2+ Pipeline management Jobs in Delhi, NCR and Gurgaon | Pipeline management Job openings in Delhi, NCR and Gurgaon

About MyOperator:

MyOperator is a Business AI Operator, a category-leader that unifies WhatsApp, Calls, and AI-powered chat & voice bots into one intelligent business communication platform. Unlike fragmented communication tools, MyOperator combines automation, intelligence, and workflow integration to help businesses run WhatsApp campaigns, manage calls, deploy AI chatbots, and track performance — all from a single, no-code platform. Trusted by 12,000+ brands including Amazon, Domino's, Apollo, and Razorpay, MyOperator enables faster responses, higher resolution rates, and scalable customer engagement — without fragmented tools or increased headcount.

Role Overview:

We are seeking a high-performing Sales Team Leader to lead and manage a team of sales consultants. This role is responsible for driving team performance, ensuring process adherence, and meeting revenue goals with a strong focus on consultative selling. If you have a strong sales background, leadership experience, and a passion for growing people and revenue together, we’d love to meet you.

Key Responsibilities:

1. Lead, manage, and mentor a team of inbound Business Consultants to achieve monthly revenue targets.

2. Conduct daily stand-ups, pipeline discussions, and deal reviews to ensure effective conversion.

3. Monitor individual performance through CRM dashboards and ensure process adherence.

4. Track and report key performance metrics (calls, demos, closures, revenue).

Revenue & Process Ownership:

1. Drive team performance for consistent achievement of MRR and closure numbers.

2. Ensure timely and high-quality follow-ups with all inbound leads.

3. Support team members in deal negotiation, closure, and retention of key customers.

Training & Development:

1. Identify skill gaps and work with L&D to enhance sales capability and product knowledge.

2. Conduct regular role-plays, feedback sessions, and performance improvement discussions.

Requirements:

1. Experience: 4–6 years in B2B Inside Sales / SaaS Sales with at least 2 years of proven experience in leading a sales team.

2. Must Have: Prior experience in handling inbound sales processes and achieving monthly revenue targets.

3. Strong understanding of CRM systems (preferably Zoho or similar).

4. Excellent communication, analytical, and leadership skills.

5. High ownership mindset with the ability to drive results under pressure.

6. ​Experience in cloud telephony, SaaS, or communication technology will be an added advantage.

Benefits:

1. High-growth work environment

2. Fixed salary + attractive performance incentives

3. Opportunity to work on impactful SaaS solutions

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.