Senior Professional Llm Ai Engineer

SummaryGainwell is seeking LLM Ops Engineers and ML Ops Engineers to join our growing AI ML team This role is responsible for developing deploying and maintaining scalable infrastructure and pipelines for Machine Learning ML models and Large Language Models LLMs You will play a critical role in ensuring smooth model lifecycle management performance monitoring version control and compliance while collaborating closely with Data Scientists DevOps andRole Description Core LLM Ops Responsibilities Develop and manage scalable deployment strategies specifically tailored for LLMs GPT Llama Claude etc Optimize LLM inference performance including model parallelization quantization pruning and fine-tuning pipelines Integrate prompt management version control and retrieval-augmented generation RAG pipelines Manage vector databases embedding stores and document stores used in conjunction with LLMs Monitor hallucination rates token usage and overall cost optimization for LLM APIs or on-prem deployments Continuously monitor models for its performance and ensure alert system in place Ensure compliance with ethical AI practices privacy regulations and responsible AI guidelines in LLM workflows Core ML Ops Responsibilities Design build and maintain robust CI CD pipelines for ML model training validation deployment and monitoring Implement version control model registry and reproducibility strategies for ML models Automate data ingestion feature engineering and model retraining workflows Monitor model performance drift and ensure proper alerting systems are in place Implement security compliance and governance protocols for model deployment Collaborate with Data Scientists to streamline model development and experimentation Leadership Skills Should be able to work as a team lead interface with team leads of other functions departments understand business requirements cost sensitivity and translate the same to an appropriate solution that is feasible to develop and deploy What Were Looking For Bachelor s or Master s degree or higher in Computer Science Data Sciences-Machine Learning Engineering or related fields Strong experience with ML Ops tools Kubeflow ML flow TFX Sage Maker etc Experience with LLM-specific tools and frameworks LangChain Lang Graph LlamaIndex Hugging Face OpenAI APIs Vector DBs like Pinecone FAISS Weavite Chroma DB etc Solid experience in deploying models in cloud AWS Azure GCP and on-prem environments Proficient in containerization Docker Kubernetes and CI CD practices Familiarity with monitoring tools like Prometheus Grafana and ML observability platforms Strong coding skills in Python Bash and familiarity with infrastructure-as-code tools Terraform Helm etc Knowledge of healthcare AI applications and regulatory compliance HIPAA CMS is a plus Strong skills in Giskard Deepeval etc Understanding of business use cases cost sensitivity strong interpersonal skills architecting skills and abilities to convince multiple stakeholders Qualifications Bachelor or Masters or Higher in Computer Sciences Data Sciences or any related field 7 years to 10-11 Years of experience in deploying ML DL and LLM based solutions in large scale deployment environment or related experience Experience with fine-tuning LLMs and serving them in production at scale Knowledge of model compression techniques for LLMs LoRA QLoRA quantization-aware training Experience with distributed systems and high-performance computing for large-scale model serving Awareness of AI fairness explainability and governance frameworks What You Should Expect in This Role Fully Remote Opportunity Work from anywhere in the U S India Minimal Travel Required Occasional travel opportunities 0-10 Opportunity to Work on Cutting-Edge AI Solutions in a mission-driven healthcare technology environment