Slingshot

About the Company

At Slingshot, the baseline is; every single student, every single course material, by the first day of class, at an affordable price. Slingshot offers Equitable Access course material delivery models, and complementary services to help institutions operate a campus store, mailroom, or print operation. Whether institutions need software or people resources, they can tailor the solution to meet campus needs. Slingshot has offices and warehouses in Central Indiana and Las Vegas, NV. Learn more at slingshotedu.com.

Listed Jobs

Company Name

Slingshot

Job Title

ML Engineer

Job Description

**Job Title:** MLOps Engineer (Machine Learning Engineer) **Role Summary:** Develop and maintain end‑to‑end machine‑learning infrastructure for psychology‑focused foundation models. Ensure data pipelines, training workflows, and model serving operate reliably at scale, while integrating cutting‑edge research into production. Collaborate with cross‑functional teams to deliver high‑impact AI features quickly and efficiently. **Expectations:** - Deliver production‑ready ML solutions in a fast‑moving startup environment. - Write clean, typed Python code and contribute to broader product stack as needed. - Communicate complex ML concepts clearly to non‑technical stakeholders. - Prioritize pragmatic MVPs over extensive documentation when validating ideas. **Key Responsibilities:** - Build and maintain scalable training and evaluation pipelines across GPU clusters, ensuring data quality and reproducibility. - Design, implement, and automate evaluation systems for performance monitoring, regression detection, and benchmarking. - Develop, operate, and optimize infrastructure for model training and inference (reliability, throughput, cost). - Stay abreast of state‑of‑the‑art research; prototype and integrate novel techniques into production workflows. - Contribute to full stack integration of new models and tools, from prototype to deployment. **Required Skills:** - Proficiency with deep‑learning frameworks (PyTorch, TensorFlow, or JAX) in production settings. - Experience training and fine‑tuning large language models; strong knowledge of dataset pipelines and reproducible environments. - Solid software engineering fundamentals; comfortable with at least one non‑Python language (e.g., Kotlin, Java, C++). - Understanding of modern service architectures, distributed systems, and MLOps tooling (containerization, orchestration, monitoring). - Ability to explain ML/MLOps concepts to non‑technical audiences. - Familiarity with version control (Git), CI/CD, and cloud GPU resources. **Required Education & Certifications:** - Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or a related quantitative field (Master’s or Ph.D. preferred). - No specific certifications required; demonstrated expertise through projects or work experience is essential.

London, United kingdom

On site

16-01-2026