ML Ops Engineer

About

is a fast-growing AI SaaS startup revolutionizing how businesses leverage AI-powered solutions. As a part of our dynamic team, you'll work alongside industry leaders and visionaries to drive innovation and execution across multiple functions.

Role Overview:

The
MLOps Engineer
will lead the design, implementation, and optimization of VerbaFlo's machine learning infrastructure and pipelines. You will ensure the reliability, scalability, and performance of AI/ML workflows while driving automation and efficiency across data, training, deployment, and monitoring processes.

Responsibilities:

• 2–4 years of experience operating & owning end-to-end availability and performance of large-scale ML pipelines and production ML systems.
• Excellent understanding of atleast one major cloud environment and technologies AWS, Azure, and GCP (with ML/AI services).
• Hands-on experience with MLOps frameworks (MLflow, Kubeflow, Vertex AI, SageMaker, or similar).
• Strong grasp of containerization & orchestration for ML workloads (Docker, Kubernetes).
• Build and maintain CI/CD/CT pipelines for ML models (continuous integration, delivery, and training).
• Programming proficiency in Python, with knowledge of ML/AI libraries and APIs.
• Implement model monitoring for drift, bias, and performance degradation; integrate alerting and auto-remediation.
• Apply best practices in versioning for data, models, and experiments.
• Dissect complex ML operational problems into scalable, automated solutions.
• Lead post-mortem reviews, change management, and workflow optimization for ML systems.
• Identify, mitigate, and root-cause ML pipeline issues while continuously driving optimization and efficiency.
• Managing and scaling query and workload on vector databases like Milvus/Qdrant/Pgvector/Weaviate, MongoDB. Postgres.
• Fluency with at least one experiment tracking & reproducibility tools (MLflow, Comet, Weights & Biases) and observability platforms (Prometheus, Datadog)
• Experience working on ETL/ELT workflows (Apache Airflow, Luigi)
• Working knowledge of model serving frameworks (TorchServe, FastAPI, BentoML, vLLM)

Essential Skills:

• MLOps frameworks (Apache Airflow / Kubeflow / MLflow / Vertex AI / SageMaker)
• Exposure to LLM hosting providers (e.g., , OpenAI, Anthropic)
• CI/CD/CT Pipelines
• Kubernetes
• Programming (Python preferred)
• ML model serving/deployment on production environments

Desirable Skills:

• Data versioning tools (DVC, LakeFS)
• Infrastructure-as-Code (Terraform)
• Feature store & model registry experience
• Exposure to model explainability & compliance frameworks

Startup Ethos & Cultural Fit

• Bias for Action
  – We move fast, experiment often, and learn quickly.
• Perfection is the enemy of Good -
  We value putting it out, with iteration & progress over endless polish.
• Ownership Mentality
  – Everyone is a builder, accountable end-to-end.
• Customer Obsession
  – Every decision ties back to solving real user problems.
• Low Ego, High Impact
  – Collaboration, candor, and humility matter more than titles.
• Resilient & Resourceful
  – We thrive in ambiguity and turn constraints into innovation.

Location: Gurgaon, On-site

Why Join Us?

• Work directly with top leadership from Tier 1 institutes in a high-impact role.
• Be part of an innovative and fast-growing AI startup.
• Opportunity to take ownership of key projects and drive efficiency.
• A collaborative, ambitious, and fast-paced work environment.
• Perks & Benefits: gym membership benefit, work-from-home and workation policy, and company-sponsored lunch.

If you're looking for an exciting role that combines strategy, execution, and ownership exposure, we'd love to hear from you