ML Ops Engineering Manager

Key Skills

AWS, Azure, Continuous Integration & Continuous Delivery - CI/CD, Docker, Effective communication skills, Google Cloud Platform (GCP), Kubernetes-K8s, MLOps tools, Python Programming, PyTorch, TensorFlow

Job Description

At Ford Credit, we believe freedom of movement drives human progress. We also believe in providing you with the freedom to define and realize your dreams. With our incredible plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career potential as you help us define tomorrow’s transportation.

As the financial engine for Ford, Ford Credit is at the heart of the customer experience, transforming the way people access and interact with vehicle finance on a global scale.

Ford Credit is experiencing significant business transformation in an ever-changing digital world. To create this all-new automotive financing experience, within our Ford Credit Tech team we are gathering a team of world-class strategists, innovators, creators, and technology leaders, who will help to unlock the power of technology and transform our relationship with customers.

The Ford Credit Tech team in India is looking for a Senior MLOps Engineering Manager. and play a pivotal role in propelling us into the future of machine learning operations. We seek an individual with a hands-on approach to lead a team of ML engineers, shape our MLOps strategy, and actively contribute to the deployment and integration of machine learning solutions into our platform and products in a fast-paced environment.

RESPONSIBILITIES

• Develop and execute a comprehensive technical strategy, overseeing the architecture, design, implementation, and operation of ML lifecycle and Experimentation capabilities.
• Establish and lead a high-performing team, taking ownership of outcomes and fostering a culture of continuous learning and innovation.
• Roll up your sleeves and get hands-on with the daily operations of the team, writing and reviewing code, troubleshooting issues, and mentoring engineers.
• Drive operational excellence by consistently improving the capabilities.
• Create and maintain scalable MLOps frameworks and infrastructure that support the entire machine learning lifecycle, from data ingestion to model deployment and monitoring.
• Collaborate seamlessly with cross-functional teams, including data scientists, data engineers, software developers, and business stakeholders to prioritize robustness, scalability, and performance in the integration of machine learning models into production systems.
• Implement rigorous security best practices for machine learning infrastructure and applications, ensuring compliance with industry standards and regulations.
• Maintain comprehensive technical documentation, guidelines, and knowledge base articles to facilitate knowledge sharing and best practices.

QUALIFICATIONS

Must Have

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience managing a team of software engineers or MLOps teams.
• 3+ years of hands-on experience deploying and managing machine learning models in production environments.
• 10+ years of overall IT experience.
• Proficiency in programming languages such as Python, coupled with experience in machine learning frameworks (e.g., TensorFlow, PyTorch) and cloud platforms (e.g., AWS, Azure, GCP).
• Solid understanding of software engineering principles, CI/CD practices, and infrastructure automation tools (e.g., Docker, Kubernetes).
• Exceptional written and verbal communication skills with the ability to convey technical information to a wide variety of audiences.

Nice to have

• Master's degree in Computer Science, Engineering, or a related field.
• Relevant certifications in MLOps, cloud platforms, or project management.
• Proficiency in GCP services.
• Knowledge of security and privacy considerations in machine learning systems, encompassing aspects such as data encryption, access controls, and adherence to regulations like GDPR or HIPAA.