Required Qualifications
We’re looking for someone with:
- 5+ years of experience in data architecture, with a focus on AI/ML-enabled systems.
- Hands-on experience with Generative AI models (e.g., OpenAI GPT, BERT, or similar), including fine-tuning and deployment.
- Proficiency in data engineering tools and frameworks, such as Apache Spark, Hadoop, and Kafka.
- Deep knowledge of database systems (SQL, NoSQL) and cloud platforms (AWS, Azure, GCP), including their AI/ML services (e.g., AWS Sagemaker, Azure ML, GCP Vertex AI).
- Strong understanding of data governance, MLOps, and AI model lifecycle management.
- Experience with programming languages such as Python or R and frameworks like TensorFlow or PyTorch.
- Excellent problem-solving and communication skills, with a demonstrated ability to lead cross-functional teams.
Preferred Skills
- Familiarity with LLM fine-tuning, prompt engineering, and embedding models.
- Strong domain expertise in Life Science Industry
- Experience integrating generative AI solutions into production-level applications.
- Knowledge of vector databases (e.g., Pinecone, Weaviate) for storing and retrieving embeddings.
- Expertise in APIs for AI models, such as OpenAI API or Hugging Face Transformers.