Senior Engineer, MLOps Platform

About the role

Entrupy is seeking a Senior ML-Ops Engineer to join our team responsible for our machine learning ops & infrastructure. This is an onsite role based out of our Bangalore office. This role will report to Ashwath, Director of Engineering

This role involves a mix of technical oversight, technical contribution, and operations work. In addition, this role will serve as a point of contact with various US-based and IN-based teams responsible for model delivery: annotation teams, infrastructure engineers, machine learning engineers, and products.

Some project areas this team is responsible for include:

• Infrastructure and libraries to define, deploy, run, and monitor training and inference jobs
• Providing interfaces and tooling for ML engineers to work with
• Job graph visualization and analytics
• Bringing research models and code to production
• Hybrid cloud server provisioning and automation
• Internal dashboards and annotation tools
• Contributing to best practices and methodology guidelines for data science teams
• Platform advocacy, training, and mentoring

Location: Bangalore, India. Hybrid

What You'll Do:

• Work with engineering leads to define and build new features and subsystems for our machine learning platform.
• Build interfaces and tools for researchers, engineers, and data teams.
• Help bring research algorithms into production and scale them alongside their products.
• Develop and maintain automated testing and contribute to integration testing and rollouts.
• Assist research and product teams in the use of the platform.
• Stay in regular communication with research and product teams to understand how the platform can best assist in other teams' objectives.
• Participate in code review and contribute to Entrupy's technical standards.
• Mentor junior developers & researchers.
• Manage annotation work from first and third-party annotation teams as required.
• Collaborate with infrastructure teams to provision services and establish deployment workflows.

Who you are:

• Experience with data pipelines, job schedulers or applied machine learning systems.
• Experience with architecting, implementing, deploying, and monitoring backend systems.
• Prior history in deploying, maintaining, and monitoring machine learning models in production environments, with a focus on model lifecycle management (retraining, versioning, etc.).
• Strong proficiency with Python.
• Experience maintaining infrastructure on AWS or other cloud services.
• Experience with reviewing code/pull requests from junior developers.
• At least 5+ years of software development experience.

Good to have

• Experience with cloud automation and DevOps tools (logging, CI, GitHub Actions and Shell Scripting etc).
• Experience with low-latency services and performance-sensitive code.
• Familiarity with Anyscale for scalable and distributed machine learning workloads is a plus.
• Experience with data visualization or analytics (Eg: Tableau).
• Experience with tools like AWSCloudFormation or Terraform is a plus.
• Experience with orchestration frameworks (Airflow)
• Experience with Experiment Tracking and model versioning (Weights and Biases, MLFlow)
• Experience with Model monitoring and alerting (Grafana, Prometheus, Data Dog)
• Previously worked in a startup-like environment.

What we offer

• Market competitive and pay equity-focused compensation structure
• Hybrid with Flexible work from anywhere for 4 weeks per year
• Generous time away including company holidays, paid time off, sick time, parental leave, and more!
• Rich medical benefits and insurance coverage
• Opportunity to be part of core team in a growing setup.
  

We have had an incredible run so far and laying the foundation for a culture that is fast-paced, entrepreneurial, and rooted in passion, kindness, and positivity. We live by these values – we hire by them, promote them, and celebrate them every day.

Please apply if you're a coding ninja with a passion for cutting-edge technology and want to be at the forefront of AI innovation.