We are seeking an experienced, leadership-driven AI/ML Engineer to lead our artificial intelligence initiatives and maintain the highest standards of model performance, system scalability, and technical innovation. In this senior role, you will oversee all aspects of the AI/ML lifecycle, including data ingestion, feature engineering, model training, deployment (MLOps), and ongoing monitoring. If you have strong team leadership skills, deep knowledge of modern machine learning frameworks, and a passion for operational excellence and robust AI solutions, this is an outstanding opportunity to shape the technical future and performance of our intelligent products.

Key Responsibilities
Team Leadership: Manage, mentor, motivate, and evaluate the entire AI/ML team, including ML engineers, data scientists, and research scientists.

Standards & Quality Control: Establish and enforce high coding standards, architectural patterns, and ethical AI/ML guidelines; conduct regular model audits and technical reviews.

Operations Planning: Develop and manage sprint cycles, experimental roadmaps, and model deployment pipelines to ensure efficient delivery and high system reliability.

Resource & Budget Management: Control cloud infrastructure costs for model training and inference, software licensing, and development tool budgets; manage relationships with cloud providers and tool vendors.

Stakeholder Collaboration: Collaborate with Product Management, Engineering, and Executive teams to translate business requirements into scalable, high-impact machine learning solutions.

Training & Development: Design and deliver comprehensive training programs on deep learning, MLOps, model deployment, and AI security; mentor team leads and engineers.

Compliance & Reliability: Ensure full adherence to data privacy regulations, ethical AI standards, and internal corporate security and governance guidelines.

Reporting & Continuous Improvement: Prepare reports on model accuracy, latency, and business impact; implement cutting-edge MLOps best practices and automated pipeline optimizations.

Requirements & Qualifications
Education: Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field is preferred. A Master’s or PhD is highly desirable.

Experience: 5–10+ years in software engineering and AI/ML, with at least 3–5 years in a technical leadership or engineering management capacity. Experience in deploying large-scale AI models in production environments is highly desirable.

Technical & Management Skills:

Strong knowledge of Python, machine learning frameworks (e.g., PyTorch, TensorFlow, JAX), and cloud-based AI platforms (AWS SageMaker, Azure ML, Vertex AI).

Experience with MLOps best practices, CI/CD pipelines, containerization (Docker/Kubernetes), and model monitoring tools.

Proven ability to lead high-performing teams and optimize end-to-end ML development lifecycles.

Soft Skills:

Excellent leadership, communication, and interpersonal skills.

Strong problem-solving, decision-making, and organizational abilities.

High attention to detail with a focus on scalable and maintainable AI architecture.

Ability to work under pressure and manage multiple technical priorities in a dynamic environment.

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