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# Senior Data Scientist

- **Company:** MIRA TALENT LLC
- **Location:** Cambridge, MA, United States
- **Experience:** Expert
- **Salary:** $220,000.0 - $300,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Continuous Integration, Python (Programming Language), Machine Learning, Molecular Modeling, Tensorflow, Workflow Management Systems, Pytorch, Large Language Models, Generative AI, Information Technology, Variational Autoencoders, Machine Learning Operations, Stable Diffusion, Data Pipelines, Docker
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25304_4f27fe6ab1aa911c7a242cfccdcc0a97

## About the Role

We are looking for go-getters with an entrepreneurial mindset, who can wear many hats and thrive in organized chaos! They are well-established, with significant financial backing and set the bar high when it comes to their people., * PhD or MSc in Machine Learning, Computational Science, Mathematics, Computer Science, or a related field

 * 5+ years of applied ML experience in biotech, pharma, or high-impact scientific environments
 * Strong hands-on expertise in Python and modern ML frameworks (PyTorch, JAX, TensorFlow)
 * Experience taking models from research to production-grade systems
 * Proven ability to lead independently on cross-disciplinary projects
 * Comfort working in fast-paced, entrepreneurial, and startup-like environments, * Proteomics or mass spectrometry integration
 * Biophysics or molecular dynamics
 * Generative modelling (diffusion, flow models, VAEs)
 * LLM-based agents and scientific workflow automation
 * MLOps and scalable infrastructure (AWS, MLflow, Docker, CI/CD, orchestration tools)

## Description

* Leading AI/ML strategy across early-stage venture programs and defining what "high impact" looks like in practice
 * Designing, building, and deploying ML systems across protein design, molecular modelling, docking, systems biology, and scientific workflow automation
 * Developing LLM-based agents to accelerate research and automate complex scientific processes
 * Establishing benchmarking, validation, scaling, and reproducibility standards to ensure models are robust and actionable
 * Owning end-to-end ML architecture - from data pipelines and infrastructure through to deployed systems
 * Partnering directly with scientific founders and cross-functional teams to guide technical direction
 * Mentoring early ML hires and helping shape the first ML teams
 * Translating emerging AI/ML research into practical tools that can move ventures forward
 * Influencing company strategy through hands-on technical leadership