AI/ML Lead

Job Position:- AI/ML Lead

Experience Required- 6-10 years

Job Type- Full-time (Onsite)

Location - Hyderabad, India

Notice:- 0-30days Max

Overview

We are seeking a dynamic AI/ML Leader to drive innovation and implementation across AI, Generative AI, and Multimodal AI initiatives. The ideal candidate will lead the end-to-end development of intelligent solutions that enhance products and business outcomes. This role requires a blend of technical expertise, strategic thinking, and people leadership—with proficiency in AI/ML frameworks, cloud platforms, and MLOps practices.

In addition, the AI/ML Lead will play a pivotal role in building high-performing teams, fostering cross-functional collaboration, and promoting AI excellence across the organization.

Key Responsibilities

1. AI/ML Solution Development & Delivery

Lead the design, development, and deployment of AI and ML-based solutions aligned with business objectives.

Evaluate and implement AI frameworks, libraries, and platforms (TensorFlow, PyTorch, Hugging Face, LangChain, AutoML).

Define and execute data strategies for AI/ML pipelines including data ingestion, feature engineering, and model lifecycle management.

Ensure that AI models are scalable, maintainable, and production-ready for real-time and batch applications.

1. Cloud & Infrastructure Enablement

Oversee the deployment of AI workloads on AWS, GCP, Azure, or OCI with a focus on performance, scalability, and cost-efficiency.

Lead the design of containerized and serverless AI solutions using Docker, Kubernetes, and modern DevOps practices.

Ensure security, reliability, and fault tolerance across AI infrastructure.

1. Data Strategy & Management

Collaborate with data engineering teams to build robust data architectures supporting AI-driven analytics and automation.

Establish data governance frameworks, storage strategies, and metadata management processes.

Leverage big data platforms such as Databricks, Snowflake, and Spark for model training and data processing.

1. MLOps & Continuous Delivery

Build and manage end-to-end MLOps pipelines using MLflow, Kubeflow, SageMaker, or Vertex AI.

Integrate CI/CD processes for model versioning, validation, and deployment automation.

Implement monitoring and alerting mechanisms to ensure model performance and reliability in production.

1. Leadership & Collaboration

Lead a cross-functional team of AI engineers, data scientists, and product owners to deliver impactful AI initiatives.

Provide mentorship and technical guidance to team members and foster a culture of innovation.

Collaborate with product and business stakeholders to align AI initiatives with strategic priorities.

Conduct technical reviews and enforce best practices across teams.

1. Performance Optimization

Monitor AI model performance and drive optimization for accuracy, latency, and resource utilization.

Develop and implement cost management and scaling strategies for AI workloads.

Troubleshoot and resolve complex system and deployment challenges.

1. Innovation & Research

Stay abreast of emerging AI trends and technologies, including Generative AI and agentic automation.

Drive proof-of-concept (PoC) projects to evaluate new AI capabilities.

Contribute to research publications, patents, and AI community engagements to promote organizational thought leadership.

1. Stakeholder Engagement

Present AI/ML strategies and outcomes to leadership and technical stakeholders.

Support business development and pre-sales efforts through technical presentations and solution demonstrations.

Collaborate with customers and partners to define solution roadmaps and drive successful delivery.

Experience Requirements

6+ years of total professional experience in technology and solution delivery.

2+ years of hands-on experience in AI/ML model development, deployment, and scaling.

3+ years of experience with cloud platforms such as AWS, GCP, Azure, or OCI.

Technical Skills

AI/ML Frameworks: TensorFlow, PyTorch, Hugging Face, LangChain, AutoML.

Cloud AI Services: SageMaker, Vertex AI, Azure ML, Bedrock, LLM APIs.

MLOps Tools: MLflow, Kubeflow, TFX, CI/CD pipelines, Docker, Kubernetes.

Data Engineering: Spark, Databricks, BigQuery, Snowflake, Airflow.

Programming: Python (advanced), Java/Scala, SQL, PySpark.

Agentic AI: RPA tools (UiPath, Automation Anywhere), process mining.

Proven experience with DevOps, automation, and AI lifecycle management.

Preferred Qualifications

Master's degree in Computer Science, Engineering, or related technical field.

Certifications in AWS, Azure, or GCP (e.g., Solutions Architect or Cloud AI Engineer).

Experience with real-time AI applications, streaming data, and microservices architecture.

Knowledge of Responsible AI practices, including ethics, fairness, and bias detection.

Expertise in Python, TensorFlow, PyTorch, scikit-learn, and other modern AI libraries.

Soft Skills

Strong leadership and mentoring capabilities with experience leading technical teams.

Excellent communication and stakeholder management skills.

Strategic and analytical problem-solving mindset.

Collaborative, adaptable, and able to thrive in fast-paced, evolving environments.