Things to Look Out For
1. Identify Key ML Skills
When defining your requirements, consider specific areas of expertise you will need, such as
- Experience with different algorithms
- Data preprocessing techniques
- Model deployment and
- Knowledge of specific ML frameworks.
2. Address Security Concerns
ML projects rely on large datasets so robust security is crucial. Ensure the partner has strong data security protocols to mitigate data breaches, leaks, and compliance risks
3. Innovation
Look for teams that can solve complex business challenges, not just apply routine automation techniques
Work Ethic
1. Code Quality
You should look for developers who write clean, high-quality code, follow best practises, and keep the code easy to maintain and scale.
2. Efficiency
You should make sure developers optimize database performance.
3. Quality Assurance
Someone who is capable of doing proper testing and evaluation for AI models.
Check for Culture Fit
1. Developers Who Communicate Clearly
They explain not just what they’re doing, but why it matters and how it benefits the business, ensuring alignment with your goals.
2. Problem-Solver Who Fills the Gaps
Proactive and adaptable, they identify issues and address them without waiting to be told—bringing value where it’s needed most.
3. Strategic Thinker
Someone who plans ahead, considers the bigger picture, and builds solutions that scale as your business grows.
