What You'll do:
- Apply leading Models to solve business problems
- Use models from GPT-* to LLama-* to solve wide range of business problems from sales tech, employee productivity, coding and automation
- Build RAG frameworks
- Build Langchain modules
- Model Development and Implementation:
- Design, develop, and deploy machine learning models to solve complex problems and improve user experiences, operational efficiency, or system performance.
- Utilize a variety of data sources, types, and structures to extract actionable insights through predictive analytics and data mining techniques.
- Research and Innovation:
- Stay abreast of the latest developments in the field of machine learning and artificial intelligence. Evaluate emerging trends and technologies for potential adoption to maintain and expand competitive advantage.
- Lead research initiatives that test new algorithms, evaluate new methodologies, and explore innovative uses of data that can lead to scalable solutions.
- Team Leadership and Development:
- Lead and mentor a team of machine learning engineers and data scientists. Ensure the continuous professional growth of team members through clear goal-setting, regular feedback, and development opportunities.
- Foster a collaborative and inclusive team workplace that encourages innovation and iterative learning.
- Cross-Functional Collaboration:
- Work closely with product management, software engineering, and data engineering teams to integrate machine learning models into larger software systems and product offerings.
- Partner with stakeholders across the organization to understand business needs and translate them into technical requirements and actionable machine learning projects.
- Project Management:
- Oversee the full project lifecycle for multiple machine learning initiatives, from ideation and data collection to model development and deployment.
- Manage resources, timelines, and risks effectively, ensuring that projects meet their objectives