DevOps Engineer

Posted 7 Days Ago
Be an Early Applicant
India
Senior level
3D Printing • Software
The Role
The MLOps Engineer will design and implement MLOps and DevOps solutions, optimize performance of ML applications, develop CI/CD pipelines for Generative AI integrations, and lead technical initiatives within the team while mentoring junior staff.
Summary Generated by Built In

Description

Imagine.io’s mission is to make 3D simple for everyone. We believe that simplicity in 3D visualization is critical for creating engaging visual content at scale. To go beyond the traditional 2D-3D canvas and create contextual, photo-realistic, and interactive experiences with ease and simplicity will come from vision and creativity. We are working to scale our 3D technology with generative AI models and easy-to-adopt UX, so brands, retailers, and individuals are empowered to generate visual content using 3D.

Imagine.io is financially backed by top VC firms.

Our Product Video - 

To learn more, log onto our website- 

Job Summary:

Imagine.io is seeking an experienced Senior DevOps Engineer to join our dynamic team and play a pivotal role in advancing our AI-driven solutions. As an Experienced Senior DevOps Engineer, you will lead the design and implementation of cutting-edge MLOps and DevOps solutions, leveraging your extensive expertise to optimize performance, scalability, and reliability. You'll collaborate closely with multidisciplinary teams to develop end-to-end CI/CD pipelines tailored for machine learning workflows and help in defining and setting development, testing, release, update, and support processes for DevOps and MLOps operations to establishing best practices for model versioning, monitoring, and governance.

Designation: DevOps Engineer

Job Location: Delhi (Hybrid/Remote)

Job Type: Full-Time

Start Date: ASAP

Responsibilities:

  • Lead the design and implementation of DevOps and MLOps solutions to enhance our platform's capabilities.
  • Defining and setting development, testing, release, update, and support processes for DevOps and MLOps operations.
  • Deployment of diffusion models, LLM Models, and Cost-effective deployment of Generative AI products.
  • Collaborate closely with data scientists, machine learning engineers, and product developers to integrate Generative AI models into our existing infrastructure seamlessly.
  • Develop and implement end-to-end CI/CD pipelines specifically tailored for Generative AI model workflows to ensure reliable and automated model deployment.
  • Optimize and fine-tune infrastructure services, including PaaS and IaaS, to maximize performance, scalability, and cost efficiency for machine learning applications.
  • Stay updated with the latest advancements in MLOps tools, techniques, and industry trends to drive innovation and continuously improve our MLOps practices.
  • Provide technical leadership and mentorship to junior team members to foster a culture of continuous learning and growth within the MLOps and DevOps team.
Requirements
  • 3+ years of total experience in DevOps with relevant experience in implementing MLOps solutions.
  • Must have experience with Google Cloud, with hands-on experience deploying machine learning models in production environments.
  • Experienced in the scalable and cost-effective deployment of machine learning models and other modules.
  • Extensive experience with containerization technologies like Docker and orchestration tools like Kubernetes for managing workloads at scale.
  • Proficiency in Infrastructure as code (IaC) for automating the provisioning and configuration of cloud resources.
  • Experience with DevOps practices and tools, including CI/CD pipelines, version control systems, and automated testing frameworks.
  • Excellent problem-solving skills and the ability to troubleshoot and debug complex MLOps workflows.

Good to have:

  • Experienced in deployment of diffusion models, LLM Models, and Generative AI products
  • Certifications in cloud platforms, such as AWS and Google Cloud.
  • Experience with MLOps tools and frameworks, such as Kubeflow, MLflow, or TFX, for managing the end-to-end machine learning lifecycle.
  • Knowledge of data engineering principles and techniques for building scalable and reliable data pipelines.
  • Familiarity with software development methodologies, such as Agile or Scrum, for iterative and collaborative project management.
Benefits
  • Build products from scratch and be part of decision making.
  • Freedom to explore and implement your own ideas
  • Hybrid Work Mode
  • Open culture with flexible timings
  • Work with a Team who is a Family

Top Skills

GCP
The Company
HQ: Winston-Salem, Carolina
111 Employees
On-site Workplace
Year Founded: 2016

What We Do

imagine.io is B2B SaaS startup that has created an easy-to-use 3D content creation platform that empowers furniture, home furnishing accessories, textile manufacturers, and more to create stunning photo realistic 3D content without any engineering or 3D design background. Our cutting-edge real-time 3D graphics technology is built by a team of 3D experts with cloud-based rendering technology all wrapped into an easy-to-use web interface. We help customers create 3D images in minutes instead of hours or days compared to studio photography at a fraction of the cost. Our 3D content is proven to drastically save time and money while dramatically improving sales and profits.

You can think of us as Canva for 3D.

-Save 70% of the costs and 80% of the time creating product images
-Get a massive lift on Ecommerce conversion rates from 55% to over 500%
-Create prototypes faster and get pre-orders before manufacturing
-Produce the highest-quality photorealistic 3D images, videos, virtual showrooms, and augmented reality experiences

Trusted by over 130+ leading manufacturers and retailers.

“We saw product views increase an average of 62% and as high as 350%, leading to an average sales increase of 46% for items using imagine.io 3D images.” - Justin Bowen, eCommerce Manager, The Great American Home Store

imagine.io is a venture-backed startup that has raised a total of $7.5M from the top investors in the United States - Venture South, Launch, CEAS Investments, Mercato Partners, and Parkwest LLC.

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