Senior Data Scientist

GE Healthcare GE Healthcare · Healthcare · Bengaluru, Karnātaka, India · Digital Technology / IT

Seeking an AI Engineer to design, develop, and deploy intelligent systems using ML, DL, and generative models. Responsibilities include data engineering, model development, deployment, monitoring, exploring GenAI and Agentic AI, and developing agentic platforms. The role involves fine-tuning GenAI models, implementing ML models for various tasks, building AI pipelines, and deploying models to production. Experience with cloud platforms like AWS (SageMaker, Bedrock) and frameworks like LangChain is expected. The role also emphasizes prompt engineering, RAG, system integration, and ensuring model safety and compliance.

What you'd actually do

  1. Develop and fine-tune Generative AI models (e.g., LLMs, diffusion models).
  2. Design and implement machine learning models for classification, regression, clustering, and recommendation tasks.
  3. Build and maintain scalable AI pipelines for data ingestion, training, evaluation, and deployment.
  4. Collaborate with cross-functional teams to understand business needs and translate them into AI solutions.
  5. Ensure model performance, fairness, and explainability through rigorous testing and validation.

Skills

Required

  • Python
  • Amazon SageMaker
  • Amazon Bedrock
  • Prompt engineering
  • fine-tuning of LLMs
  • LLMs: Claude, LLaMA, Gemini, Mistral, Falcon
  • APIs: Amazon Bedrock
  • model types: encoder-decoder, decoder-only, diffusion models
  • design, develop, and deploy agent-based AI systems
  • Integrate Generative AI into real-world applications
  • Prompt design for zero-shot, few-shot, and chain-of-thought reasoning
  • Fine-tuning and parameter-efficient tuning (LoRA, PEFT)
  • Retrieval-Augmented Generation (RAG) design and implementation
  • Event-driven and serverless architectures (e.g., AWS Lambda, EventBridge)
  • LangChain, LlamaIndex
  • Vector databases: FAISS, Pinecone, Weaviate, Amazon OpenSearch
  • Langgraph, Langchain
  • AWS (Bedrock, SageMaker, Lambda, S3)
  • CI/CD pipelines for GenAI workflows
  • Data privacy and governance (GDPR, HIPAA)
  • Model safety: content filtering, moderation, hallucination control
  • Model performance tracking (latency, cost, accuracy)
  • Logging and observability (CloudWatch, Prometheus, Grafana)
  • Cost optimization strategies for GenAI inference
  • Working with product, legal, and compliance teams
  • Translating business requirements into GenAI use cases
  • Creating PoCs and scaling to production
  • Bachelor’s degree in engineering with minimum four years of experience

Nice to have

  • Azure (OpenAI, Functions)
  • GCP (Vertex AI)

What the JD emphasized

  • expertise in both traditional Artificial Intelligence and emerging Generative AI technologies
  • designing, developing, and deploying intelligent systems
  • exploring GenAI applications, Agentic AI and developing agentic platforms
  • experimentation, rapid prototyping, and delivering scalable AI solutions
  • Develop and fine-tune Generative AI models
  • Design and implement machine learning models
  • Build and maintain scalable AI pipelines
  • Deploy models to production
  • design, develop, and deploy agent-based AI systems
  • Integrate Generative AI into real-world applications
  • Prompt Engineering & Fine-Tuning
  • Retrieval-Augmented Generation (RAG) design and implementation
  • Data privacy and governance (GDPR, HIPAA)
  • Model safety: content filtering, moderation, hallucination control

Other signals

  • designing, developing, and deploying intelligent systems
  • exploring GenAI applications, Agentic AI and developing agentic platforms
  • develop and fine-tune Generative AI models
  • design and implement machine learning models
  • build and maintain scalable AI pipelines
  • deploy models to production
  • design, develop, and deploy agent-based AI systems
  • integrate Generative AI into real-world applications