# Machine Learning SME

> Weekday AI · Pune, India · Full-time · Posted 2026-10-05

**Salary:** INR 1,000,000–2,000,000

**Workplace:** on_site

**Department:** Weekday's Client via platform

## Description

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟭𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟮𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟭𝟬-𝟮𝟬 𝗟𝗣𝗔)

Experience: 6+ yrs

Location: pune, Hyderabad, Telangana, India, Bengaluru, Karnataka, India

Job Type: Full-time

We are looking for an experienced **MLOps / Machine Learning SME** to lead the design, development, deployment, and operationalisation of machine learning solutions across the complete ML lifecycle. The role requires strong hands-on expertise in **MLOps, Machine Learning, Python, AWS SageMaker, and AWS Bedrock**, along with the ability to provide technical leadership and work directly with clients and cross-functional stakeholders.

The ideal candidate will combine deep technical expertise with strong problem-solving and communication skills to build reliable, scalable, and production-ready machine learning platforms and solutions.

## Requirements

Key Responsibilities

-   Design and implement **end-to-end MLOps pipelines** covering model development, training, deployment, monitoring, and lifecycle management.
-   Develop and productionise machine learning solutions using **Python and modern ML frameworks**.
-   Build scalable ML workflows and infrastructure using **AWS SageMaker**.
-   Leverage **AWS Bedrock** to develop, integrate, and operationalise AI and foundation-model-based solutions.
-   Deploy machine learning models into scalable and reliable production environments.
-   Implement model monitoring, performance tracking, drift detection, alerting, and continuous improvement processes.
-   Develop automated workflows for model training, validation, deployment, and retraining.
-   Establish best practices for ML experimentation, versioning, reproducibility, governance, and deployment.
-   Collaborate with Data Scientists, Data Engineers, Software Engineers, DevOps, Cloud Architects, and Product teams.
-   Troubleshoot complex issues across ML pipelines, infrastructure, deployments, and production environments.
-   Optimise ML workloads for performance, scalability, reliability, and cost efficiency.
-   Evaluate emerging machine learning and AI technologies and identify opportunities for practical adoption.
-   Provide technical guidance and mentorship to engineering and machine learning teams.
-   Lead technical discussions, solution reviews, architecture sessions, and client-facing engagements.
-   Translate business and client requirements into scalable ML and MLOps solutions.
-   Prepare technical documentation, architecture designs, implementation approaches, and operational guidelines.
-   Contribute to engineering standards, reusable frameworks, automation, and continuous improvement initiatives.

What Makes You a Great Fit

-   **6+ years of experience** in Machine Learning, MLOps, ML Engineering, AI Engineering, or a closely related technical field.
-   Strong hands-on expertise in **end-to-end MLOps and Machine Learning**.
-   Advanced proficiency in **Python** for machine learning and production engineering.
-   Mandatory hands-on experience with **AWS SageMaker**.
-   Mandatory experience with **AWS Bedrock** and foundation-model/GenAI solutions.
-   Strong understanding of **ML model development, deployment, monitoring, and lifecycle management**.
-   Experience building production-grade ML pipelines and automated model deployment workflows.
-   Strong understanding of cloud infrastructure, CI/CD, containers, APIs, and scalable application architectures.
-   Experience with model monitoring, observability, model performance, drift, and reliability practices.
-   Strong troubleshooting and problem-solving skills across machine learning and cloud environments.
-   Proven experience working as a **Technical SME, Lead, or senior technical contributor**.
-   Strong client-facing experience with excellent communication and presentation skills.
-   Ability to explain complex ML and MLOps concepts to both technical and non-technical stakeholders.
-   Strong stakeholder management and cross-functional collaboration skills.
-   Ability to work independently, take ownership of complex technical initiatives, and provide effective technical leadership.
-   Experience working in Agile environments and managing multiple priorities effectively.
-   A Bachelor's or Master's degree in **Computer Science, Engineering, Data Science, Artificial Intelligence, or a related discipline** is preferred.

## Apply

[Apply at Weekday AI](https://apply.workable.com/weekday-1/j/C5CBE9A180/apply)

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