Data and MLOps Engineer in InTune Analytics

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At InTune Analytics, we are building a next-generation data and ML platform to operationalize models across diverse environments. Our team collaborates to design scalable data pipelines, model deployment strategies, and automated monitoring to ensure reliable, production-ready ML workflows. You will contribute to the end-to-end lifecycle of models—from data ingestion and feature engineering to model serving, monitoring, and governance—driving measurable business impact through robust, cloud-native infrastructure.

Exclusive offer from getonbrd.com.

Key Responsibilities

Design, build, and maintain end-to-end ML pipelines and data infrastructure that scale across global teams and production workloads.
Operationalize models, including deployment, monitoring (drift detection, logging, alerting), and observability to ensure reliability and performance in production.
Collaborate with data engineers, software engineers, and product stakeholders to translate requirements into robust data and ML solutions.
Implement and optimize data models, feature stores, and model registries; manage data quality, lineage, and versioning.
Develop and maintain documentation, runbooks, and best practices for MLOps across the organization.
Participate in agile ceremonies, contribute to code reviews, and mentor junior teammates to raise the team’s technical bar.

What we're looking for

We seek a seasoned Data & MLOps Engineer with strong Python expertise and hands-on experience building, deploying, and maintaining machine learning pipelines in cloud environments. You should be comfortable working with cloud providers (AWS, GCP, Azure) and be adept at delivering scalable, reliable ML systems in globally distributed teams. You will work on data tooling (Python, dbt, Spark), SQL and relational databases, and data warehousing (e.g., Snowflake). You should value collaboration, clear communication, and ownership of outcomes, and be capable of operating in a fast, high-performing environment where curiosity and humor are welcome.

Nice-to-have qualifications

Experience with feature stores and model registries; monitoring and observability of ML systems (drift detection, logging, alerting); familiarity with ETL/ELT workflows (Dagster, Airflow); experience with OSS and cloud-native MLOps tooling; strong stakeholder management and ability to convey complex technical concepts to non-technical audiences.

What we offer

Join a collaborative, growth-oriented team at InTune Analytics. We offer competitive compensation, opportunities for continuous learning, flexible work arrangements, and a culture that values experimentation and well-being. If you’re excited by building scalable ML platforms and operating at the intersection of data, software, and AI, we’d love to hear from you.

GETONBRD Job ID: 56556

Fully remote You can work from anywhere in the world.

Remote work policy

Fully remote

Candidates can reside anywhere in the world.