Applied Machine Learning Scientist

Job Title :

ML Ops Engineer / ML Engineer

Experience - 5Yrs -20 Yrs

Location - Chennai / Bangalore / Hyderabad / Pune / Noida / Mumbai /

Job Overview :

We are looking for an experienced MLOps Engineer to help deploy, scale, and manage machine learning models in production environments. You will work closely with data scientists and engineering teams to automate the machine learning lifecycle, optimize model performance, and ensure smooth integration with data pipelines.

Key Responsibilities :

Transform prototypes into production-grade models

• Assist in building and maintaining machine learning pipelines and infrastructure across cloud platforms such as AWS, Azure, and GCP.
• Develop REST APIs or FastAPI services for model serving, enabling real-time predictions and integration with other applications.
• Collaborate with data scientists to design and develop drift detection and accuracy measurements for live models deployed.
• Collaborate with data governance and technical teams to ensure compliance with engineering standards.

Maintain models in production

Contribute to AI platform and engineering practices

Minimum Required Skills :

Tools and Technologies :

Model Development & Tracking : TensorFlow, PyTorch, scikit-learn, MLflow, Weights & Biases

Model Packaging & Serving : Docker, Kubernetes, FastAPI, Flask, ONNX, TorchScript

CI / CD & Pipelines : GitHub Actions, GitLab CI, Jenkins, ZenML, Kubeflow Pipelines, Metaflow

Infrastructure & Orchestration : Terraform, Ansible, Apache Airflow, Prefect

Cloud & Deployment : AWS, GCP, Azure, Serverless (Lambda, Cloud Functions)

Monitoring & Logging : Prometheus, Grafana, ELK Stack, WhyLabs, Evidently AI, Arize

Testing & Validation : Pytest, unittest, Pydantic, Great Expectations

Feature Store & Data Handling : Feast, Tecton, Hopsworks, Pandas, Spark, Dask

Message Brokers & Data Streams : Kafka, Redis Streams

Vector DB & LLM Integrations (optional) : Pinecone, FAISS, Weaviate, LangChain, LlamaIndex, PromptLayer