Vice President-Applied AI ML Lead

Description

Join us in shaping the future of data-driven decision-making. As a Lead Data Science, you will spearhead AI/ML engagements from conception to production, collaborating closely with business, governance, and tech stakeholders to articulate clear business use cases and deliver high-quality machine learning models, integrations and agentic solutions.

As a Vice President – Applied AI/ML Lead, you will become a seasoned member of our Architecture & AI/ML team. You will be responsible to lead and implement impactful data science, machine learning and agentic solutions / microservices and integrating them into our ecosystem of applications used by our Commercial Real-Estate business and clients. This hands-on role will provide rewarding opportunities to build end-to-end AI/ML solutions while partnering very closely with our agile engineering teams across the organization. Your expertise will help us unlock new insights and deliver exceptional value to our business partners.

Job Responsibilities:

Lead end-to-end AM/ML projects, interfacing with various stakeholders.

Hands on coding, testing and deployment of high-quality machine learning models, LLM integrations and agents.

Optimize and maintain AI/ML models for improved performance and accuracy.

Conduct data analysis and preprocessing for model training.

Manage project prioritization and lead technology meetings with stakeholders.

Participate in code reviews and foster a culture of continuous improvement.

Provide technical guidance and mentorship to engineering team members.

Required qualifications, capabilities, and skills:

M.S. degree in Statistics, Engineering, Computer Science, or Mathematics.

7+ years of experience in developing statistical or machine learning models.

5+ years of experience with AI, including reinforcement learning or optimization algorithms.

Proficient in Java or Python programming.

Deep knowledge of data structures, algorithms, machine learning, and statistics.

Experience with agentic frameworks & workflow tools like LangChain & LangGraph.

Expertise in at least one area: NLP, Computer Vision, Ranking and Recommendation, or Time Series Analysis.

Experience with machine learning frameworks like Scikit-Learn, etc.

Experience with LLM usage, integration, and custom models & fine-tuning.

Experience with ETL data pipelines and data warehousing.

Proficiency in SQL and NoSQL platforms for data mining and analysis and strong analytical and critical thinking skills and excellent communication skills and a team player.

Preferred qualifications, capabilities, and skills:

Experience with cloud computing platforms: AWS, Azure, Google Cloud

Experience with Spring-Boot / Flask or similar frameworks

Experience with Rest APIs (consumption & implementation)

Experience in distributed systems design, including microservices and messaging systems.

Familiarity with Financial Services and Real-Estate domains.