Data Infrastructure Engineer (ML Workflows & Analytics) - Contract at Jobgether. This position is posted by Jobgether on behalf of a partner company. We are currently looking for a . Data Infrastructure Engineer (ML Workflows & Analytics). in . India. .. This role offers an exciting opportunity to work at the intersection of data engineering, machine learning, and analytics. You will manage and visualize large-scale datasets, develop internal dashboards, and automate workflows to provide actionable insights across ML pipelines. The position allows you to collaborate with ML engineers and developers to build intuitive tools that optimize performance, enhance data quality, and streamline annotation workflows. Ideal candidates are independent, fast-moving, and thrive in a startup-like, agile environment. You will be responsible for designing, implementing, and maintaining Python-based analytics and automation tools that have a direct impact on internal processes and ML operations. This is a hands-on role suited for engineers passionate about ML infrastructure, data visualization, and workflow optimization.. . Accountabilities. Build internal dashboards to track ML metrics, contributor performance, and data quality.. Develop lightweight visualization tools and custom reporting APIs.. Write clean, maintainable Python code to support analytics, automation, and workflow optimization.. Design human-in-the-loop (HITL) annotation feedback workflows.. Collaborate on prompt engineering and LLM-assisted tooling to improve developer efficiency.. Partner with engineers and ML teams to create internal tools for enhanced data insights and operational transparency.. . 3+ years of professional experience coding in Python.. Experience building data visualizations through custom dashboards, APIs, or visualization frameworks.. Solid understanding of ML pipeline structures and metric tracking.. Familiarity with LLMs and prompt engineering concepts.. Ability to work autonomously in a remote and agile environment.. Strong problem-solving skills and attention to detail.. Preferred/“Nice to Have” Skills:. Experience with workflow orchestration tools like Airflow.. Exposure to Google Cloud Platform (GCP) or cloud-based ML environments.. Experience working with large-scale, video-based datasets.. Prior experience integrating LLMs into developer workflows or internal analytics tools.. Knowledge of building developer platforms, analytics layers, or feedback systems.. . Company Location: India.
Data Infrastructure Engineer (ML Workflows & Analytics) - Contract at Jobgether