
Modelling and Data Science Manager
2 days ago
Job Description:
Experience - 7+ Years
Should have some Team management experience along with
a. ML Ops, model deployment etc.
b. On DS front, NLP, LLM, RAG with langchain
c. Databricks & any cloud
What are we looking for :
• Experience in Data Science, Machine Learning, Deep Learning and Gen AI.
• Design, Architect and Execute end to end Data Science pipelines which includes
Data extraction, data preprocessing, Feature engineering, Model building, tuning
and Deployment.
• Experience in leading a team and responsible for project delivery.
• Experience in Building end to end machine learning pipelines with expertise in
developing CI/CD pipelines using Azure Synapse pipelines, Databricks, Google
Vertex AI and AWS.
• Experience in developing advanced natural language processing (NLP) systems,
specializing in building RAG (Retrieval-Augmented Generation) models using
Langchain. Deploy RAG models to production.
Classification models, Regression models and Clustering Techniques.
• Maintaining GitHub repositories and cloud computing resources for effective and
efficient version control, development, testing and production.
• Developing proof-of-concept solutions and assisting in rolling these out to our
clients.
Required Skills & Qualifications:
• Hands-on experience with Azure Databricks, Azure ML, Azure Synapse, Azure
Blob Storage, and Azure Kubernetes Service (AKS).
• Experience with forecasting models, time series analysis, and predictive
analytics.
• Proficiency in Python (NumPy, Pandas, TensorFlow, PyTorch, Statsmodels, Scikitlearn, Hugging Face, FAISS).
• Experience with model deployment, API optimization, and serverless
architectures.
• Hands-on experience with Docker, Kubernetes, and MLflow for tracking and
scaling ML models.
• Expertise in optimizing time complexity, memory efficiency, and scalability of ML
models in a cloud environment.
• Experience with Langchain or equivalent and RAG and multi-agentic generation
Location:
DGS India - Mumbai - Thane Ashar IT ParkBrand:
MerkleTime Type:
Full timeContract Type:
Permanent-
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