ML Ops Engineer

2 days ago

Hyderabad, India Mastech Digital Full time

Position Title: ML Ops Engineer 4 Complete onsite . Full-Time role Shift Timings: 10-7 pm /11-8 pm /12-9 pm Address: Spire T110, Hyderabad Knowledge City, Madhapur, Hyderabad, Telangana, India, . Job Description: Roles & Responsibilities: Define the long-term vision and strategy for MLOps initiatives: Set the direction for the organization’s MLOps, model deployment, and monitoring practices. Lead and manage a team of MLOps engineers: Provide technical guidance, mentorship, and career development for team members. Identify and explore cutting-edge research areas and technologies: Stay abreast of the latest advancements in MLOps, model serving, and AI operations. Drive innovation and the development of novel MLOps solutions: Lead efforts, prototype new approaches, and oversee implementation of advanced MLOps platforms. Design and manage scalable ML infrastructure and pipelines on GCP; oversee model deployment (A/B testing, rollouts/rollbacks, auto-scaling), and establish monitoring/observability (performance, drift, KPIs). Ensure ML operations meet governance, security, compliance, and disaster recovery standards across the organization. Collaborate with executive leadership on strategic decision-making: Align MLOps initiatives with business objectives and organizational priorities. Establish and enforce MLOps standards and best practices: Ensure quality, reproducibility, and security of ML systems across the organization. Represent the organization in external MLOps communities: Speak at conferences, publish thought leadership, and build partnerships with academia and industry. Technical Skills: 12+ - years of experience Mastery of relevant technical skills: Deep expertise in MLOps, model deployment, monitoring, and governance. Significant experience in designing and implementing complex MLOps systems at scale: Lead the architecture and deployment of large-scale MLOps platforms on GCP. Hands-on experience architecting large-scale ML platforms on GCP (Vertex AI, GKE, Dataflow, Big Query, Pub/Sub, Cloud Composer), implementing experiment tracking (MLflow, Weights & Biases, TensorBoard), feature stores (Vertex AI), data pipelines and workflow orchestration, and ensuring cloud security, compliance, disaster recovery, and cost optimization. Strong leadership and team management skills: Build, mentor, and lead high-performing MLOps teams. Excellent strategic thinking and problem-solving abilities: Translate business challenges into scalable, reliable MLOps solutions. Exceptional communication and influencing skills: Advocate for MLOps initiatives, and influence executive decisions and represent the organization externally through conferences, publications, and industry engagement. Must Have Skills: Deep expertise in MLOps, model deployment, monitoring, and governance Experience building scalable MLOps platforms on GCP Proficiency with CI/CD for ML, containerization (e.g. Docker, Kubernetes), IaC (Terraform), and orchestration Leadership in MLOps strategy, standards, and cross-team collaboration Hands-on expertise with GCP ML and data services (Vertex AI, Dataflow, BigQuery, Pub/Sub, Cloud Composer, GKE). Experience implementing model observability (performance monitoring, drift detection, dashboards, and alerts). Proficiency with experiment tracking (MLflow, W&B) and feature store management. Knowledge of cloud security, compliance, and cost optimization strategies.

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