Description :

About Netscribes :

Netscribes is a global leader in data, insights, and digital solutions, helping the worlds largest organizations accelerate growth and innovation. As a growth catalyst, we empower sales, marketing, product development, and strategy through a unique blend of domain expertise and technological capabilities. Our end-to-end solutions span data engineering, advanced analytics, AI, and intelligent automationbuilt to scale and adapt to dynamic business environments. We partner with clients across the implementation journey, aligning with their ecosystem to deliver actionable intelligence, operational efficiency, and competitive advantage. For more information, visit www.netscribes.com.

LoB Overview :

Netscribes delivers integrated solutions across content, process, and technology to help global businesses scale efficiently and stay competitive in fast-moving markets.

Our services are structured across three key areas :

Content Solutions

We specialize in building, managing, and optimizing large-scale content ecosystems for global brands. Our expertise spans product data enrichment, taxonomy development, catalog and digital shelf management, content operations, and digital asset optimization.

These solutions help improve product discoverability, streamline content workflows, and enhance customer experience across digital platforms.

Process Solutions :

Our research and insights-driven services support core business processes across marketing, product, customer experience, and operations. This includes market and competitive research, campaign analysis, customer intelligence, and content performance tracking. Through Information Management Services (IMS) and managed service models, we embed scalable, high-quality support directly into client workflows, ensuring agility, consistency, and speed.

Technology Solutions :

Complementing our content and process offerings, we bring advanced technology capabilities through data engineering, data analytics, and AI. From building unified data platforms and real-time dashboards to deploying intelligent automation and machine learning models, we help organizations modernize operations and unlock data-driven decisions at scale.

Profile Description :

JOB DESCRIPTION :

Role : ML/AI & Databricks Specialist

Location : Bengaluru, India (Work From Office)

Shift : IST 9 :30 AM to 6 :30 PM

Experience : 3 - 4 Years

Employment Type Full-Time

About the Role :

We are looking for a skilled Databricks Engineer with a strong blend of classical Machine Learning & Agentic AI expertise on Databricks platform.

The ideal candidate will have 3 to 4 years of hands-on experience building end-to-end ML and data pipelines on Databricks, with deep familiarity with the latest Databricks AI/ML features including Mosaic AI, AgentBricks, Agentic AI frameworks, Foundation Models, and AI Functions.

Mandatory Skills :

- Python / PySpark strong proficiency in ML/AI workflows

- SQL / Spark SQL from fundamentals to complex transformations

- Databricks including :

1. Mosaic AI (model training, fine-tuning, and serving)

2. AgentBricks / Agentic AI (multi-agent frameworks, tool use)

3. Foundation Models & Model Serving endpoints

4. AI Functions (ai_query, ai_summarize, ai_classify, etc.)

5. Delta Lake, Unity Catalog

6. LLM integration and prompt engineering experience

- Classical ML feature engineering, model evaluation, MLflow

- Strong foundations of RAG Pipeline Building

Good to Have Skills :

- Vector databases (e.g., Pinecone, Weaviate, Databricks Vector Search)

- Azure DE Services : Synapse Analytics, Microsoft Fabric

- AWS DE Services : Glue, SageMaker

- LLM integration and prompt engineering experience

- Certifications : Databricks ML Associate/Professional or Gen AI Associate

Key Responsibilities :

ML & AI Engineering :

- Design, develop, and deploy end-to-end ML pipelines on Databricks using MLflow for experiment tracking, model registry, and deployment

- Build and fine-tune models using Mosaic AI; serve them via Databricks Model Serving endpoints

- Develop Agentic AI workflows using AgentBricks and multi-agent frameworks on Databricks

- Leverage Databricks Foundation Models and AI Functions (ai_query, ai_summarize, ai_classify) to embed intelligence directly in data pipelines

- Implement RAG pipelines using Databricks Vector Search and open-source LLM integrations

- Manage the full ML lifecycle : data prep, feature engineering, training, evaluation, deployment, and monitoring

Collaboration & Delivery :

- Work closely with senior engineers, data scientists, and business stakeholders to understand requirements

- Write clean, modular, reusable, and well-documented code in Python, PySpark, and SQL

- Provide regular updates on project status and proactively flag risks or blockers

- Participate in code reviews and contribute to best practices for ML/AI

Technical Expertise Area :

Technologies / Skills :

- Databricks AI/ML Mosaic AI, AgentBricks, Agentic AI, Foundation Models, AI Functions, Model Serving, Vector Search

- Classical ML Scikit-learn, XGBoost, MLflow, feature engineering, model evaluation, experiment tracking

- Engineering PySpark, Spark SQL, Unity Catalog

- Languages Python, SQL, PySpark

Good to Have : AI/BI Dashboards, Data Engineering experience

Other Requirements :

- 3 to 4 years of experience in ML/AI engineering roles on Databricks

- Demonstrated experience building production ML and data pipelines on Databricks

- Strong communication skills written and verbal; ability to articulate technical decisions clearly

- Strong problem-solving skills and attention to detail

- Ability to work independently and collaborate with cross-functional teams

- Must be available to work from our Bengaluru office, Monday to Friday, 9 :30 AM 6 :30 PM IST

Designation : Assistant Manager

Employment Type : Permanent

Work Mode : Hybrid

Working Days : 5 days (Sat-Sun week off)

Shift : Fixed Shift (9 hours)

Shift Timings : General Shift

Location : Bengaluru

Key Responsibilities :

ML & AI Engineering :

- Design, develop, and deploy end-to-end ML pipelines on Databricks using MLflow for experiment tracking, model registry, and deployment

- Build and fine-tune models using Mosaic AI; serve them via Databricks Model Serving endpoints

- Develop Agentic AI workflows using AgentBricks and multi-agent frameworks on Databricks

- Leverage Databricks Foundation Models and AI Functions (ai_query, ai_summarize, ai_classify) to embed intelligence directly in data pipelines

- Implement RAG pipelines using Databricks Vector Search and open-source LLM integrations

- Manage the full ML lifecycle : data prep, feature engineering, training, evaluation, deployment, and monitoring

Education : Graduates only (please ignore pursuing/drop out/12th or 10th pass)