Senior Machine Learning Engineer

Where you’ll work: Bangalore, KA, IN 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.     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 ML Engineer - you would be: Build and maintain scalable batch and near real-time data pipelines using PySpark, SQL, Airflow, Databricks, and AWS services   Work with structured and semi-structured datasets using modern lakehouse/data platform architectures   Ensure data quality, reliability, observability, and operational stability across pipelines   Design and operate production ML systems for use cases such as recommendations, churn prediction, anomaly detection, and usage intelligence   Work across the ML lifecycle including:   feature engineering   model training and evaluation   batch / real-time inference   monitoring and retraining   Build and maintain practical MLOps workflows including deployment, model versioning, monitoring, and rollback strategies   Partner with Product, Marketing, Sales, Platform, and Engineering teams to translate business problems into scalable ML solutions   Contribute to architecture discussions around scalability, performance, reliability, and cost optimization   Mentor engineers and contribute to engineering best practices  What We’re Looking For As a Senior ML Engineer, your background will look like 5+ years of experience in data engineering, ML engineering, or backend engineering with exposure to production systems   Hands-on experience with PySpark and SQL for large-scale data processing   Experience working with Databricks and/or AWS data stack (EMR, EKS, S3, Glue, etc.)   Good practical understanding of data pipelines, ETL/ELT workflows, and distributed processing systems   Hands-on experience building and deploying ML systems for real business problems (not just POCs or experimentation)   Exposure across the ML lifecycle including feature engineering, training, inference, monitoring, and retraining workflows   Practical exposure to MLOps concepts such as deployment pipelines, model versioning, monitoring, and production debugging   Strong debugging and problem-solving skills in production environments   Ability to work across data pipelines, ML systems, and production workflows with strong ownership. Nice-to-have Experience building  feature pipelines or feature stores    Exposure to  streaming systems  (Kafka, Spark Streaming, Kinesis)   Experience with  CI/CD pipelines  for data and ML workflows   Familiarity with  data governance frameworks  (e.g., Unity Catalog)   Exposure to  AI/LLM-based systems (RAG, etc.)  as an extension (not primary focus) Core Hiring Principle   We are NOT hiring a pure Data Engineer or pure Data Scientist   We are hiring someone who can  build and own ML systems in production   What Success Looks Like   Building reliable ML pipelines and systems   Operating ML workflows in production   Collaborating across data, product, and engineering teams   Taking practical engineering decisions with strong ownership.  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