Senior Data Engineer – Ml / Ai Platform

Job Description Where you’ll work: Remote / Bangalore

Engineering at GoTo We’re trailblazers in remote work technology—building powerful, flexible solutions that empower everyone to live their best life, both at work and beyond. With us, you’ll have the opportunity to chart new paths and help redefine how the world works. For us, AI isn’t just a buzzword; it’s a tool we use to deliver real, practical value to our customers and teams. We focus on solving meaningful problems, not just adding features for the sake of using AI. Here, growth takes many forms: you can expand your skills, take on new challenges, lead initiatives, and explore creative ideas. Join a GoTo product team and play a key role in transforming the workplace for millions of users worldwide—your work will truly make a difference.

Your Day to Day As a Senior Data Engineer – ML / AI Platform you would be:

• Design, build, and optimize scalable batch and near-real-time data pipelines using PySpark, SQL, Airflow, and Databricks/AWS services.
• Develop and maintain data models (conceptual, logical, physical) for structured and semi-structured datasets.
• Work with Delta Lake, Hive, and Lakehouse architectures to manage large-scale datasets efficiently.
• Implement data quality, governance, observability, and security best practices across pipelines.
• Participate in architecture discussions around scalability, reliability, and cost optimization.
• Mentor junior engineers and contribute to data platform and engineering best practices.
• Design, build, and deploy ML/AI solutions end-to-end for real SaaS use cases (e.g., recommendations, churn/retention, usage intelligence, anomaly detection, automation).
• Partner with external teams like product, sales, marketing etc to translate business problems into deployable ML solutions.
• Own ML productionization: feature pipelines, training/inference workflows, model packaging, deployment, and monitoring.
• Implement and maintain MLOps pipelines (model versioning, retraining strategies, performance tracking, and rollback mechanisms).
• Integrate models into data platforms and downstream applications with reliability and observability in mind.
• Apply pragmatic ML choices - prioritizing business impact, simplicity, and maintainability over complexity.
• Collaborate with platform and infra teams to optimize cost, scalability, and reliability of ML workloads.
• Mentor and technically guide engineers in building, deploying, and operating ML/AI solutions in production SaaS environments.

What We’re Looking For As a Senior Data Engineer, your background will look like

• 5+ years of experience in data engineering or backend engineering, with production ownership of large-scale data systems.
• Strong hands-on experience in PySpark and SQL for distributed data processing.
• Proven experience working with Databricks and/or AWS data stack (EMR, EKS, S3, etc.).
• Deep understanding of ETL/ELT design, data modeling, and performance optimization.
• Demonstrated experience building and deploying ML/AI solutions in production (beyond experimentation or POCs).
• Practical exposure to the ML lifecycle, including training, inference, monitoring, and retraining.
• Strong debugging, problem-solving skills, and sound engineering judgment in production environments.

Nice-to-have

• Background as a data engineer who has transitioned into ML/AI ownership.
• Hands-on experience owning MLOps pipelines for production ML systems, including deployment, monitoring, retraining, and rollback strategies.
• Experience building and maintaining feature engineering pipelines and serving features at scale.
• Familiarity with Unity Catalog or similar data governance frameworks.
• Experience with CI/CD pipelines for data and ML workflows.
• Exposure to streaming or near-real-time systems (Spark Streaming, Kinesis, Kafka).
• Experience collaborating cross-functionally teams like Product, Marketing, Sales (external) and Platform/Infrastructure teams (internal).
• Familiarity with AI-assisted development and data tools (e.g., LLM-based coding assistants, data exploration, documentation, or debugging tools) to improve engineering productivity.
• Experience or interest in applying AI/LLMs to internal platforms or data products (e.g., automation, intelligent insights, developer enablement, analytics acceleration).

What We Offer At GoTo, we believe in supporting our employees with a comprehensive range of benefits designed to fit your life—at work and beyond. Here are just some of the benefits and perks you can expect when you join our team:

• Comprehensive health benefits, life and disability insurance, and fertility and family-forming support program
• Generous paid time off, paid holidays, volunteer time off, and quarterly self-care days and no meeting days
• Tuition and reading reimbursement programs to support your continuous learning and professional growth
• Thrive Global Wellness Program, confidential Employee Assistance Program (EAP), as well as One to One Wellness Coaching
• Employee programs—including Employee Resource Groups (ERGs), GoTo Gives, and our charitable matching program—to amplify your connection and impact
• GoTo performance bonus program to celebrate your impact and contributions
• Monthly remote work stipend to support your home office expenses.

At GoTo, you’ll find the flexibility, resources, and support you need to thrive—at work, at home, and everywhere in between. You’ll work towards a shared goal with an open-minded, cohesive team that’s greater than the sum of its parts. We’re committed to creating an inclusive space for everyone, because we know unique perspectives make us a stronger company and community. Join us and be part of a company that invests in your future, where together we’ll Be Real, Think Big, Move Fast, Keep Growing, and stay Customer Obsessed .Learn more.