Machine Learning Engineer (Data Infrastructure)

Machine Learning Engineer (classification, detection, clustering, time-series)

Our client is developing a next-generation distributed infrastructure that turns idle digital resources into real-time, high-throughput data streams for AI and large-scale analytics. Supported by leading investors and seasoned founders, the company has gained significant traction with a large user base, maintains a high-performance, ownership-driven culture, and operates across multiple international hubs. They are assembling a team of exceptional professionals to drive their next phase of growth.

Role Requirement

We’re searching for a skilled Machine Learning Engineer to help our client scale their next-generation multimodal data infrastructure. This hands-on role combines system-level design with technical execution, ensuring pipelines that process audio, video, text, and image data are robust, scalable, and production-ready. The Machine Learning Engineer will work closely with internal teams and external stakeholders to transform complex data into actionable intelligence, while leading end-to-end ML projects from initial design through deployment, delivering high-impact solutions across diverse B2B use cases.

Responsibilities

• Develop, train, and fine-tune classical machine learning models across diverse multimodal datasets, including audio, video, text, and images.
• Build and maintain reliable pipelines for model evaluation, testing, and performance monitoring.
• Develop and operate scalable ETL/ETN workflows to continuously ingest, process, and clean datasets at petabyte scale.
• Uphold data integrity, reproducibility, and regulatory compliance, including GDPR and CCPA standards.
• Support the company’s B2B initiatives by addressing client-specific use cases and, at times, leading projects end-to-end in partnership with the sales team.
• Design, deploy, and manage Fast API-based microservices for delivering ML models and datasets in production environments.
• Ensure seamless and secure integration with internal platforms and external client systems.
• Partner with senior Data Scientists to improve methodologies, validate model outputs, and speed up knowledge transfer.
• Coordinate with full-stack engineers and DevOps teams to deliver robust, high-performance ML solutions.
• Research and experiment with novel algorithms and multimodal methods, evaluating and implementing leading open-source solutions.

Qualifications

• Minimum of 3 years’ experience as a Machine Learning Engineer or Data Scientist, specializing in core ML methods such as classification, clustering, detection, and time-series analysis
• Practical expertise in applying ML to audio, video, text/NLP, and image data, with direct multimodal experience considered a significant advantage
• Advanced Python programming skills with experience developing robust production backends using Fast API
• Demonstrated experience in designing and managing ETL/ETN pipelines for large-scale data ingestion and processing
• Knowledge of JavaScript/TypeScript or openness to learning, enhancing opportunities for cross-stack collaboration
• Enthusiasm for collaborating closely with a senior Data Scientist to develop and implement advanced, cutting-edge solutions
• Highly curious and data-driven, with a passion for building solutions
• Comfortable taking end-to-end ownership of projects, from initial concept and design to full production deployment
• Motivated to drive impact through hands-on execution and problem-solving

This is a unique opportunity to contribute to the development of a next-generation multimodal data infrastructure at a fast-growing, high-impact company backed by leading investors.

Salary: Highly competitive, in line with experience and market standards.

To apply, please submit your CV via the link.

For additional information about open vacancies and events we are attending, please feel free to follow our LinkedIn Page.