Lead AI Engineer

Technologies we use

Your responsibilities

• Collaborate with technical stakeholders to define the AI strategy and objectives.
• Leading the development of AI strategies and roadmaps aligned with business goals and objectives.
• Design and implement end-to-end AI pipelines, from data ingestion to model deployment.
• Designing and developing complex machine learning algorithms including advanced techniques in deep learning, reinforcement learning, or other AI subfields.
• Lead and manage a team of junior AI Ops Engineers.
• Provide technical guidance, mentorship, and career development to the team.
• Foster a culture of continuous learning, innovation, and best engineering practices.
• Developing robust strategies for deploying AI models into production environments
• Implement best practices for model versioning, monitoring, and scalability.
• Collaborate with DevOps teams to integrate AI pipelines into CI/CD workflows.
• Oversee the seamless deployment of AI models into production environments.
• Lead Implementation of monitoring solutions to track model performance, detect data drift, and ensure data quality.
• Ownership of end-to-end AI design and Implementation from technology perspective
• Ensure robust security controls and compliance with industry standards (e.g., GDPR, HIPAA) for AI systems.
• Collaborate with legal and compliance teams to address regulatory requirements.
• Work closely with cross-functional engineering teams to understand operational requirements.
• Communicate effectively with technical leaders, project managers, and business stakeholders.
• Provide regular updates on project progress, performance, and technical roadblocks.

Our requirements

• A relevant Bachelors or higher-education degree in Computer Science, Data Science, or related fields.
• 5+ years of experience in the field of AI operations, machine learning, and DevOps.
• Proven leadership experience, preferably leading small teams of AI Ops engineers.
• Minimum of 4 years of professional experience in AI Ops, machine learning, and DevOps.
• Preferred certifications in AI, machine learning, and cloud platforms (e.g., AWS, Azure, GCP).
• Proficiency in Python, SQL, and relevant AI libraries (e.g., TensorFlow, PyTorch).
• Familiarity with cloud platforms (e.g., GCP, AWS) and containerization (Docker, Kubernetes).
• Excellent problem-solving, critical thinking, and analytical skills.
• Excellent communication, collaboration, and leadership skills.
• Familiarity with AI best practices, including model versioning, monitoring, and automated deployment.
• Ability to travel to other client offices or locations as needed.

What we offer