Data Infrastructure Engineer (ML Workflows & Analytics) - Contract at Jobgether

, , India -

Full Time

Start Date

Immediate

Expiry Date

27 Jan, 26

Salary

0.0

Posted On

29 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Machine Learning, Analytics, Python, Data Visualization, Workflow Optimization, ML Pipelines, APIs, LLMs, Prompt Engineering, Problem-Solving, Attention to Detail, Cloud Computing, Airflow, Video Datasets, Developer Platforms

Industry

Internet Marketplace Platforms

Description

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. Competitive hourly rate, commensurate with experience. Fully remote work with flexible schedule. Short-term contract with potential for renewal or transition to long-term engagement based on performance. Opportunity to work in a fast-moving, collaborative, and innovative environment. Exposure to advanced ML workflows, AI tools, and data visualization projects. Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. 🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. 📊 It compares your profile to the job’s core requirements and past success factors to determine your match score. 🎯 Based on this analysis, we automatically shortlist the three candidates with the highest match to the role. 🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team. Thank you for your interest! #LI-CL1

Responsibilities

You will manage and visualize large-scale datasets, develop internal dashboards, and automate workflows to provide actionable insights across ML pipelines. This role involves collaborating with ML engineers and developers to build tools that optimize performance and enhance data quality.