Job Overview
Location
New York City, New York, USA
Job Type
Full-time
Category
Machine Learning Engineer
Date Posted
February 25, 2026
Full Job Description
📋 Description
- • As the Founding Machine Learning Engineer at a high-growth AI cybersecurity company, you will be instrumental in defining and building the company's machine learning capabilities from the ground up. This pivotal role is central to the product vision, moving beyond incremental improvements to owning the overarching strategy, infrastructure, and execution of machine learning across the entire organization.
- • You will be the architect of the company's ML future, establishing the foundational elements necessary for success. This includes identifying key areas where machine learning can deliver maximum product value, designing robust end-to-end production systems, and setting the technical direction for the evolution of ML within the company.
- • This is a high-impact, highly autonomous position, ideal for an experienced individual who has a proven track record of building and deploying ML systems in production environments and is eager to architect an ML function from its inception to a scalable operation.
- • **Define the ML Strategy:** You will be responsible for charting the course for machine learning within the company. This involves identifying strategic applications of ML across existing and future products, determining the necessary infrastructure to support these applications, and making critical build vs. buy decisions for technology and tools.
- • **Design and Build Production ML Systems:** Take ownership of the end-to-end development of ML systems. This encompasses building sophisticated data pipelines for ingestion and processing, creating efficient model training workflows, establishing comprehensive evaluation frameworks to ensure model quality and detect regressions, and implementing scalable inference serving mechanisms for production deployment.
- • **Establish Rigorous Evaluation:** Develop and implement a robust methodology for evaluating ML model performance. This includes defining key metrics, setting up continuous monitoring, and creating processes to support data-driven iteration and improvement of models over time.
- • **Own the Data Strategy:** Play a crucial role in defining the company's data acquisition, management, and utilization strategy for ML. This involves identifying critical data requirements, overseeing data labeling processes, structuring effective feedback loops for continuous learning, and ensuring that models can be continuously improved based on real-world performance and new data.
- • **Collaborate Across Teams:** Work closely with product managers and backend engineers to seamlessly integrate ML capabilities into customer-facing systems and product features. This requires strong communication and collaboration skills to ensure ML solutions meet business needs and are technically feasible.
- • **Contribute to Codebase and Architecture:** Write production-quality code that adheres to high engineering standards, contributing directly to the existing codebase. You will also play a significant role in architectural decision-making, shaping the technical direction of the platform.
- • **Future Team Leadership:** As the ML function grows, you will have the opportunity to recruit, mentor, and lead a team of talented ML engineers, helping to build a world-class ML organization. This includes setting technical standards and fostering a culture of innovation and excellence.
- • **Impact and Growth:** This role offers a unique opportunity to make a foundational impact on a rapidly growing company at the forefront of AI cybersecurity. You will gain invaluable experience in building ML infrastructure from scratch, working with cutting-edge AI technologies, and contributing to solutions that protect enterprises from sophisticated AI-powered threats. The massive market opportunity and strategic backing provide a fertile ground for career acceleration and leadership development.
- • **Technical Ownership:** You will have significant autonomy and ownership, driving technical direction and executing on strategic initiatives without the constraints of established playbooks. This is a chance to build something truly impactful and define how ML shapes the future of cybersecurity.
🎯 Requirements
- • 8+ years of experience building and deploying machine learning systems in production environments.
- • Proven experience in establishing ML infrastructure from the ground up at an early-stage startup or serving as the senior/lead ML engineer in a growing company.
- • Strong software engineering fundamentals with hands-on production experience in languages such as Python, Java, or TypeScript.
- • Experience with cloud-based ML infrastructure platforms (e.g., AWS SageMaker, Azure ML, Google AI Platform, Modal, Baseten, or similar).
- • Hands-on experience with core ML and data processing frameworks (e.g., PyTorch, TensorFlow, Scikit-learn, Spark, or equivalent).
- • Demonstrated ability to mentor engineers and elevate technical standards within a team.
🏖️ Benefits
- • Competitive salary and equity options.
- • Comprehensive health, dental, and vision insurance.
- • 401k retirement savings plan.
- • Hybrid work flexibility.
Skills & Technologies
Python
TypeScript
Java
TensorFlow
PyTorch
Hybrid
About Pragmatike Soluciones Tecnológicas S.L.
Spanish technology firm founded in 2014, delivering custom software, mobile apps, cloud migration, and data analytics. Combines agile development, AI, and DevOps practices to serve finance, healthcare, retail, and public sectors across Europe and Latin America. Core services include UX/UI design, QA automation, and 24/7 managed support, with ISO 27001-certified processes and multilingual teams in Madrid, Barcelona, and remote hubs.
