The RoleWe’re looking for a Senior ML Engineer to lead the design, deployment, and optimization of large-scale models powering intelligent agents. Your role spans model architecture, operational deployment, and production monitoring.Key ResponsibilitiesDesign, fine-tune, and evaluate large language models and neural networks for modular agent behaviorBuild robust ML pipelines (data ingestion, feature engineering, model training, serving, monitoring)Develop containerized model serving infrastructure (Docker, Kubernetes), integrating with backend APIsImplement evaluation frameworks, A/B testing, and performance metrics to quantify agent effectivenessEnsure reproducibility, traceability, and compliance across ML lifecycleCollaborate with backend engineers to define inference service SLAs and efficient real-time ML deliveryMentor junior ML teammates and establish team-level best practicesRequirements5+ years as an ML Engineer or applied ML researcher with production model deployment experienceStrong Python skills, experience with ML frameworks (TensorFlow, PyTorch) and LLM tooling (HuggingFace)Expertise in MLops: Docker, Kubernetes, model serving (e.g., Triton, FastAPI), CI/CDFamiliarity with data pipelines, SQL, cloud platforms (AWS SageMaker, GCP Vertex, Azure ML)Solid understanding of model evaluation, A/B testing, and ML performance metricsExcellent collaboration skills with product, backend, and data teamsNice to HavesPrior work with conversational agents, retrieval-augmented generation, or multi-model orchestrationExperience with vector search stacks (e.g. Pinecone, FAISS)Knowledge of embedding techniques, prompt engineering, or Reinforcement Learning from Human Feedback (RLHF)Startup experience and ability to navigate ambiguity and shape technical directionWhy You Should JoinCompetitive equity & pay - get in early and own what you build.Work closely with experienced founders with a proven startup track record.Move fast, ship fast - no corporate bureaucracy.Shape the AI revolution in healthcare - massive market, untapped potential #J-18808-Ljbffr