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Machine Learning Engineer
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- Posted 19 days ago
- Be among the first 10 applicants
Job Description
Role: MLOps Engineer
Experience: 6–10 Years
Location: Chennai, Bangalore, Hyderabad, Pune, Mumbai
Notice Period: Immediate Joiners
Required Skills
- Strong experience in MLOps, Machine Learning, and AI/ML lifecycle management
- Hands-on experience with Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
- Expertise in ML model deployment, monitoring, and automation
- Experience with MLflow, Kubeflow, Airflow, or similar MLOps platforms
- Strong knowledge of Docker, Kubernetes, and CI/CD pipelines
- Experience with Cloud Platforms (AWS, Azure, or GCP)
- Knowledge of model versioning, feature stores, and model registries
- Experience with Git, DevOps practices, and Infrastructure as Code
More Info
Key Skills
Infrastructure as Code
model versioning
MLflow
Kubeflow
model registries
feature stores
DevOps practices
Scikit-learn
CI CD pipelines
ML model deployment
About Company
Skills:
Docker, Pyspark, Pytest, Azure Databricks, Azure Cloud Services, Python, Sql, MLflow
Skills:
Java, Machine Learning, Distributed Systems, Hadoop, Statistical Modelling, Sql, API Design, MLops, Spark, Python, Scalable Architectures, Large-scale Data Systems, Go, Optimisation Techniques, Scientific Computing
Skills:
Spark, Java, Hadoop, Cloudformation, Yarn, Tensorflow, Hive, MLops, Docker, Sns, Python, Kubernetes, AWS, Airflow, Pipelines, H2O, EventBridge, CodeBuild, SageMaker, CodePipeline, CodeCommit, CloudTrail
Skills:
Prometheus, Gpu, Grafana, Pytorch, Docker, Python, Linux, Kubernetes, embeddings, ML Engineering, tool calling, Hugging Face, LLM Inference, SGLang, LangSmith, Langfuse, RAG LangGraph, quantization, Observability, TensorRT-LLM, KV Cache, vLLM, Agentic AI, TGI, LoRA, RAG, W B, LlamaIndex, QLoRA, AI Infrastructure
Skills:
AWS, Apis, integrating ML models into production systems, automated testing of model performance and stability, model evaluation techniques, feature engineering, data preprocessing, MLOps tools and frameworks