We are looking for a hands-on technical project manager to drive AI & ML related project operations from inception to execution. The technical project manager is responsible for understanding solution requirements, maintaining schedules and timelines, enforcing deadlines and supervising team members.
To be successful as a technical project manager you must be highly organized. A good technical project manager is able to multitask successfully on both technical and project delivery fronts.
- Lead technical project management for AI/ML-driven projects from concept to execution.
- Define project deliverables, roles, and responsibilities.
- Collaborate with the team in solutioning, design, and code reviews.
- Manage AI/ML system development with stakeholders and internal teams.
- Develop and oversee project requirements, scope, and schedules.
- Assign tasks to engineers and monitor progress.
- Conduct technical team meetings and maintain project time frames.
- Provide hands-on technical project management throughout the project lifecycle.
- Maintain project timeframes, KPIs, and status reports.
- Work independently with minimal supervision.
- 3+ years of project management experience, 8+ years in software/systems engineering.
- Practical experience with at least one of Spring, Flask, Django, or Node.js.
- Strong SQL query skills is a must.
- Direct involvement with the team in design and code reviews is required.
- Knowledge of ETL (Extract, Transform, Load).
- Familiarity with AI platforms like OpenAI, Langchain, Llama index.
- Understanding of advanced analytics and machine learning pipelines.
- Hands-on experience with cloud platforms and APIs.
- Track record of moving technical projects from inception to delivery.
- Bachelor’s in Computer Science, MCA, or equivalent.
- Effective communication and agile methodology knowledge.
- Analytical and problem-solving skills.
- Ability to build relationships across teams and partners.
- Strong organizational and multitasking abilities.
- Background in Deep Learning, Machine Learning, Natural Language Processing.
- Knowledge of data engineering concepts, DataOps, and MLOps.