AI ML Lead

Job Position:- AIML Lead

Experience Required- 7-10 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

• 7+ 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
  .