Position: Machine Learning Researcher
Company: Freelance
Experience required: 3y
English level: upper

**About Us:**
Ladder Therapeutics is a Y-Combinator-backed company, working at the intersection of machine learning and RNA biology. We are creating an in-silico and in-vitro platform that enables the discovery of small molecule modulators of RNA. We are backed by mission-driven investors Hummingbird Ventures, 50Years, AME Cloud Ventures.

The current toolkit for developing drugs is focused almost entirely on protein targets. The actions of these proteins however are known to be influenced by areas of the genome that do not encode proteins, the non-coding genome, classically termed “junk DNA”. Variation in the non-coding genome, the “dark genome” is associated with many diseases but remains inaccessible by classical drug discovery. 

**The Role:**
We are seeking curious people, with a desire to make a significant impact on the strategy and culture of the company. 

In this role, you will lead the scientific and technical development of the machine learning pipelines at the intersection of RNA biology and chemistry. You will be working closely with the biologists and influencing the experimental design, target selection and progression of biology programs.  

You will be the face of the company, presenting your work to the research community and conferences such as NeurIPS. 

**A bit about you:**
- PhD or equivalent in a quantitative field (e.g., computer science, computational biology, bioinformatics, statistics, or equivalent). 
- Experience with RNA structure datasets and methods is highly desirable
- Knowledge of modern tools for ML such as Tensorflow, Pytorch. 
- Understanding of both emerging and foundational machine learning methods (supervised/unsupervised) such as:  linear/nonlinear methods for regression, classification, and dimensionality reduction, deep learning (CNNs, RNNs, GCN, transformers). Experience with graph-based representations is a plus.
- Experience building research prototypes and developing product-worthy tools from them.
- Track record of collaborative research in machine learning, biology, and related fields.

**Nice to have:**
- Experience in mining features from large data sets
- Experience with MLOps frameworks such as TensorFlow Extended, Kubeflow, MLFlow.
- Experience with end-to-end ownership and engineering practices for AI/ML pipelines.
- Experience with cloud platforms (AWS, GCP, Azure).
- Experience with containerization and deployment of machine Learning models.

**What we offer:**
- We offer an opportunity to work at a rapidly growing YC-backed start-up. Your work will have a direct impact on the experiments we run, and direction of the drug discovery programs. You have the ability to propel your career forward with significant responsibility and autonomy. 
- We pride ourselves in an environment that cultivates curiosity, creativity and autonomy, where why, is always the most important question.
- Our stellar SAB Includes industry leaders in Pharma, AI, and RNA Biology. You will work closely with thought leaders in the field and shape the future of RNA drug discovery.