Join a high-impact AI and Data Engineering team building scalable, cloud-native machine learning solutions that power enterprise analytics, intelligent automation, and next-generation AI applications. You'll work on designing and deploying production-grade ML systems, implementing MLOps best practices, and developing cutting-edge Generative AI solutions for enterprise customers.
This is an opportunity to work on real-world AI challenges, leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and cloud-native data platforms to drive business innovation.
Key Responsibilities
- Design, develop, and deploy scalable machine learning solutions for enterprise customers.
- Build and productionize ML workloads using MLOps best practices across multiple business domains.
- Develop Generative AI applications using Large Language Models (LLMs), including:
- Retrieval-Augmented Generation (RAG) solutions on enterprise knowledge repositories.
- Natural language querying over structured and unstructured data.
- AI-powered content generation and intelligent assistants.
- Collaborate with data engineering and business teams to design robust AI and ML architectures.
- Build, monitor, and optimize production ML pipelines, including model performance and drift monitoring.
- Provide technical guidance on machine learning architecture, tooling, and industry best practices.
- Work with large-scale distributed data processing platforms to build efficient and scalable ML solutions.
Required Skills & Qualifications
- 4–6 years of experience for
Senior Machine Learning Engineer
or 6+ years for
ML Architect
.
- Robust programming experience in Python.
- Hands-on experience with machine learning libraries such as:
- Pandas
- Scikit-learn
- MLflow
- TensorFlow and/or PyTorch
- Gensim
- NLTK
- Experience deploying and managing production-grade machine learning systems.
- Strong understanding of MLOps, incl
📌 Machine Learning Engineer(Databricks+MlOps (India)
🏢 Recro
📍 India
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