AI/ML Engineering Manager

AI/ML Engineering Manager Job Description

The AI/ML Engineering Manager is a technical leadership role responsible for overseeing the development and implementation of artificial intelligence (AI) and machine learning (ML) solutions. The primary goal of this role is to lead a team of engineers and researchers in designing, building, and deploying AI/ML models and systems that drive business value.

Key Responsibilities:

1. Technical Leadership: Provide technical guidance and oversight to a team of AI/ML engineers and researchers, ensuring the development of high-quality AI/ML models and systems.
2. Strategy and Planning: Collaborate with cross-functional teams to develop and implement AI/ML strategies that align with business objectives.
3. Model Development: Oversee the design, development, and deployment of AI/ML models, including data preprocessing, feature engineering, model training, and model evaluation.
4. Data Management: Ensure the quality, integrity, and security of data used for AI/ML model development and deployment.
5. Engineering and Operations: Collaborate with engineering teams to ensure seamless integration of AI/ML models with existing systems and infrastructure.
6. Research and Development: Stay up-to-date with the latest advancements in AI/ML and identify opportunities to apply new techniques and technologies to drive business value.
7. Talent Development: Mentor and develop the skills of AI/ML engineers and researchers, ensuring the team has the necessary expertise to deliver high-quality AI/ML solutions.
8. Communication: Effectively communicate technical concepts and results to both technical and non-technical stakeholders, including business leaders and customers.

Technical Skills:

1. Programming languages: Python, Java, C++, etc.
2. AI/ML frameworks: TensorFlow, PyTorch, Scikit-learn, etc.
3. Data management: Data warehousing, data governance, data quality, etc.
4. Cloud platforms: AWS, Azure, Google Cloud, etc.
5. Containerization: Docker, Kubernetes, etc.
6. Agile methodologies: Scrum, Kanban, etc.

Soft Skills:

1. Leadership: Proven experience leading technical teams and mentoring engineers.
2. Communication: Excellent communication and presentation skills.
3. Collaboration: Ability to work effectively with cross-functional teams.
4. Problem-solving: Strong problem-solving skills, with the ability to analyze complex technical issues and develop creative solutions.
5. Adaptability: Ability to adapt to changing priorities and technical requirements.

Education and Experience:

1. Bachelor's degree: Computer Science, Mathematics, Statistics, or related field.
2. Master's degree or Ph.D.: Preferred, but not required.
3. 5+ years of experience: AI/ML engineering, software development, or related field.

3+ years of experience: Technical leadership or management role.

• Bachelor's Degree in Computer Science or a related technical discipline, or the equivalent combination of education, professional training or work experience (6 years)
• 8+ years of IT experience is required
• CISSP Required
• 5+ Years Cybersecurity experience (hands on)
• Experience in AI/ML development and design
• 6+ years of Python coding experience
• Hands on experience with Linux, Dockers
• Experience/ working knowledge of AWS, Google, Azure clouds
• Well versed in the NIST RMF and associated standards
• Extensive knowledge of Xacta Risk Management Solution