MLOps Engineer / ML Platform Engineer

Location: [Remote / Gurgaon]

Experience: 3-7 years

Type: Full-time

About the Role:

We are looking for a passionate and skilled MLOps Engineer to design, implement, and manage scalable ML

infrastructure and pipelines.

You will work closely with Data Scientists, ML Engineers, and DevOps to ensure smooth experimentation,

model deployment, and lifecycle management using modern tools and cloud-native technologies.

Key Responsibilities:

- Design and implement CI/CD pipelines for ML workflows using GitHub Actions, Jenkins, or ArgoCD

- Build and manage containerized ML applications using Docker and deploy on Kubernetes

- Automate end-to-end ML pipelines using Kubeflow or similar workflow orchestration tools

- Track model lifecycle, parameters, and metrics using MLflow

- Collaborate with ML teams to enable reproducible and version-controlled training and deployment

- Implement monitoring, logging, and rollback mechanisms for ML models in production

- Optimize resource allocation and scaling using Kubernetes-native solutions

Must-Have Skills:

- 3+ years of experience in DevOps, MLOps, or cloud-native infrastructure roles

- Hands-on with Kubernetes and Docker for orchestration and deployment

- Proficient in building CI/CD pipelines (GitHub Actions, Jenkins, etc.)

- Strong understanding of MLflow for experiment tracking and model registry

- Experience with Kubeflow or similar ML workflow orchestration tools

- Knowledge of Python and shell scripting

- Familiarity with cloud platforms (AWS, GCP, or Azure)

Good to Have:

- Exposure to infrastructure-as-code (e.g., Terraform, Helm)

- Understanding of feature stores, model monitoring tools (e.g., Evidently, Prometheus)- Knowledge of data versioning tools (e.g., DVC)

What We Offer:

- Opportunity to build and scale cutting-edge ML infrastructure

- Collaborative and fast-paced environment

- Learning budget for certifications, conferences, and courses

- Remote-friendly and flexible work culture

Bern AI Lab

We’re a team of engineers, researchers, and builders obsessed with pushing the boundaries of what’s possible with AI. Whether it’s automating model lifecycle management or designing real-time inference systems, we operate at the intersection of machine learning, systems engineering, and modern DevOps.

If you're excited by clean abstractions, real-world scale, and working on problems no one has solved yet, we’d love to hear from you.

To Apply:

Apply over LinkedIn and send your resume and GitHub/portfolio to talent@bernailab.com