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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Scientist (USA Remote) - **Company:** Turnitin, LLC - **Location:** Dallas, TX, United States (Remote available) - **Experience:** Expert - **Salary:** $112,125.0 - $186,875.0 - **Contract:** Permanent contract - **Skills:** JavaScript (Programming Language), Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Automation of Tests, Unix, Computer Programming, DevOps, Github, Python (Programming Language), Machine Learning, Language Modeling, Open Source Technology, Raw Data, Software Engineering, SQL Databases, Web Services, Scripting, Pytorch, ReactJS, Flask (Web Framework), Large Language Models, Prompt Engineering, Deep Learning, Jupyter, Git, Scikit Learn, Information Technology, HuggingFace, Front End Software Development, Docker - **Published:** May 19, 2026 - **Apply:** https://jobs.smartrecruiters.com/TurnitinLLC/744000111110355-senior-machine-learning-scientist-usa-remote- ## About the Role * Experience working with text data to build Deep Learning and ML models, both supervised and unsupervised. Experience with deep learning in other modalities such as vision and speech would be a strong bonus. * A strong understanding of the math and theory behind machine learning and deep learning. * Software engineering background with at least 8 years of experience (we use Python, SQL, Unix-based systems, git, and github for collaboration and review). * Machine / Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). * An understanding of Language Models, using and training / fine-tuning and a familiarity with industry-standard LM families. * Master's degree or PhD in Computer Science, Electrical Engineering, AI, Machine Learning, applied math or related field, with relevant industry experience, or outstanding previous achievements in this role. A Computer Science background is required as opposed to statistics or pure mathematics. We're an applied science group leaning towards deep learning and therefore software development proficiency is a prerequisite. * Excellent communication and teamwork skills. * Fluent in written and spoken English. Would be a plus: * Familiarity in coding for at-scale production, ranging from best practices to building back-end API services or stand-alone libraries. * Essential dev-ops skills (we use Docker, AWS EC2/Batch/Lambda). * Familiarity in building front-ends (LLMs or more standard React, Javascript, Flask) for simple demos, POCs and prototypes. * Experience with advanced prompting, fine-tuning or training an LLM, open-source or cloud, using industry accepted platforms (such as mosaic.ai or stochastic.ai). * Showcase previous work (e.g. via a website, presentation, open source code). ## Description We expect Senior Machine Learning Scientists to be versatile and have a well-balanced set of skills. You will focus on model training and maintenance with significant capacity for research (developing novel model architectures), dataset construction, and model hardening (preparing the model and code for production pipelines). Day-to-day, your responsibilities are to: * Work with subject matter experts and product owners to determine what questions should be asked and what questions can be answered. * Work with subject matter experts to curate, generate, and annotate data, and create optimal datasets following responsible data collection and model maintenance practices. * Answer questions and make trainable datasets from raw data, using efficient SQL queries and scripting languages, visualizing when necessary. * Develop and tune Machine Learning models, following best practices to select datasets, architectures, and model parameters. * Utilize, adopt, and fine-tune Language Models, including third-party LLMs (through prompt engineering and orchestration) and locally hosted LMs. * Stay current in the field - read research papers, experiment with new architectures and LLMs, and share your findings. * Optimize models for scaled production usage. * Communicate insights, as well as the behavior and limitations of models, to peers, subject matter experts, and product owners. * Write clean, efficient, and modular code, with automated tests and appropriate documentation. * Stay up to date with technology, make good technological choices, and be able to explain them to the organization. ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [WeAreDevelopers LIVE - Node and Package Security](https://www.wearedevelopers.com/videos/2138-wearedevelopers-live-node-and-package-security) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Inside the Mind of an LLM](https://www.wearedevelopers.com/videos/1617-inside-the-mind-of-an-llm) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Machine Learning for Software Developers (and Knitters)](https://www.wearedevelopers.com/videos/154-machine-learning-for-software-developers-and-knitters) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Tell if Something Was Written by ChatGPT](https://www.wearedevelopers.com/magazine/314-how-to-tell-if-something-was-written-by-chatgpt) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)