Sales - BPO

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. 

Location: Bangalore (Hybrid/Onsite)

Experience: 5–8 Years

Work location -Manyata Tech park

Job Description

We are seeking a skilled GCP Data Engineer with 5–8 years of experience in designing, developing, and maintaining scalable data pipelines and cloud-based data solutions. The ideal candidate should have strong expertise in Google Cloud Platform (GCP), Python, PySpark, SQL, and Data Engineering concepts.

Key Responsibilities

• Design, build, and optimize scalable ETL/ELT data pipelines.
• Develop and maintain data processing solutions using Python and PySpark.
• Work with large-scale structured and unstructured datasets.
• Implement data ingestion, transformation, and data quality frameworks.
• Build and manage data solutions on Google Cloud Platform (GCP).
• Develop and optimize complex SQL queries, stored procedures, and data models.
• Collaborate with business stakeholders, data analysts, and cross-functional teams to understand data requirements.
• Monitor, troubleshoot, and improve data pipeline performance and reliability.
• Ensure data governance, security, and compliance standards are followed.
• Support data warehousing and analytics initiatives.

Required Skills

• 5–8 years of experience in Data Engineering.
• Strong programming experience in Python.
• Hands-on experience with PySpark and distributed data processing.
• Strong expertise in SQL and database performance tuning.
• Experience with Google Cloud Platform (GCP) services such as:
• BigQuery
• Cloud Storage
• Dataflow
• Dataproc
• Cloud Composer
• Pub/Sub
• Experience in designing ETL/ELT workflows.
• Knowledge of data warehousing concepts and dimensional modeling.
• Experience with version control tools such as Git.
• Strong problem-solving and analytical skills.

Preferred Skills

• Experience with CI/CD pipelines and DevOps practices.
• Exposure to orchestration tools like Airflow/Cloud Composer.
• Experience working in Agile/Scrum environments.
• Knowledge of streaming data processing and real-time data pipelines.

Educational Qualification

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.

Job Title: ELK Stack Engineer

Position Overview:

We are seeking a skilled and experienced Senior Elasticsearch Developer to join our team. The ideal candidate will be responsible for designing, developing, and maintaining data pipelines using the ELK Stack (Elasticsearch 7.1 or higher, Logstash, Kibana). The Senior Elasticsearch Developer will play a key role in managing large datasets, optimizing complex queries, and maintaining self-hosted Elastic Search clusters.

Responsibilities:

• Design, develop, and maintain data pipelines using the ELK Stack.
• Handle large datasets (3 billion+ records, 100+ fields per index) with efficiency and accuracy.
• Develop and optimize complex Elasticsearch queries for efficient data retrieval and analysis.
• Manage and maintain self-hosted Elastic Search clusters.
• Implement DevOps practices, including containerization with Docker.
• Perform backups, disaster recovery, and index migrations to ensure data security and integrity.
• Execute data processing and cleaning techniques, including writing custom scripts to extract and transform data into usable formats.
• Collaborate with the engineering team to integrate Elastic Search with other systems.

Requirements:

• Bachelor's degree in Computer Science, Engineering, or related field.
• Minimum 5+ years of experience in designing, developing, and maintaining data pipelines using the ELK Stack.
• Hands-on experience handling large datasets (3 million+ records, 50+ fields per index).
• Strong proficiency in developing and optimizing complex Elasticsearch queries.
• Experience managing and maintaining self-hosted ElasticSearch clusters.
• Proficiency in DevOps practices, including containerization with Docker.
• Knowledge of security best practices, including backups, disaster recovery, and index migrations.
• Experience with database administration and data processing techniques.
• Excellent communication and teamwork skills.

Benefits:

• Competitive salary and benefits package between 20 to 35 LPA.
• Opportunities for professional development and growth.
• Collaborative and inclusive work environment.
• Flexible work hours and remote work options.

Job Responsibilities:

• Must have knowledge of at least one PHP framework out of Laravel and Cakephp.
• Must have basic knowledge of HTML, CSS, JavaScript and jQuery.
• Good knowledge of Object-Oriented Concepts & a strong passion for Software Development.
• Strong Interaction and Design Sense
• Familiarity with LAMP stack (Apache, MySQL and phpMyAdmin)
• Comfortable with SQL and/or Script Programming.
• Experience in Designing & Developing Database in MySQL is a MUST.

Required Skills:

• Knowledge and/or willingness to learn, highly motivated.
• Fully comfortable working in English, both in written and spoken language.

• Work with stakeholders and fellow developers.
• Design and implement Python code using the Django framework.
• Identify and fix bottlenecks that may arise from inefficient code.
• Identify and fix software bugs.
• Create a wide variety of unit tests to verify the functionality of software.
• Manage the security of the platform.
• Write detailed documentation around the code.
• Knowledge of front end languages.

Work Location:Mumbai,Gurgoan,Indore,Bangalore,Hyderabad

• J2EE
• Web services
• JSON
• JSP Servlet
• Exception handling
• Multithreading
• Rest API
• Microservices