Your potential, unleashed.

India s impact on the global economy has increased at an exponential rate and Deloitte presents an opportunity to unleash and realise your potential amongst cutting edge leaders, and organisations shaping the future of the region, and indeed, the world beyond.

At Deloitte, your whole self to work, every day. Combine that with our drive to propel with purpose and you have the perfect playground to collaborate, innovate, grow, and make an impact that matters.

The team

Deloitte s SA&MA- AI&Data practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning. Learn more about SAMA Practice.

Your work profile

As a level in our Consultant/Senior Consultant/Manager you ll build and nurture positive working relationships with teams and clients with the intention to exceed client expectations: -

We are seeking skilled ML-Ops Manager / Senior Consultants to implement and manage ML-Ops frameworks for various industries. The ideal candidates will have a minimum of 8+ Years (Manager)/4-7 Years of experience (Senior Consultant) in Designing, Implementing, and leading ML-Ops frameworks. In this role, you will be responsible for the deployment, testing, and continuous integration of machine learning models while working with cross-functional teams.

Following are the Key requirements:

Collaborate with data scientists, developers, and infrastructure teams to ensure seamless integration of machine learning models into production environments.

Develop and implement ML-Ops best practices to streamline the end-to-end machine learning lifecycle, from model training and testing to deployment and monitoring.

Design, build, and maintain scalable and reliable machine learning pipelines for data ingestion, preprocessing, feature engineering, model training, and deployment.

Implement and manage continuous integration and continuous deployment (CI/CD) processes for machine learning models.

Monitor the health and performance of deployed models, identifying and addressing issues related to data drift, model degradation, and performance bottlenecks.

Automate model retraining and deployment processes to ensure models remain up to date with changing data and requirements.

Collaborate with cross-functional teams to ensure data security, compliance, and privacy standards are met throughout the ML-Ops lifecycle.

Drive improvements in the machine learning infrastructure by evaluating new tools, technologies, and processes.

Participate in on-call rotations to address critical system issues as they arise.

Additional Preferred Skills:

Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack) for tracking model performance and system health.

Knowledge of machine learning model monitoring and management platforms.

Background in distributed computing and parallel processing.

Domain expertise in Telecom, Retail / BFSI, Marketing, Life science, Manufacturing etc.

Desired qualifications

Bachelors or Masters degree in Computer Science, Engineering, Data Science, or related field.

Proven experience in deploying and managing machine learning models in production environments.

Strong programming skills in languages such as Python, and experience with relevant libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

Hands-on experience with containerization technologies such as Docker and orchestration platforms like Kubernetes.

Proficiency in designing and optimizing data pipelines for large-scale data processing and machine learning.

Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and services for ML model deployment and management.

Experience with version control systems (e.g., Git) and CI/CD tools (e.g., Jenkins, GitLab CI/CD).

Strong understanding of DevOps principles and practices, and the ability to collaborate effectively with cross-functional teams.

Excellent problem-solving skills and the ability to diagnose and resolve complex technical issues.

Strong communication skills, both written and verbal, to effectively convey technical information to non-technical stakeholders.

Location and way of working.

• Base location: PAN India


• This profile involves occasional travelling to client locations OR this profile does not involve extensive travel for work.


• Hybrid is our default way of working. Each domain has customized the hybrid approach to their unique needs.

Your role as a Consultant/Senior Consultant/Manager

We expect our people to embrace and live our purpose by challenging themselves to identify issues that are most important for our clients, our people, and for society.

In addition to living our purpose, Consultant/Senior Consultant/Manager across our organization must strive to be:

• Inspiring - Leading with integrity to build inclusion and motivation


• Committed to creating purpose - Creating a sense of vision and purpose


• Agile - Achieving high-quality results through collaboration and Team unity


• Skilled at building diverse capability - Developing diverse capabilities for the future


• Persuasive / Influencing - Persuading and influencing stakeholders


• Collaborating - Partnering to build new solutions


• Delivering value - Showing commercial acumen


• Committed to expanding business - Leveraging new business opportunities


• Analytical Acumen - Leveraging data to recommend impactful approach and solutions through the power of analysis and visualization


• Effective communication - Must be well abled to have well-structured and well-articulated conversations to achieve win-win possibilities


• Engagement Management / Delivery Excellence - Effectively managing engagement(s) to ensure timely and proactive execution as well as course correction for

the success of engagement(s)

• Managing change - Responding to changing environment with resilience


• Managing Quality & Risk - Delivering high quality results and mitigating risks with utmost integrity and precision


• Strategic Thinking & Problem Solving -