Weekday AI

Proactive software engineer recruitment via referrals

AI Lead – Technical

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeMumbai, Maharashtra, IndiaNo salary listedIn-person

About the Job

Requirements

At least 10 years of experience in IT, software engineering, or data science-related positions.
At least 5 years of direct experience with AI/ML technologies, platforms, and solutions in production environments.
At least 3 years in technical leadership, architecture, or a senior engineering role.
Experience designing and implementing large-scale AI/ML solutions and systems.
Experience working with cloud platforms and understanding cloud-native architectures.
Experience with DevOps, CI/CD pipelines, and containerized deployments.
Experience with machine learning frameworks including TensorFlow, PyTorch, scikit-learn, and XGBoost.
Experience with AI/ML platforms including Azure AI, AWS SageMaker, Google Vertex AI, and Databricks.
Experience with large language models and generative AI, including transformers, retrieval-augmented generation, prompt engineering, and LLMOps.
Experience with data processing and analytics tools including Spark, Hadoop, pandas, and SQL.
Experience with cloud platforms including Azure, AWS, and Google Cloud Platform.
Experience with container orchestration using Kubernetes and Docker.
Experience with MLOps and model deployment tools including MLflow, Kubeflow, DVC, and Weights & Biases.
Experience with data engineering and extract, transform, and load tools.
Experience with monitoring, logging, and observability tools including Prometheus, ELK, Grafana, and Datadog.
Experience with scripting and programming languages including Python, Java, Scala, and SQL.
Experience with Git and version control systems.

Responsibilities

Investigate, analyze, and troubleshoot AI/ML technology stacks, frameworks, and infrastructure using appropriate diagnostic and monitoring tools.
Provide technical leadership and mentoring to AI Engineering, Data Engineering, and Platform teams, fostering technical excellence and continuous improvement.
Enable AI/ML platforms, tooling, and best practices across the organization.
Provide architecture guidance and technical oversight for AI/ML solution design, implementation, and optimization.
Lead the evaluation, selection, and integration of AI/ML tools, frameworks, and cloud services, including Azure AI, AWS SageMaker, and Google Vertex AI.
Establish and maintain monitoring, logging, and observability standards for AI/ML systems and models.
Investigate opportunities to optimize AI/ML technology stacks, including model performance tuning and infrastructure efficiency.
Work with solution architects and business stakeholders to translate business requirements into technical AI/ML solutions.
Provide support and enablement for containerized and cloud-native environments, specifically Kubernetes and serverless platforms.
Ensure compliance, security, and governance best practices are implemented across AI/ML solutions.
Stay current with emerging AI/ML technologies, frameworks, and industry best practices.

Desired Qualifications

Engineering Manager experience or capability is listed as a good-to-have skill.

AI Lead (Technical)

Weekday AI · Mumbai, India · Full-time · Posted 2026-08-19

Workplace: on_site

Department: Weekday's Client via platform

Description

This role is for one of Weekday’s clients

Min Experience: 12+ years
Location: Mumbai, Maharashtra, India
JobType: full-time

The incumbent shall be responsible for leading AI/ML operational and platform engineering functions across the organization. The focus of this role is to provide and ensure technical excellence in the AI/ML technology landscape and drive the adoption of AI solutions across business units.

Requirements

Relevant Experience:

10 years’ experience in IT, software engineering, or data science related positions
5 years of direct experience with AI/ML technologies, platforms, and solutions in production environments.
3 years in technical leadership, architecture, or senior engineering role.
Experience in Designing and implementing large-scale AI/ML solutions and systems.
Experience working with cloud platforms and understanding of cloud-native architectures.
Experience with DevOps, CI/CD pipelines, and containerized deployments.

Responsibilities:

Deep dive technical investigation, analysis and troubleshooting across AI/ML technology stacks, frameworks, and infrastructure using appropriate diagnostic and monitoring tools.
Provide technical leadership and mentoring to AI Engineering, Data Engineering, and Platform teams, fostering a culture of technical excellence and continuous improvement.
Drive the enablement of AI/ML platforms, tooling, and best practices across the organization.
Provide architecture guidance and technical oversight for AI/ML solution design, implementation, and optimization.
Lead the evaluation, selection, and integration of AI/ML tools, frameworks, and cloud services (e.g., Azure AI, AWS SageMaker, Google Vertex AI).
Establish and maintain monitoring, logging, and observability standards for AI/ML systems and models.
Investigate opportunities for optimization of AI/ML technology stacks, including model performance tuning and infrastructure efficiency.
Work with solution architects and business stakeholders to translate business requirements into technical AI/ML solutions.
Provide support and enablement for containerized and cloud-native environments, specifically Kubernetes and serverless platforms.
Ensure compliance, security, and governance best practices are implemented across all AI/ML solutions.
Stay current with emerging AI/ML technologies, frameworks, and industry best practices.

Mandatory Skills:

Machine Learning Frameworks (TensorFlow, PyTorch, scikit-learn, XGBoost)
AI/ML Platforms (Azure AI, AWS SageMaker, Google Vertex AI, Databricks)
Large Language Models and GenAI (transformers, RAG, prompt engineering, LLMOps)
Data Processing and Analytics (Spark, Hadoop, pandas, SQL)
Cloud Platforms (Azure, AWS, GCP)
Container Orchestration (Kubernetes, Docker)
MLOps and Model Deployment tools (MLflow, Kubeflow, DVC, Weights & Biases)
Data Engineering and ETL tools
Monitoring, Logging, and Observability tools (Prometheus, ELK, Grafana, DataDog)
Scripting and Programming Languages (Python, Java, Scala, SQL)
Git and Version Control Systems

Must-have skills

AI/ML technology, AI/ML operational

Good-to-have skills

Engineering Manager

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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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