
• Experience with cloud platforms and their ML services:
• AWS (SageMaker)
• Azure (Azure ML)
• Google Cloud (Vertex AI)
• Proven track record working with Generative AI models (e.g., GPT, BERT), including fine-tuning and deployment
• Familiarity with AIOps, MLOps, and data security protocols

Nice-to-Have Skills:

• Experience with vector databases (e.g., Pinecone, Weaviate)
• Familiarity with LLM prompt engineering and embedding techniques
• Integration experience with OpenAI APIs, Hugging Face Transformers, and LangChain
• Domain knowledge in the Life Sciences industry
• Experience deploying AI-powered applications in production environments

Education: Bachelor's Degree in related field