Field Sales Executive

Review Criteria:

• Strong MLOps profile
• 8+ years of DevOps experience and 4+ years in MLOps / ML pipeline automation and production deployments
• 4+ years hands-on experience in Apache Airflow / MWAA managing workflow orchestration in production
• 4+ years hands-on experience in Apache Spark (EMR / Glue / managed or self-hosted) for distributed computation
• Must have strong hands-on experience across key AWS services including EKS/ECS/Fargate, Lambda, Kinesis, Athena/Redshift, S3, and CloudWatch
• Must have hands-on Python for pipeline & automation development
• 4+ years of experience in AWS cloud, with recent companies
• (Company) - Product companies preferred; Exception for service company candidates with strong MLOps + AWS depth

Preferred:

• Hands-on in Docker deployments for ML workflows on EKS / ECS
• Experience with ML observability (data drift / model drift / performance monitoring / alerting) using CloudWatch / Grafana / Prometheus / OpenSearch.
• Experience with CI / CD / CT using GitHub Actions / Jenkins.
• Experience with JupyterHub/Notebooks, Linux, scripting, and metadata tracking for ML lifecycle.
• Understanding of ML frameworks (TensorFlow / PyTorch) for deployment scenarios.

Job Specific Criteria:

• CV Attachment is mandatory
• Please provide CTC Breakup (Fixed + Variable)?
• Are you okay for F2F round?
• Have candidate filled the google form?

Role & Responsibilities:

We are looking for a Senior MLOps Engineer with 8+ years of experience building and managing production-grade ML platforms and pipelines. The ideal candidate will have strong expertise across AWS, Airflow/MWAA, Apache Spark, Kubernetes (EKS), and automation of ML lifecycle workflows. You will work closely with data science, data engineering, and platform teams to operationalize and scale ML models in production.

Key Responsibilities:

• Design and manage cloud-native ML platforms supporting training, inference, and model lifecycle automation.
• Build ML/ETL pipelines using Apache Airflow / AWS MWAA and distributed data workflows using Apache Spark (EMR/Glue).
• Containerize and deploy ML workloads using Docker, EKS, ECS/Fargate, and Lambda.
• Develop CI/CT/CD pipelines integrating model validation, automated training, testing, and deployment.
• Implement ML observability: model drift, data drift, performance monitoring, and alerting using CloudWatch, Grafana, Prometheus.
• Ensure data governance, versioning, metadata tracking, reproducibility, and secure data pipelines.
• Collaborate with data scientists to productionize notebooks, experiments, and model deployments.

Ideal Candidate:

• 8+ years in MLOps/DevOps with strong ML pipeline experience.
• Strong hands-on experience with AWS:
• Compute/Orchestration: EKS, ECS, EC2, Lambda
• Data: EMR, Glue, S3, Redshift, RDS, Athena, Kinesis
• Workflow: MWAA/Airflow, Step Functions
• Monitoring: CloudWatch, OpenSearch, Grafana
• Strong Python skills and familiarity with ML frameworks (TensorFlow/PyTorch/Scikit-learn).
• Expertise with Docker, Kubernetes, Git, CI/CD tools (GitHub Actions/Jenkins).
• Strong Linux, scripting, and troubleshooting skills.
• Experience enabling reproducible ML environments using Jupyter Hub and containerized development workflows.

Education:

• Master’s degree in computer science, Machine Learning, Data Engineering, or related field. 

Understand product requirements and translate them into effective test cases.

Perform manual functional, regression, UI, and integration testing.

Conduct thorough API testing using tools like Postman or Swagger.

Perform database validation using SQL queries to verify data integrity.

Create, manage, and execute detailed test plans and test cases.

Log and track defects using tools like JIRA, Bugzilla, or Azure DevOps.

Participate in Agile ceremonies (daily standups, sprint planning, retrospectives).

Collaborate closely with the development and product teams to reproduce issues and validate fixes

Job Responsibilities

• Build, test and set up cutting-edge website applications in an efficient matter; work with other developers to fill data acquisition requirements
• Identify and fix CSS, HTML and scripting compatibility issues between a variety of platforms and browsers; test websites on different browsers and mobile device browsers; correct problems identified by customer feedback
• Investigate and discover architectural considerations, such as web usability, site performance and database design, as part of the system design process; research and assess implementation alternatives for new application features
• Collaborate and communicate with development teams and management to resolve conflicts, prioritize needs, choose solutions or develop content criteria
• Develop procedures for ongoing website revision; recommend performance improvements; create and refine style guidelines for website content; select design tools, programming languages or applications
• Provide detailed explanations of website specifications, such as activities, software, product features, programming languages, communication protocols and operating systems hardware and software
• Remain up to date about current programming practices and web technologies through reading, continuing education opportunities or participation in professional workshops, groups or conferences

Requirements:

• Bachelor’s degree
• Proficient in PHP, Javascript, MySQL, AJAX, jQuery, CSS and HTML
• Demonstrated attention to detail
• Excellent written and oral communication skills

• 5 years of experience as Java/Jee Developer, Springboot
• Good knowledge of OOPS concepts.
• Experience in Java8, JSP, Spring Core, Spring MVC, Spring Rest & Spring JPA Repository
• Experience in Hibernate, relational databases and sql.
• Experience in Rest API development.
• Experience in implementation of Jasper Reports
• Familiar with Git & Maven