Lead Machine Learning Engineer

Weekday 1; Bengaluru; On-site; INR 5,000,000 - 9,900,000; Full time

Job summary

Weekday 1 in Bengaluru seeks a Senior ML Engineer to design, build, and deploy production-scale ML and GenAI solutions. You will own end-to-end ML lifecycles, from data exploration to model deployment, collaborating with product and engineering teams.

The role requires 10+ years in ML/DS, strong communication, and expertise in ML/DL frameworks, LLMs, GenAI, and MLOps. This is a full-time opportunity enabling scalable AI systems in a dynamic environment.

Qualifications

• 10+ years of experience in ML/DS or related fields.
• Experience building end-to-end ML solutions and GenAI applications.
• Strong communication and collaboration skills.

Responsibilities

• Design, build, deploy, and monitor production-grade ML solutions
• Develop AI/ML applications using modern ML and GenAI frameworks
• Build and optimize end-to-end ML pipelines
• Collaborate with Product and Engineering teams to deliver business impact
• Drive best practices in MLOps, model governance, and scalability

Skills

Python

SQL

Spark

ML/DL frameworks

LLMs

GenAI

Docker

Kubernetes

Cloud platforms

MLOps

Tools

Docker

Kubernetes

AWS/Azure/GCP

Job description

This role is for one of Weekday’s clients Salary range: Rs 5000000 - Rs 9900000 (ie INR 50 - 99 LPA)

Min Experience: 10+ years Location: Bengaluru JobType: full-time

Requirements

Key Responsibilities:

Machine Learning & Data Science

• Design, develop, and deploy end-to-end ML solutions at scale.
• Build and optimize predictive models, recommendation systems, NLP solutions, and deep learning applications.
• Drive the complete data science lifecycle:
• Problem formulation
• Data exploration
• Feature engineering
• Model training
• Evaluation

Generative AI

• Build enterprise-grade GenAI applications using:
• OpenAI
• Azure OpenAI
• Anthropic Claude
• Llama
• Mistral
• Gemini
• Design and implement:
• RAG architectures
• Agentic AI systems
• Multi-agent frameworks
• Prompt engineering strategies
• Fine-tuning pipelines

Key Responsibilities:

• Design, build, deploy, and monitor production-grade ML solutions
• Develop AI/ML applications using modern ML and GenAI frameworks
• Build and optimize end-to-end ML pipelines
• Collaborate with Product and Engineering teams to deliver business impact
• Drive best practices in MLOps, model governance, and scalability

Preferred Skills:

• Python, SQL, Spark
• ML/DL frameworks (PyTorch, TensorFlow, Scikit-learn)
• LLMs, RAG, Agentic AI
• Docker, Kubernetes, Cloud Platforms (AWS/Azure/GCP)
• MLOps and model deployment
• Production deployment
• Excellent communication skills and ability to work with diverse stakeholders

What Sets You Apart:

• Experience optimizing LLMs for production (cost, latency, scaling)
• Track record of maintaining AI systems in production
• Ability to balance innovation with practical business needs
• Experience with HR/people analytics domain

Must-have skills

• Machine Learning, GENAI, Production

Good-to-have skills

• Gen AI