As we continue to build...
We’re seeking curious, growth minded thinkers to help shape our vision, structures and systems; playing a key-role as we launch into our ambitious future. If you’re invigorated by our mission, values, and drive to change the world — we’d love to have you apply.
About the role
Entrupy is seeking a ML-Ops Engineer to join our growing team supporting machine learning infrastructure and operations. This is a great opportunity for someone early in their ML-Ops or data engineering career who is excited to work on real-world AI products and wants to grow their experience in deploying and managing machine learning systems in production.
As part of this role, you'll collaborate with experienced engineers, data scientists, and product teams to help streamline ML workflows—from model training and evaluation to deployment and monitoring.
Location: Bangalore, India (Hybrid)
Reports To: VP of Engineering
This role involves a mix of 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
What You'll Do:
- Collaborate with engineering leads to define and implement new features and subsystems for our machine learning platform.
- Build interfaces and tools for ML researchers, engineers, and data teams.
- Operationalize research models — bringing them from prototype to production and scaling them effectively.
- Design, build, and maintain data and training pipelines, job orchestration systems, and monitoring setups.
- 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 ML research and product teams to understand how the platform can best assist in other teams' objectives.
- Collaborate with infrastructure teams for provisioning, deployment workflows, and automation.
Who you are:
- 3-5 years of experience working in ML-Ops, data engineering, backend development, or DevOps.
- Exposure to deploying or maintaining ML models in real-world applications (internships or full-time roles).
Experience writing Python scripts and familiarity with software engineering best practices (e.g., version control, testing). - Comfortable working with cloud platforms (AWS preferred) or containerized environments like Docker.
- Curious, proactive, and eager to learn from more experienced team members.
Good to have
- Experience with job schedulers or orchestration tools (e.g., Airflow).
- Familiarity with model monitoring tools (e.g., Prometheus, Grafana).
- Exposure to experiment tracking tools like MLflow or Weights & Biases.
- Interest or experience in working with automation and infrastructure-as-code tools (e.g., Terraform).
- Prior experience in startup or cross-functional team environments.
- Familiarity with Anyscale Ray for scalable machine learning workloads is a plus.
What we offer
- Market competitive and pay equity-focused compensation structure
- 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 the diverse and growing team across Japan, US, India, and Brazil.
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 want to be a part of a collaborative and dynamic team with a passion for working with high-end luxury brands and cutting-edge technology and want to be at the forefront of AI innovation.
Entrupy embraces a diversity of backgrounds and experiences and provides equal opportunity for all applicants and employees. We are dedicated to building a company that represents a variety of backgrounds, perspectives, and skills. We believe that the more inclusive we are, the better our work (and work environment) will be for everyone.
Skills Required
- 3-5 years of experience in ML-Ops, data engineering, backend development, or DevOps
- Exposure to deploying or maintaining ML models in real-world/production applications
- Experience writing Python scripts and familiarity with software engineering best practices (version control, testing)
- Experience with containerized environments like Docker
- Comfortable working with cloud platforms (AWS preferred)
- Ability to collaborate with cross-functional teams and serve as point of contact for ML delivery
- Experience with job schedulers/orchestration tools (e.g., Airflow)
- Familiarity with model monitoring tools (e.g., Prometheus, Grafana)
- Exposure to experiment tracking tools (e.g., MLflow, Weights & Biases)
- Interest or experience with infrastructure-as-code and automation (e.g., Terraform)
- Familiarity with Anyscale Ray for scalable ML workloads
- Prior startup or cross-functional team experience
What We Do
Entrupy is the only company using artificial intelligence to instantly authenticate luxury handbags and accessories. Our mission is to become the Verisign of physical goods to attack the $1.7 trillion sales of counterfeit goods globally. Entrupy’s authentication service uses patented computer vision algorithms and microscopy to bring trust to transactions of high-value physical goods. Currently in use by hundreds of secondary resellers and marketplaces worldwide, Entrupy provides the only independent, scalable technology capable of objectively authenticating luxury products.
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