Company Description

Prakash Software Solutions Pvt. Ltd. is a technology and software engineering company that helps enterprises address complex business challenges with scalable, secure, and future-ready solutions. Founded in 2000, the company brings over 26 years of software engineering experience and a team of 250 engineers working across AI, Microsoft technologies, cloud, product engineering, and custom development.

Its AI capabilities span generative AI, AI agents, RAG, machine learning, computer vision, NLP, chatbots, AI assistants, predictive analytics, MLOps, and model development.

Prakash Software Solutions is a Microsoft Solutions Partner for Data & AI and Digital & App Innovation, ISO 9001 and ISO 27001 certified, and a partner of OpenAI and Anthropic Claude. Headquartered in Vadodara, India with multiple development centers, the company serves a global client base across the US, Europe, and Asia.

About the role

We're hiring an AI/ML Engineer to ship production AI on Databricks for enterprise clients. You'll take ML and GenAI use cases from notebook to governed, scalable production. You'll work with data scientists, ML scientists and solution architects, and directly with client teams. This role suits someone who loves hands-on engineering, client work, and keeping up with Databricks, MLOps and GenAI.

Experience

- 3 years as an ML engineer, data scientist or similar. At least 2 years hands-on with Databricks in real production projects.
- Data science foundation: Strong hands-on ML with pandas, scikit-learn and PyTorch. Solid on feature engineering, model selection, validation and avoiding leakage.
- Applied ML at scale: You've built or supported large consumer or enterprise ML systems — recommenders, ranking, forecasting or personalisation.
- Python and PySpark: You write production-quality Spark jobs, not just notebooks.
- MLOps: Hands-on with MLflow for tracking, model registry and serving. You've taken at least one model from notebook to production.
- GenAI and agents:



Practical delivery of RAG and agentic systems. Experience with LangChain, LangGraph or similar. Familiar with evaluation, monitoring and governance for agents.
- SQL and cloud: Solid SQL. Experience on Azure, AWS or GCP. Azure Databricks is a plus.
- Client-facing: Comfortable scoping and delivering work with clients and cross-functional teams, including direct client interviews.

Databricks experience is the deciding factor for this role, and it is the client's deciding factor too. Client interviews probe Databricks depth in detail, and profiles without genuine production Databricks experience do not progress.

Roles and Responsibilities

- Build ML pipelines.
- Build feature, training and serving pipelines for ML and GenAI.
- Use MLflow for experiment tracking, model registry and serving.
- Deliver GenAI and agents.
- Prepare data for RAG, integrate Databricks Vector Search, and build agentic assistants.
- Set up AI/BI tools such as Genie Spaces.
- Launch recent use cases.
- Take ideas from data prep to a working prototype, then to production.
- Partner with data scientists along the way.
- Build accelerators.
- Create reusable Databricks templates for RAG, agentic assistants, forecasting and personalisation.
- Cut time-to-delivery on new engagements.
- Evaluate and monitor.
- Set up evaluation, tracing and monitoring for models and agents.
- Track drift and quality in production.
- Optimise for scale.
- Tune jobs, clusters and workflows for cost, performance and reliability.
- Work with clients.
- Gather requirements, troubleshoot issues, and hand over documentation and runbooks.

Certifications

Strongly expected for this level: Databricks Machine Learning Professional or Generative AI Engineer Associate (Associate acceptable if paired with deep production experience).

Nice to have

Delta Lake and medallion architecture experience. Unity Catalog or similar governance and access-control tools. Consulting or professional-services experience in AI/ML delivery. A/B testing and experimentation pipelines on Databricks. Applied statistics or causal inference, such as uplift modelling or Double ML.

📌 Artificial Intelligence Engineer (Vadodara)
🏢 Prakash Software Solutions
📍 Vadodara