Job Description
Job Position:- AIML Lead
Experience Required- 8-10 years
Job Type- Full-time
Location - Hyderabad, India
Notice:- 0-30days
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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.
8. 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
• 8+ years of total professional experience in technology and solution delivery.
• 2+ years of hands-on experience in AI/ML model development, deployment, and scaling.
• 5+ 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.
Experience Required- 8-10 years
Job Type- Full-time
Location - Hyderabad, India
Notice:- 0-30days
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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.
7. 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.
8. 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
• 8+ years of total professional experience in technology and solution delivery.
• 2+ years of hands-on experience in AI/ML model development, deployment, and scaling.
• 5+ 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.
💡 Quick Summary
Seeking a career-building opportunity? The AIML Lead position is now open for candidates interested in the Operations Executive Jobs sector. This role in Ahmedabad offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in Operations Executive Jobs is a plus.
