AI ML

The AI Lead Developer is responsible for architecting designing and developing advanced AI ML solutions that power intelligent applications and data driven capabilities This role leads the end to end lifecycle of AI development including research model design training deployment monitoring and optimization while guiding a team of engineers and collaborating closely with product data and business stakeholders The AI Lead Developer ensures scalable ethical and production grade AI implementations
Key Responsibilities
AI ML Architecture Development
Architect design and develop machine learning and deep learning models for various use cases NLP CV LLMs recommendation systems predictive analytics etc
Implement end to end AI pipelines including data processing feature engineering model training evaluation and deployment
Build scalable and efficient model inference systems using microservices APIs or distributed frameworks
Optimize models for performance accuracy fairness and cost efficiency
Technical Leadership
Lead a team of AI ML engineers and data scientists oversee technical direction and code quality
Provide mentorship conduct code reviews and establish best practices for AI development
Collaborate with architects and tech leadership to define AI strategy standards and roadmaps
MLOps Deployment
Implement ML operationalization pipelines including model versioning CI CD for ML automated retraining and monitoring
Work with DevOps and Cloud teams to deploy models to AWS Azure or GCP using tools like SageMaker Vertex AI or Azure ML
Ensure robust monitoring of model drift data drift performance metrics and reliability
Research Innovation
Evaluate and incorporate emerging AI technologies transformers LLMs Diffusion models vector databases RAG etc
Conduct experimentation and POCs to determine feasibility of new AI solutions
Stay updated with cutting edge AI research frameworks and best practices
Collaboration Stakeholder Engagement
Work closely with product managers data teams and business stakeholders to define AI requirements and translate them into technical solutions
Communicate complex AI concepts in clear actionable terms for non technical audiences
Drive AI adoption and provide thought leadership across the organization
Required Skills Qualifications
Bachelor s or Master s degree in Computer Science Data Science AI ML or equivalent field
6 12 years of software AI engineering experience including
Strong hands on experience building ML DL models using Python TensorFlow PyTorch Scikit learn Transformers or similar frameworks
Proven experience in designing and deploying AI solutions at scale
Strong expertise in
NLP LLMs Computer Vision or Predictive Modeling based on role focus
Data engineering concepts ETL data pipelines data quality
Experience with cloud based ML platforms AWS Azure Google Cloud
Proficiency with MLOps tools MLflow Kubeflow Airflow Docker CI CD
Strong understanding of distributed systems microservices and API development
Excellent communication and leadership skills