Applied AI Engineer

CoSourcing Partners Inc.; New York (NY); On-site; USD 96,000 - 165,000; Full time

Job summary

CoSourcing Partners Inc. is seeking an Applied AI Engineer for a 6- to 12-month contract-to-hire onsite role in NYC or San Francisco, CA.

You will apply state-of-the-art ML methods to assess biological threats and design precision biologics, collaborating with computational biologists and software engineers. You will contribute to a client-wide R&D roadmap, adapt frontier models for biological tasks, and build robust evaluation frameworks to measure performance while staying current at the

Qualifications

• Data-centric development and evaluation of ML models.
• Strong Python and PyTorch knowledge.
• Experience with cloud platforms (AWS) and distributed systems.
• Solid understanding of probability and statistics.

Responsibilities

• Contribute to crafting and executing on the client-wide R&D roadmap.
• Develop and apply modeling approaches for biological security and precision biologics.
• Create evaluation frameworks to measure model performance on key tasks.
• Collaborate with computational biologists to curate meaningful biological datasets.
• Build, deploy, and scale model training and evaluation infrastructure with software engineers.
• Interpret and communicate results to clients and external collaborators.

Skills

Data-centric ML

Python

PyTorch

AWS

Distributed systems

Probability & statistics

Tools

PyTorch

AWS

Job description

Job Title: Applied AI Engineer Duration: 6-12 months contract to hire Location: NYC or San Francisco, CA Job Type: Onsite

Our client is an applied biological intelligence company. They build and deploy software and biological AI systems to safeguard humanity.

The same AI architectures that enable self-driving cars, land rockets with precision, and deliver expert-level reasoning are beginning to be deployed in biological design. To stay ahead, we must advance our arsenal of tools to capture and design against real-time sensitivities in nature’s evolving mutational landscape.

Our client is a group of mission-driven software engineers from Palantir and applied biological ML engineers from MIT’s Broad Institute and DeepMind making the latest advances in computational biology accessible in the real-world for federal and commercial use.

We are seeking a highly skilled, data-centric AI Engineer to develop and apply state-of-the‑art ML methods for assessing and responding to biological threats and for rapidly designing precision biologics.

The Role

• Contribute to crafting and executing on the client-wide research and development roadmap


• Develop, build, and apply modeling approaches—including adapting and post-training biological frontier models—for tasks in biological security and the design of precision biologics


• Develop, build, and apply evaluation frameworks to rigorously assess model performance on key tasks


• Interrogate models to understand their biological learnings, capabilities, and limitations


• Collaborate closely with computational biologists to understand the signal and artifacts inherent in biological data, and to create and curate datasets


• Collaborate closely with software engineers to build, deploy, and scale model training and evaluation infrastructure


• Visualize and communicate results within Client and externally


• Work with customers and external collaborators to understand their needs and be an effective representative of Client


• Embrace learning about areas technical and non-technical across Client


• Stay up-to-date on the state-of-the‑art methods at the intersection of AI and biology

Qualifications (required)

• Experience with data-centric development and evaluation of ML models


• Highly proficient in Python and deep learning libraries (e.g., PyTorch)


• Experience with cloud computing platforms (e.g., AWS) and distributed systems


• Strong understanding of probability and statistics

Qualifications (preferred)

• Proven ability to design, implement, and evaluate new ideas in ML


• Experience with pre- or post-training language models, developing reasoning agents, and/or time series modeling


• Experience working with biological data or other types of noisy and heterogenous datasets


• Experience with ML-centric bioinformatics and structure-based tools (e.g., AlphaFold)


• Experience building data pipelining and training infrastructure


• Contributions to open-source projects