Staff ML Ops Engineer: Aviso is the end-to-end AI-powered Revenue Operating System that helps GTM teams deliver 98 %+ accurate forecasts, predict future pipeline, and help sellers deliver more value. Customers run their business their way on Aviso, which doesn’t require them to change their internal processes based on their CRM.
Leaders such as Honeywell, New Relic, Armis, GitHub, and RingCentral have standardized on Aviso to manage revenue teams, gaining over 55% net new revenue per rep, 40% higher win rates, 160% higher pipeline conversion rates, and over 31% faster sales cycles.
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Table of Contents
Aviso is an all-in-one revenue intelligence and operations platform and an AI single pane of glass for modern GTM teams.
Job Title: Staff ML Ops Engineer
Location: India
Job Type: Full Time
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About the job
About Aviso
At Aviso, we’re transforming revenue intelligence through advanced machine learning and AI. Our platform helps sales organizations optimize their revenue operations with accurate forecasting, insightful deal analytics, and data-driven recommendations.
We’re looking for experienced MLOps Engineers to help scale our AWS-based machine learning infrastructure and operations.
Position Overview
As a Staff MLOps Engineer on the Revenue Intelligence team, you’ll lead the design and implementation of our ML production infrastructure on AWS. You’ll work closely with data scientists and software engineers to build robust pipelines for model training, deployment, and monitoring using Kubeflow within our AWS environment. Your expertise will directly impact the scalability, reliability, and performance of our ML systems.
Key Responsibilities
- Design, build, and maintain scalable ML infrastructure on AWS for model training, deployment, and monitoring
- Lead the development of CI/CD pipelines for ML workflows using Kubeflow and AWS services
- Implement robust monitoring, logging, and alerting for production ML systems
- Architect and implement data pipelines that efficiently handle large-scale data processing
- Collaborate with data scientists to optimize model training and inference workflows
- Define and implement best practices for model versioning, A/B testing, and gradual deployments
- Drive infrastructure automation initiatives to improve operational efficiency
- Mentor junior team members on MLOps best practices and AWS architecture
Requirements
- 8+ years of experience in software engineering or DevOps roles
- 5+ years of hands-on experience with AWS services (EKS, ECR, S3, Lambda, Step Functions, etc.)
- Strong experience with Kubernetes and container orchestration, particularly Kubeflow
- Proficiency in infrastructure-as-code using Terraform, CloudFormation, or equivalent
- Experience implementing and operating CI/CD pipelines for ML workloads
- Staff ML Ops Engineer Strong programming skills in Python and shell scripting
- Experience with monitoring tools and observability practices for production systems
- Understanding of ML lifecycle and familiarity with common ML frameworks
- Experience with distributed systems and data processing at scale
- Strong communication skills and ability to collaborate effectively with cross-functional teams
Preferred Qualifications
- Experience mentoring junior engineers and technical leadership
- Experience with revenue forecasting, classification, or clustering models in production
- AWS Professional certifications (DevOps, Solutions Architect, etc.)
- Staff ML Ops Engineer Experience with stream processing frameworks (Kafka, Kinesis)
- Familiarity with feature stores and ML metadata tracking
How to Apply:
Please submit your resume and cover letter through Submit Resume to apply for this position.
Apply Here
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Job Search FAQs
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Q: What skills are required for the Staff ML Ops Engineer role?
A: Expertise in Kubernetes, CI/CD pipelines, TensorFlow/PyTorch, and cloud platforms (AWS/GCP/Azure).
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Q: Is this a fully remote position?
A: Yes! This role offers full remote flexibility with competitive compensation (8-20 LPA).
