Weekday AI

Proactive software engineer recruitment via referrals

Staff Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

At least 10 years of experience in Machine Learning, Data Science, and AI Engineering.
A proven track record of delivering production-grade AI and machine learning products at scale.
Experience leading complex technical initiatives and influencing engineering direction.
Experience mentoring engineers and driving technical excellence across teams.
Strong expertise in Python, SQL, and distributed computing frameworks such as Spark.
Deep knowledge of machine learning and deep learning frameworks including PyTorch, TensorFlow, and Scikit-learn.
Strong expertise in large language models, retrieval-augmented generation, agentic AI systems, reinforcement learning concepts, and AI evaluation frameworks.
Hands-on experience with Docker, Kubernetes, AWS, Azure, or GCP; vector databases; and API and microservices architecture.
Expertise in MLOps, model deployment, feature stores, experiment tracking, observability, and monitoring.
Strong architectural and systems-thinking mindset.
Ability to influence without authority and drive cross-functional alignment.
Exceptional communication and stakeholder management skills.
Passion for mentoring, innovation, and continuous learning.
Applied machine learning is listed as a must-have skill.

Responsibilities

Define and drive the technical vision for Machine Learning and Generative AI initiatives.
Lead architecture reviews and establish best practices for scalable AI systems.
Mentor and guide ML engineers and data scientists across teams.
Influence product strategy through AI-driven innovation and technical thought leadership.
Partner with Engineering leadership to build scalable, reliable, and secure AI platforms.
Design, develop, and deploy large-scale machine learning solutions in production environments.
Build advanced predictive models, recommendation systems, forecasting solutions, natural language processing applications, and deep learning systems.
Drive the complete machine learning lifecycle, including problem definition, data acquisition and exploration, feature engineering, model development, model evaluation and validation, production deployment, monitoring, governance, and continuous improvement.
Develop frameworks and reusable components to accelerate machine learning development across teams.
Establish model governance, explainability, fairness, and compliance standards.
Architect and deliver enterprise-scale Generative AI solutions using OpenAI, Azure OpenAI, Anthropic Claude, Llama, Mistral, and Gemini.
Design and implement advanced retrieval-augmented generation architectures, agentic AI systems, multi-agent workflows, AI orchestration frameworks, prompt engineering and evaluation frameworks, fine-tuning and model adaptation pipelines, knowledge graph-assisted AI systems, and AI observability and evaluation frameworks.
Lead experimentation and adoption of emerging AI technologies.
Architect scalable machine learning platforms and infrastructure.
Build and optimize end-to-end machine learning pipelines.
Drive MLOps practices including CI/CD for machine learning, model serving, feature stores, experiment tracking, monitoring and observability, automated retraining pipelines, and model governance and security.
Optimize system performance, scalability, reliability, and cost efficiency.
Partner with Product Managers, Engineering leaders, and Business stakeholders to identify high-impact AI opportunities.
Translate business problems into scalable AI solutions.
Define success metrics and measure business impact.
Drive AI adoption and technical excellence across the organization.

Desired Qualifications

Machine learning and AI engineering are listed as good-to-have skills.

Staff Machine Learning Engineer

Weekday AI · Bengaluru, India · Full-time · Posted 2026-09-22

Workplace: on_site

Department: Weekday's Client via platform

Description

This role is for one of Weekday’s clients

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

We are seeking a highly experienced Staff Machine Learning Engineer to lead the architecture, development, and scaling of enterprise-grade Machine Learning and Generative AI platforms.

As a senior technical leader, you will drive AI strategy, establish engineering best practices, mentor ML engineers, and collaborate cross-functionally with Product, Engineering, Data, and Business stakeholders to deliver measurable business outcomes. You will play a critical role in shaping our AI roadmap and building intelligent products that impact thousands of businesses globally.

The ideal candidate will have 8+ years of experience building and deploying large-scale ML systems, deep expertise across the full ML lifecycle, and hands-on experience delivering production-grade Generative AI solutions at scale.

Requirements

Key Responsibilities

Technical Leadership

Define and drive the technical vision for Machine Learning and Generative AI initiatives.
Lead architecture reviews and establish best practices for scalable AI systems.
Mentor and guide ML engineers and data scientists across teams.
Influence product strategy through AI-driven innovation and technical thought leadership.
Partner with Engineering leadership to build scalable, reliable, and secure AI platforms.

Machine Learning & Data Science

Design, develop, and deploy large-scale ML solutions in production environments.
Build advanced predictive models, recommendation systems, forecasting solutions, NLP applications, and deep learning systems.
Drive the complete machine learning lifecycle:
Problem definition
Data acquisition and exploration
Feature engineering
Model development
Model evaluation and validation
Production deployment
Monitoring, governance, and continuous improvement
Develop frameworks and reusable components to accelerate ML development across teams.
Establish model governance, explainability, fairness, and compliance standards.

Generative AI & LLM Applications

Architect and deliver enterprise-scale GenAI solutions leveraging:

OpenAI
Azure OpenAI
Anthropic Claude
Llama
Mistral
Gemini

Design and implement:

Advanced RAG architectures
Agentic AI systems
Multi-agent workflows
AI orchestration frameworks
Prompt engineering and evaluation frameworks
Fine-tuning and model adaptation pipelines
Knowledge graph-assisted AI systems
AI observability and evaluation frameworks

Lead experimentation and adoption of emerging AI technologies to create competitive advantage.

Platform Engineering & MLOps

Architect scalable ML platforms and infrastructure.

Build and optimize end-to-end ML pipelines.

Drive MLOps best practices including:

CI/CD for ML
Model serving
Feature stores
Experiment tracking
Monitoring and observability
Automated retraining pipelines
Model governance and security

Optimize system performance, scalability, reliability, and cost efficiency.

Cross-Functional Collaboration

Partner with Product Managers, Engineering leaders, and Business stakeholders to identify high-impact AI opportunities.
Translate business problems into scalable AI solutions.
Define success metrics and measure business impact.
Drive AI adoption and technical excellence across the organization.

Preferred Qualifications

Experience

10+ years of experience in Machine Learning, Data Science, and AI Engineering.
Proven track record of delivering production-grade AI/ML products at scale.
Experience leading complex technical initiatives and influencing engineering direction.
Experience mentoring engineers and driving technical excellence across teams.

Technical Skills

Strong expertise in Python, SQL, and distributed computing frameworks such as Spark.

Deep knowledge of machine learning and deep learning frameworks:

PyTorch
TensorFlow
Scikit-learn

Strong expertise in:

Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Agentic AI Systems
Reinforcement Learning concepts
AI Evaluation Frameworks

Hands-on experience with:

Docker
Kubernetes
AWS, Azure, or GCP
Vector Databases
API and Microservices Architecture

Expertise in:

MLOps
Model Deployment
Feature Stores
Experiment Tracking
Observability and Monitoring

Leadership Attributes

Strong architectural and systems-thinking mindset.
Ability to influence without authority and drive cross-functional alignment.
Exceptional communication and stakeholder management skills.
Passion for mentoring, innovation, and continuous learning.

Must-have skills

Applied Machine Learning

Good-to-have skills

Machine Learning, AI ENGINEERING

Apply

Apply at Weekday AI

About the Company

Weekday AI

Proactive software engineer recruitment via referrals

Weekday.works helps companies hire software engineers through proactive outreach and peer-recommended candidates. Its platform automates tracking, pipeline management, and provides weekly updates, while it actively identifies engineers via peer networks, reaches out, shortlists, checks references, and schedules interviews. Differentiators include peer-backed vetting instead of traditional job boards, proactive outreach, and a passive-income reference feature that monetizes referrals. The goal is to reduce the time and effort of hiring by connecting companies with pre-vetted engineers who are open to new opportunities through a network-driven approach.

Company size: 201-500
Company stage: Seed
Total funding: $2.3M
Headquarters: Bengaluru, India
Founded: 2021

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