AI/ML

Job Description:

• About the job
• Step into a high impact leadership role where you ll shape intelligent products and guide teams in building practical scalable AI solutions
• You ll work at the intersection of machine learning NLP and data driven experimentation turning complex business problems into models that deliver measurable outcomes
• This role is ideal for someone who enjoys mentoring engineers setting technical direction and collaborating closely with product data and engineering stakeholders
• You ll champion best practices across the ML lifecycle from data preparation and feature engineering to model deployment and continuous improvement while fostering a culture of curiosity ownership and learning
• If you re excited to lead with both technical depth and a collaborative mindset this is a chance to build meaningful AI capabilities and help teams deliver smarter experiences at scale

Key Responsibilities:

• Key Responsibilities
• Technical Leadership Delivery
• Lead end to end AI ML initiatives translating business goals into model strategies milestones and measurable success metrics
• Provide technical direction on model selection training approaches evaluation frameworks and deployment patterns for production grade ML systems
• Mentor and guide ML engineers and data scientists through design reviews code reviews and model performance deep dives
• Drive engineering excellence by defining standards for reproducibility experimentation tracking documentation and model governance
• Model Development AI ML NLP Data Learning
• Build and optimize machine learning models using structured and unstructured data ensuring robustness generalization and interpretability where needed
• Design and implement NLP pipelines for tasks such as text classification entity extraction semantic search summarization or intent detection based on product needs
• Partner with data stakeholders to improve data learning workflows data quality checks feature engineering labeling strategies and feedback loops
• Establish model evaluation practices including offline metrics error analysis bias checks and A B testing where applicable
• Collaboration Stakeholder Management
• Collaborate with product and engineering teams to align model capabilities with user experience latency scalability and reliability requirements
• Communicate technical trade offs and model outcomes clearly to both technical and non technical stakeholders
• Identify risks early data drift model decay dependency gaps and drive mitigation plans to ensure stable delivery
• Minimum Qualifications
• 5 9 years of overall experience with strong hands on ownership of AI ML solution delivery in real world environments
• Strong expertise in AI ML including model development training evaluation and iterative improvement
• Solid experience in NLP and applied learning from data data learning workflows feature engineering and experimentation
• Ability to lead technical discussions mentor team members and drive execution across multiple workstreams
• Education BTECH MTECH MCA MSC or equivalent

Technical Requirements:

• Good to have skills
• MLOps Model Monitoring Drift Detection Feature Store A B Testing Experimentation Data Engineering Pipelines

Additional Responsibilities:

• Preferred Qualifications
• Proven experience leading production ML deployments including monitoring retraining strategies and performance optimization over time
• Strong understanding of modern NLP approaches transformer based modeling embeddings prompt based workflows and how to evaluate them reliably
• Experience designing scalable ML architectures and collaborating closely with platform engineering teams to operationalize models
• Demonstrated ability to define best practices for experimentation versioning and model governance across teams
• Track record of delivering measurable business impact through ML initiatives and influencing stakeholders with data backed recommendations

Preferred Skills:

Technology->AI-AI Engineering->AI/ML Solution Architecture and Design