Senior Software Engineer
Telangana, India
Role : ML Engineer (Associate / Senior)
Experience : 2-3 Years (Associate) 4-5 Years (Senior)6-12 Years
Mandatory Skill: Python/MLOps/Docker and Kubernetes/FastAPI or Flask/CICD/Jenkins/Spark/SQL/RDB/Cosmos/Kafka/ADLS/API/Databricks
Location: Bangalore
Notice Period: less than 60 Days
Job Description:
Other Skills: Azure/LLMOps/ADF/ETL
We are seeking a talented and passionate Machine Learning Engineer to join our team and play a pivotal role in developing and deploying cutting-edge machine learning solutions. You will work closely with other engineers and data scientists to bring machine learning models from proof-of-concept to production, ensuring they deliver real-world impact and solve critical business challenges.
- Collaborate with data scientists, model developers, software engineers, and other stakeholders to translate business needs into technical solutions.
- Experience of having deployed ML models to production
- Create high performance real-time inferencing APIs and batch inferencing pipelines to serve ML models to stakeholders.
- Integrate machine learning models seamlessly into existing production systems.
- Continuously monitor and evaluate model performance and retrain the models automatically or periodically
- Streamline existing ML pipelines to increase throughput.
- Identify and address security vulnerabilities in existing applications proactively.
- Design, develop, and implement machine learning models for preferably insurance related applications.
- Well versed with Azure ecosystem
- Knowledge of NLP and Generative AI techniques. Relevant experience will be a plus.
- Knowledge of machine learning algorithms and libraries (e.g., TensorFlow, PyTorch) will be a plus.
- Stay up-to-date on the latest advancements in machine learning and contribute to ongoing innovation within the team.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs Azure Databricks Docker ETL FastAPI Flask Generative AI Jenkins Kafka Kubernetes LLMOps Machine Learning ML models MLOps NLP Pipelines Python PyTorch Security Spark SQL TensorFlow
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