• Design, adapt, and optimize deep learning architectures for scientific domains and data modalities. • Own and deliver on complex ML projects, including experiment design, implementation, evaluation, and iteration based on results. • Write clean, well-tested code in PyTorch and NumPy enabling a high experimentation rate. • Stay current with deep learning research and its applications in chemistry and biology. • Propose and prototype new ideas to enhance our modeling capabilities. • Work closely with scientists and engineers across the team to integrate models into our product and infrastructure.

• Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives. • Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain. • Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration). • Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid). • Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services. • Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT). • Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy. • Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots. • Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and aligned with customer needs. • Participate in peer reviews, contribute to shared repositories, and document models and experiments for reproducibility.

• Own ML powered features from design through deployment • Understand and share domain knowledge • Prioritize your work independently • Proactively seek and offer support to teammates • Understand and troubleshoot our deployment pipelines • Use our monitoring and observability tools • Serve as a subject matter expert for the features and services

• lead machine learning efforts across Hightouch • oversee product development and team execution • enhance team reliability and incident management • foster team growth and engagement