Forward Deployed Engineer

Tamarind Bio Inc.
San Francisco, CA, United States
6 days ago
Apply on startup.jobs
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Computational Biology Software Debugging DevOps Python (Programming Language) Machine Learning Machine Learning Operations Data Pipelines

Job description

We’re hiring a Forward Deployed Engineer - one of the highest-leverage roles on the team. You’ll sit at the intersection of engineering, product, and customers - working directly with scientists, ML teams, and pharma stakeholders to deploy Tamarind into real-world workflows. This role owns the full arc: from first technical conversation * pilot * production deployment. Every deployment becomes a product signal, a reference customer, and a revenue driver. The customer relationship moves at the speed you move., * 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

Week in the Life

  • Join customer calls to scope scientific workflows
  • Deploy and test models on real customer datasets
  • Work across infrastructure, APIs, and ML systems to ensure performance
  • Iterate quickly based on feedback from scientists
  • Translate field learnings into product improvements, 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

Requirements

  • 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

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on startup.jobs
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:17 min

Mapping the maturity roadmap for scaled devops adoption

Dominik Krichbaum Dominik Krichbaum · World Congress 2026 Europe

6:08 min

Applying software engineering environments and testing to data pipelines

Matthias Niehoff Matthias Niehoff · World Congress 2024

2:36 min

Applying supervised machine learning for practical rule extraction

Katja Träumner

1:20 min

Identifying multi-disciplinary talent for developer experience engineering roles

Hazal Mestci +1 · Coffee With Developers

7:10 min

Exploring pathways into the machine learning engineering field

Jose Luis Latorre Millas · LIVE

3:18 min

Scaling global network engineering through DevOps culture

Stuart Clark · LIVE

Videos

See all

Related articles

See all