Key Responsibilities:

• Lead a team of AI ML engineers, providing technical guidance, mentorship, and support.

• Collaborate directly with client teams to understand business problems, explain technical solutions clearly, and lead the implementation of AI/ML features while representing 3Pillar’s technical excellence.

• Lead technical execution of AI/ML projects from experimentation to production.

• Translate business problems into AI/ML solutions and manage solution delivery.

• Guide team members on model selection, evaluation, fine-tuning, and Gen AI usage.

• Collaborate with product, data engineering, and software teams for integrated delivery.

• Conduct code reviews, ensure best practices, and contribute to model deployment pipelines.

• Maintain documentation and model governance as per responsible AI standards.

• Define project goals, scope, and deliverables in collaboration with stakeholders.

• Create scalable architecture and robust machine learning systems that meet business objectives of a software product.

• Collaborate with cross-functional teams to integrate machine learning solutions into existing products and workflows.

• Establish best practices and standards for machine learning development within the organization.

• Monitor and evaluate the performance of machine learning models in production and implement improvements as needed.

• Stay updated on industry trends and advancements in machine learning technologies.

• Implement, deploy, optimize AI/ML algorithms and models into production environments.

• Conduct experiments, perform data analysis, and present findings to stakeholders.

Minimum Qualifications:

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; a Master’s degree is preferred.

• 8+ years of experience in building AI models with ML, NLP and deep learning.

• Proven track record of successfully delivering machine learning projects from concept to production.

• Strong leadership, interpersonal skills, and ability to effectively communicate technical concepts to non-technical stakeholders.

• Excellent problem-solving abilities and attention to detail.

• Strong knowledge of AI/ML techniques, algorithms, and frameworks. Experience building and deploying ML models (classification, NLP, forecasting). 

• Experience with cloud platforms such as AWS, Azure, or Google Cloud.

• Strong programming skills in Python, and familiarity with libraries such as PyTorch, TensorFlow, and Scikit-Learn.

• Exposure to Matplotlib, Seaborn, or Plotly

• Solid understanding of machine learning concepts, algorithms, and statistical methods. 

• Experience with computer vision libraries (OpenCV, etc.) and NLP libraries (spaCy, Hugging Face, etc.). 

• Knowledge of MLOps practices and experience with CI/CD tools.

• Good understanding of using LLMs via APIs or fine-tuning open-source models.

• Hands-on with data prep (Pandas, Spark), feature engineering, model training and tuning. 

• Knowledge of vector stores, embeddings, and LLMOps tools (LangChain, LlamaIndex, etc.).

• Experience with at least one cloud platform and CI/CD for ML (GitHub Actions, MLflow, etc.).

• Exposure to monitoring frameworks (evidently.ai, whylogs, or custom dashboards).

• Proven ability to work independently and with a team.

• Extensive expertise in refining LLMs, implementing RAG architectures, Weaviate vector databases, and advanced prompt engineering.

Additional Experience Desired:

• Led teams building GenAI, LLM, or agentic AI applications.

• Experience building reusable AI frameworks or platforms.

• Experience with vector databases (FAISS, Pinecone), RAG, Hugging Face.

• Contributions to research papers, blogs, or open-source projects.