ML Ops / Gen AI Engineer

Company Description

DataZymes is revolutionizing the pharma industry with data-driven digital products that address the inefficiencies of traditional consulting and technology solutions. Focused on creating the best user experiences for working with data, DataZymes enables individuals to address complex questions without requiring expertise in advanced technical skills. By building platforms for data integration, management, and security, the company powers human-assisted, machine-driven interactive analysis. DataZymes is committed to innovation and delivering tailored solutions that meet the unique demands of pharma commercial teams.

Job Location: Bengaluru

Experience Required: 3-5 Years

Industry: Pharmaceutical / Life Sciences

Role Overview:

We are looking for a highly skilled MLOps / AI Engineer to design, build, and deploy scalable

machine learning and Generative AI systems in production. The role involves owning the

end-to-end ML lifecycle, from data pipelines and model training to deployment, monitoring, and

optimization.

Key Responsibilities:

1.ML Ops & ML Lifecycle

Design and implement end-to-end ML pipelines

Build scalable feature engineering workflows

Implement CI/CD workflows for ML models

Manage model versioning and experiment tracking

2.Model Deployment & Infrastructure

Deploy models using Docker and Kubernetes

Build real-time and batch inference systems

Expose models via APIs

Optimize for latency and scalability.

3.Generative AI & LLM Systems

Develop LLM-powered applications

Implement RAG pipelines with vector databases

Fine-tune models using LoRA/adapters

Design prompt engineering workflows

4.Cloud & Platform Engineering

Work with AWS or GCP ML services

Design scalable cloud ML architectures

Integrate with data platforms

5.Monitoring & Optimization

Monitor model performance and drift

Optimize latency and cost

Implement logging and alerting systems

Required Skills & Qualifications:

35 years experience in ML / MLOps

Strong Python programming

Experience with Docker, Kubernetes, CI/CD

Knowledge of PyTorch/TensorFlow

Experience with Hugging Face, LangChain

Understanding of RAG and LLM systems

Experience with AWS or GCP.

Strong data engineering fundamentals.

Preferred Skills:

Experience with large-scale ML systems

Familiarity with Databricks or Snowflake

Knowledge of responsible AI

Experience building NLP/chatbot systems