Job Description :

Machine Learning Engineer

Location : Mumbai (Andheri East), India (In-Office)

Experience : 3+ Years

About Skima Innovation :

At Skima, we don't just build models; we build the future. We are a dynamic team dedicated to pushing the boundaries of what's possible through data-driven innovation. We are looking for a talented Machine Learning Engineer who is ready to take ownership of end-to-end ML lifecycles and transform complex data into scalable, real-world solutions.

The Role :

As an ML Engineer at Skima, you will sit at the intersection of data science and software engineering. You won't just be "playing with data" - you will be designing, developing, and deploying high-performance models that drive our core products. You will work in a collaborative environment where your algorithms directly impact business outcomes.

Key Responsibilities :

- Production Pipelines: Architect and manage automated ML implementation pipelines for seamless transition from research to production.

- Deep Learning Deployment: Optimize and deploy large-scale Deep Learning models using specialized inference engines.

- Containerization & Orchestration: Package ML services using Docker and manage deployments via Kubernetes to ensure high availability and scalability.

- MLOps Mastery: Establish CI/CD for ML, implementing automated testing, versioning (DVC), and model registry workflows.

- Model Observability: Implement comprehensive monitoring for model drift, data integrity, and real-time performance latency.

- Optimization: Fine-tune models for resource efficiency, focusing on quantization and pruning for production-grade inference.

What You Bring :

- Experience: 3+ years of hands-on experience in ML engineering with a focus on production-grade deployments.

- MLOps Stack: Proficiency with tools like MLflow, Kubeflow, W&B for managing the model lifecycle.

- Cloud & Infrastructure: Strong experience with AWS/Azure/GCP ML services and containerized environments.

- Technical Depth: Expert-level Python and deep familiarity with PyTorch or TensorFlow.