Founding Forward Deployed Engineer
Deploys AI/ML workflows for scientists and pharma customers, owning pilots from scoping to production. Configures models, optimizes pipelines, and feeds insights to product team. Requires strong Python engineering and AI systems experience.
About the job
What You’ll Do
- Work directly with customers (scientists, ML teams, pharma orgs) to understand workflows and translate needs into deployable solutions
- Stand up AI/ML workflows using Tamarind’s platform — often within days of initial engagement
- Configure and deploy models (e.g. protein structure, docking, generative models) against real datasets
- Own pilots end-to-end — from scoping to execution to expansion
- Debug, adapt, and optimize workflows across compute, models, and data pipelines
- Partner with product and engineering to turn customer feedback into roadmap inputs
- Support technical discussions, demos, and deployments across the sales cycle
Ideal Qualifications
- Strong engineering fundamentals (Python preferred)
- Experience working with AI/ML systems or data pipelines
- Ability to operate in ambiguous, fast-moving environments
- Strong communication skills — able to interface with both technical and non-technical stakeholders
- Willingness to work onsite in San Francisco
Technology
Tamarind operates at the intersection of DevOps, MLOps, and Computational Biology. You’ll work across:
- ML models (protein design, structure prediction, docking)
- GPU-based compute infrastructure
- APIs, workflows, and orchestration layers
- Scientific datasets and research pipelines
Skills
Python, AI/ML, MLOps, DevOps, GPU, APIs, Computational Biology, Protein Design, Structure Prediction, Docking
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