
Role - MLops Engineer
Location - Pune, Gurgaon, Noida, Bhopal, Bangalore
Mode - Hybrid
Role Overview
We are looking for an experienced MLOps Engineer to join our growing AI/ML team. You will be responsible for automating, monitoring, and managing machine learning workflows and infrastructure in production environments. This role is key to ensuring our AI solutions are scalable, reliable, and continuously improving.
Key Responsibilities
- Design, build, and manage end-to-end ML pipelines, including model training, validation, deployment, and monitoring.
- Collaborate with data scientists, software engineers, and DevOps teams to integrate ML models into production systems.
- Develop and manage scalable infrastructure using AWS, particularly AWS Sagemaker.
- Automate ML workflows using CI/CD best practices and tools.
- Ensure model reproducibility, governance, and performance tracking.
- Monitor deployed models for data drift, model decay, and performance metrics.
- Implement robust versioning and model registry systems.
- Apply security, performance, and compliance best practices across ML systems.
- Contribute to documentation, knowledge sharing, and continuous improvement of our MLOps capabilities.
Required Skills & Qualifications
- 4+ years of experience in Software Engineering or MLOps, preferably in a production environment.
- Proven experience with AWS services, especially AWS Sagemaker for model development and deployment.
- Working knowledge of AWS DataZone (preferred).
- Strong programming skills in Python, with exposure to R, Scala, or Apache Spark.
- Experience with ML model lifecycle management, version control, containerization (Docker), and orchestration tools (e.g., Kubernetes).
- Familiarity with MLflow, Airflow, or similar pipeline/orchestration tools.
- Experience integrating ML systems into CI/CD workflows using tools like Jenkins, GitHub Actions, or AWS CodePipeline.
- Solid understanding of DevOps and cloud-native infrastructure practices.
- Excellent problem-solving skills and the ability to work collaboratively across teams.

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drives large-scale data modernization and AI readiness for global enterprises. We are looking for an experienced Data Modeler to design, standardize, and maintain enterprise data models across our modernization initiatives — ensuring consistency, quality, and business alignment across cloud data platforms.
The person will be responsible for translating business requirements and data flows into robust conceptual, logical, and physical data models across multiple domains (Customer, Product, Finance, Supply Chain, etc.). You will work closely with Data Architects, Engineers, and Governance teams to ensure data is structured, traceable, and optimized for analytics and interoperability across platforms like Snowflake, Dremio, and Databricks.
Key Responsibilities-
- Develop conceptual, logical, and physical data models aligned with enterprise architecture standards.
- Engage with Business Stakeholders: Collaborate with business teams, business analysts and SMEs to understand business processes, data lifecycles, and key metrics that drive value and outcomes.
- Value Chain Understanding: Analyze end-to-end customer and product value chains to identify critical data entities, relationships, and dependencies that should be represented in the data model.
- Conceptual and Logical Modeling: Translate business concepts and data requirements into conceptual and logical data models that capture enterprise semantics and support analytical and operational needs.
- Physical Data Modeling: Design and implement physical data models optimized for performance and scalability
- Semantic Layer Design: Create semantic models that enable business access to data via BI tools and data discovery platforms.
- Data Standards and Governance: Ensure models comply with enterprise data standards, naming conventions, lineage tracking, and governance practices.
- Implement naming conventions, data standards, and metadata definitions across all models.
- Collaboration with Data Engineering: Work closely with data engineers to align data pipelines with the logical and physical models, ensuring consistency and accuracy from ingestion to consumption.
- Manage version control, lineage tracking, and change documentation for models.
- Participate in data quality and governance initiatives to ensure trusted and consistent data definitions across domains.
- Create and maintain a business glossary in collaboration with the governance team.
Ideal Candidate
- Strong Enterprise Data Modeller profile (Modern Data Platforms)
- Mandatory (Experience 1) – Must have 7+ years of experience in Data Modeling or Enterprise Data Architecture, with strong hands-on expertise in designing conceptual, logical, and physical data models for enterprise data platforms
- Mandatory (Experience 2) – Must have Strong hands-on experience with enterprise data modeling tools such as Erwin, ER/Studio, PowerDesigner, SQLDBM, or similar enterprise data modeling tools
- Mandatory (Experience 3) – Must have Deep understanding of dimensional modeling (Kimball / Inmon methodologies), normalization techniques, and schema design for modern data warehouse environments.
- Mandatory (Experience 4) – Proven experience designing data models for modern data platforms such as Snowflake, Databricks, Redshift, Dremio, or similar cloud data warehouse / lakehouse systems.
- Mandatory (Experience 5) – Must have strong SQL expertise and schema design skills, with the ability to validate data model implementations and collaborate closely with data engineering teams
- Mandatory (Education) – Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related technical field.
- Preferred (Experience 1) – Should have familiarity with data governance, metadata management, lineage, and business glossary tools such as Collibra, Alation, or Microsoft Purview.
- Preferred (Experience 2) – Exposure to data integration pipelines and ETL frameworks such as Informatica, DBT, Airflow, or similar tools.
- Preferred (Data Management) – Understanding of master data management (MDM) and reference data management principles.
- Preferred (Domain) – Experience working with high-tech or manufacturing data domains, including customer, product, or supply chain data models
Responsibilities:
- Design and develop clean, high-performing, responsive and multilingual user experiences for our eCommerce sites using alpinejs and tailwind
- Working closely with project managers to address client requests
- Managing multiple projects simultaneously, and be able to address their specific needs and requirements quickly
- Proactively identify and address engineering challenges to enhance the overall quality and performance of our web applications.
Skills:
- Excellent communication skills with the ability to understand business requirements and effectively translate them into technical requirements.
- Ability to write algorithms in Javascript
- Strong knowledge of web technologies and concepts, including HTML, CSS, Tailwind CSS, components architecture, performance optimization techniques, and tools like Lighthouse.
- Proficiency in core JavaScript concepts and familiarity with jQuery.
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- Familiarity with working with RESTful APIs.
- Understanding of B2C user experience metrics using industry-standard analytics tools.
- Knowledge of php and Magento would be an advantage.
- Understanding of web UIs, demonstrated through a portfolio
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Candidate Profile:
Our requirement is extremely specific, and we are very particular about the candidate we are looking for. The selected candidate would be a street-smart individual with a focus on the completion of tasks at hand. We are NOT looking for candidates who require hand-holding at every stage. The candidate is expected to be enterprising enough to read between the lines (of the requirements) and deliver them in a ‘deployable’ state. We do not have the liberty to document every requirement and provide the same to the developers. Hence, as mentioned above, the requirements would be provided swiftly and only through conversations.
If you believe you fit the role well and would like to grow in a great work environment, we would like to talk to you!
- Lead and design solutions for complex testing problems by driving the requirements discussions with existing customers
- Conceptualize, design, develop and present the proposed solution; ensuring an integrated end-to-end testing solution is delivered 'right first time'
- Responsible for end to end pre-sales pursuit management in coordination with cross functional teams such as sales, delivery, horizontals, networking, marketing and process teams in global delivery model for the existing accounts
- Stay up to speed on process, practice and technology developments to ensure they enhance the solutions applied to the testing problems
- Act as a technical liaison between prospects, clients, quality engineering teams and management
- Engage with the customer build professional relationship; participate in teleconferences; lead customer workshops and presentations
- Mentor and train team members on domain and technology, help resolve any technical issues
- Travel to customer location across the geography to participate in proposal / RFP / SOW defense discussions and presentations
- Lead continuous improvement activities through contribution to technology repositories, supporting process change, leading transformational changes and driving re-use
Good to have Skills / Experience
- 14-18 years proven experience as a Solution Architect on large-scale testing accounts
- Experience as a Solution Architect or senior SME leading the development of solutions for testing complex systems, ensuring consistency with specified requirements agreed with both external and internal customers.
- Awareness of testing approaches, practices, techniques and methodologies to help design the overall testing solution
- Ability to have conversation with client (key stakeholders or key technologist at client). Ability to drive the discussion and arrive at conclusion
- The ability to see the big picture and manage multiple threads at the same time
- Well-versed in continuous integration, continuous delivery and continuous testing
- Understand and plan for commercial aspects and impact on winnability and deliverability of the solution
- In depth knowledge of one or more technical specializations including - quality engineering, release management, test environment management, test automation, test data management, testing approaches and test execution, performance engineering, development operations.
- Experience with all SDLC (Agile, Scaled Agile, DevOps) and engagement models
- Strong stakeholder relationship management and the confidence to initiate and influence relationships with and between key stakeholders
- Know the art of negotiation, persuasion and deal management
Object oriented design patterns
Maven build process and how Maven works
Working knowledge and good proficiency in Git , Git repo , git bash and git commands
Programming logic and reasoning
Learnability






