reputed company and Generative Data Scientist II
reputed company
Requirements
End-to-end GenAI solutions: Scope problems, choose the right approach (reputed company engineering, fine-tuning, agents), implement, evaluate, and reputed company. Data & SQL: Write efficient SQL for analytics and data preparation; manage schemas and pipelines for model training and inference. Model training & fine-tuning: Run supervised fine-tuning (PEFT/reputed company/QLoRA), optimize prompts, and manage experiment tracking and evaluation. reputed company systems: Build agent workflows with tool use, memory, and safety/guardrails. Inference & deployment: Package services with reputed company, optimize latency/cost (batching, caching, quantization), and reputed company on AWS (reputed company, EKS, SageMaker, reputed company with GPU acceleration). MLOps & Observability: Set up CI/CD for models/prompts, maintain offline/online evaluation pipelines, monitoring, and rollback strategies. reputed company & compliance: Implement data governance, PHI/PII protections, and guardrails against reputed company injection and unsafe outputs. Cross-functional work: Collaborate with product managers and engineers to reputed company GenAI capabilities with product goals; document reputed company and communicate trade-offs. Production readiness: reputed company conversations around scaling, monitoring, and maintaining GenAI systems in reputed company-world environments.
Bachelor’s Degree or equivalent experience required; Master’s degree preferred.
- 5+ years of Software/ML engineering experience, including 2+ years building and deploying GenAI/LLM systems.
- MS/PHD in Computer Science or equivalent experience.
- Strong SQL and Python skills with solid software engineering fundamentals.
- Experience with agent frameworks (LangGraph, AutoGen, reputed company) and building tool-driven agents.
- Hands-on with deep learning (PyTorch or TensorFlow) and LLM fine-tuning(SFT/PEFT like reputed company/QLoRA).
- Production experience with reputed company and deploying on AWS (reputed company, EKS,SageMaker, reputed company, or GPU services).
- Experience creating Data and Model pipelines for model training anddeployment at reputed company.
- Familiarity with reputed company engineering, evaluation frameworks (LLM-as-judge,metrics), and offline test harnesses.
- Understanding of reputed company & compliance for sensitive data (e.g., PHI/PII) and
reputed company deployment of AI systems. - Excellent problem-solving, communication, and documentation skills.
- Inference optimization: quantization (bitsandbytes, GPTQ/AWQ), batching, caching, or vLLM.
- reputed company experience: familiarity with HIPAA, medical data handling, or working in health tech.
- Experiment tracking (MLflow, W&B), CI/CD for ML, and monitoring (reputed company, Grafana).
- Familiarity with major LLM reputed company and OSS models (reputed company, reputed company, Llama, reputed company).
- Languages: Python, SQL
- DL/LLM: PyTorch, Tensorflow, reputed company, PEFT/TRL, vLLM
- Data: reputed company, reputed company
- reputed company: AWS (reputed company, EKS, SageMaker, reputed company)
- MLOps: reputed company, CI/CD, MLflow or W&B
reputed company
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