The Role
Leads AI/ML platform engineering and operational excellence across the organization. Provides technical leadership, architecture guidance, mentoring, tool and cloud-service evaluation, and enablement for AI/ML teams. Oversees model deployment, monitoring, observability, optimization, governance, security, and compliance across cloud-native and containerized environments. Translates business requirements into scalable AI/ML solutions and supports Kubernetes, serverless, MLOps, and generative AI initiatives.
Summary Generated by Built In
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
AI/ML technology, AI/ML operational
Good-to-have skillsEngineering Manager
Skills Required
- 10+ years of experience in IT, software engineering, or data science-related positions
- 5+ years of direct experience with AI/ML technologies, platforms, and production solutions
- 3+ years in technical leadership, architecture, or senior engineering roles
- Experience designing and implementing large-scale AI/ML solutions and systems
- Experience with cloud platforms and cloud-native architectures
- Experience with DevOps, CI/CD pipelines, and containerized deployments
- Proficiency with TensorFlow, PyTorch, scikit-learn, and XGBoost
- Experience with Azure AI, AWS SageMaker, Google Vertex AI, and Databricks
- Experience with large language models, transformers, RAG, prompt engineering, and LLMOps
- Experience with Spark, Hadoop, pandas, SQL, and data engineering or ETL tools
- Experience with Azure, AWS, and GCP
- Experience with Kubernetes and Docker
- Experience with MLflow, Kubeflow, DVC, or Weights & Biases
- Experience with monitoring, logging, and observability tools such as Prometheus, ELK, Grafana, or DataDog
- Programming experience with Python, Java, Scala, and SQL
- Experience with Git and version control systems
- Engineering Manager experience
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The Company
What We Do
Weekday is an AI-powered recruitment platform that helps startups hire top-tier engineering and product talent. By leveraging a massive database of white-collar professionals and advanced outreach tools, the company streamlines the hiring process through automated sourcing, AI-driven resume screening, and white-glove contingency services. Their mission is to modernize recruitment by enabling companies to discover and engage passive candidates efficiently, ensuring high-quality hires for critical roles.
