Roles and Skills
ECLARO delivers top talent for a variety of AI Engineer roles, tailored to meet different project needs, skills, and levels of experience and expertise. Although the specifics and titles may vary for each individual business, our experienced recruiters have a track record of success in helping businesses hire at all levels
Junior AI Engineers
Focus on developing basic AI models, assisting in the maintenance of existing AI systems, and debugging AI algorithms.
Mid-Level AI Engineers
Handle more complex AI tasks, integrate AI models with other technologies, and contribute to the development of new AI features.
Senior AI Engineers
Lead AI strategy and development, develop and implement advanced AI solutions, and manage AI projects from start to finish.
Key skills
- Machine Learning Model Development (TensorFlow, PyTorch, scikit-learn)
- Python Programming & Software Engineering
- Data Processing & Feature Engineering
- Deep Learning & Neural Network Architecture
- Natural Language Processing (NLP) & Computer Vision
- MLOps & Model Deployment (Docker, Kubernetes, cloud platforms)
- Problem-Solving & Cross-functional Communication
Frequently asked questions
What does an AI Engineer do on a daily basis?
AI Engineers design, develop, and deploy machine learning models that solve business problems. Day-to-day responsibilities include writing and optimizing code, training and evaluating models, analyzing datasets, troubleshooting model performance, collaborating with product and data teams, and maintaining production systems. They work across the full lifecycle—from problem definition and prototyping through deployment and ongoing monitoring.
What are the core technical qualifications hiring managers should look for?
Strong candidates have expertise in Python, machine learning frameworks (TensorFlow, PyTorch), and statistical/mathematical foundations. Look for for hands-on experience building production ML systems, familiarity with cloud platforms (AWS, GCP, Azure), and demonstrable ability to handle data pipelines and model optimization. Many have degrees in computer science, mathematics, or a related field, though practical experience and portfolios are equally valued. Certifications in cloud platforms or specialized ML tracks are beneficial additions.
How can ECLARO help us hire an AI Engineer quickly?
ECLARO maintains a network of pre-vetted AI Engineers ready for both contract and full-time placements. We handle recruitment, screening, and verification so your team can focus on integration. Whether you need someone for a short-term project, a strategic hire, or to augment your existing team, ECLARO matches engineers to your specific technical requirements, team culture, and project timeline—often filling roles within days rather than months.
What's the difference between hiring an AI Engineer vs. a Data Scientist through a staffing firm?
AI Engineers focus on engineering rigor—building scalable, production-ready systems and optimizing model performance at scale. Data Scientists focus more on analysis, statistical modeling, and business insight extraction. AI Engineers typically have stronger software engineering skills and deeper expertise in deployment and systems architecture. ECLARO can help you identify the right role for your need and source talent accordingly.
Ways to hire through ECLARO
ECLARO can fill this role through contract or contract-to-hire staffing, direct placement, an Employer of Record (EOR), recruitment process outsourcing (RPO), or a dedicated offshore team in the Philippines (ECAPTIVE).