About the Role:

We are looking for an experienced Engineering Manager AI/ML to lead a team of talented engineers and data scientists in developing scalable, production-grade AI and machine learning solutions. The ideal candidate combines strong technical expertise with people leadership, fostering collaboration, innovation, and operational excellence.

In this role, you will drive end-to-end AI/ML product delivery from architecture and experimentation to deployment and monitoring while building a high-performing engineering culture that aligns with organizational goals.

Key Responsibilities:

- Lead and mentor a team of AI/ML engineers, data scientists, and MLOps specialists.

- Oversee the design, development, and deployment of machine learning and AI-powered systems at scale.

- Collaborate with cross-functional teams (Product, Data, Cloud, and Engineering) to translate business problems into technical solutions.

- Establish and enforce best practices for software development, MLOps, and model governance.

- Drive technical excellence through architecture reviews, code quality, and robust testing standards.

- Manage project delivery timelines, priorities, and stakeholder expectations.

- Foster a culture of innovation, continuous learning, and collaboration within the AI/ML engineering team.

- Stay current with emerging AI technologies, frameworks, and tools to enhance capabilities and performance.

Required Qualifications:

- Bachelors or Masters degree in Computer Science, Engineering, Data Science, or related field.

- 812 years of total experience, with at least 3+ years in a technical leadership or people management role.

- Proven experience designing, developing, and deploying AI/ML or data-driven applications in production.

- Strong programming background in Python, with hands-on experience in frameworks like TensorFlow, PyTorch, or Scikit-learn.

- Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps tools (MLflow, Kubeflow, SageMaker, etc.).

- Deep understanding of model lifecycle management, CI/CD pipelines, and data versioning.

- Excellent problem-solving and analytical skills, with the ability to make data-driven decisions.

Preferred Qualifications:

- Experience working with Generative AI, LLMs, or NLP solutions.

- Exposure to data engineering and cloud-native AI platforms (Databricks, Azure ML, Vertex AI).

- Knowledge of AI governance, compliance, and ethical AI practices.

- Strong understanding of Agile methodologies and project management principles.

Soft Skills:

- Proven ability to lead, motivate, and develop engineering teams.

- Strong communication and stakeholder management skills.

- Ability to balance technical depth with strategic leadership.

- Proactive, adaptable, and comfortable working in a fast-paced environment.