AI Engineering Manager

Ford Motor Company

AI Engineering Manager leading end-to-end AI/ML solutions across SSDA. Collaborating with teams to drive enterprise-grade AI adoption and implement best practices for project lifecycles.

Posted 7/21/2026full-timeChennai • 🇮🇳 IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading the design and deployment of AI/ML solutions, with a strong focus on Generative AI technologies and MLOps principles. Proven ability to manage high-performing teams and align AI initiatives with business outcomes.

Highest-signal resume keywords

AI/ML Solution DevelopmentGenerative AI TechnologiesCloud AI Platforms (GCP)Team Leadership in AI/Data ScienceAdvanced Predictive Analytics Techniques

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonRSparkSQLPredictive AnalyticsNeural NetworksNatural Language Processing (NLP)Genetic AlgorithmsEnsemble LearningDesign of Experiments

Tools & Technologies

MLOpsLLMOpsEnterprise AI Architecture Patterns

Certifications & Qualifications

Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Statistics, Applied Mathematics, ITMaster’s or PhD in Data Science, Machine Learning, Statistics, Applied Mathematics, or Computer Science

Industry Keywords

AI Project LifecycleData AcquisitionEnterprise AI DeploymentAI AdoptionBusiness Outcomes

Tech Stack

Tools & technologies

CloudGoogle Cloud PlatformPythonSparkSQL

About the role

Key responsibilities & impact

Lead the design, development, deployment, and scaling of AI/ML and Generative AI solutions across SSDA within GDIA.
Define and govern AI project lifecycles — from data acquisition and experimentation to production deployment, monitoring, and continuous optimisation.
Lead AI engineers and data scientists, establish best practices, and drive enterprise-grade AI adoption using modern MLOps and LLMOps principles.
Collaborate with business stakeholders, product leaders, engineering teams, and enterprise architects to ensure AI investments are aligned with measurable business outcomes.

Requirements

What you’ll need

Bachelor’s Degree in a related field (Data Science, Machine Learning, Computer Science, Statistics, Applied Mathematics, IT, or equivalent).
5 to 8 years of experience applying analytical methods and AI/ML solutions in enterprise environments.
5 to 8 years of experience using Python-based AI/ML technologies.
Experience leading AI or Data Science teams.
Experience acting as a senior technical lead facilitating solution trade-offs and architectural decisions.
Experience using Cloud AI Platforms (GCP preferred).
Hands-on experience with Generative AI technologies and enterprise AI deployment.
Master’s or PhD in Data Science, Machine Learning, Statistics, Applied Mathematics, or Computer Science (preferred).
Experience managing and growing high-performing AI teams (preferred).
Expert-level knowledge in advanced predictive analytics and AI techniques (Genetic Algorithms, Ensemble Learning, Neural Networks, NLP, Simulation, Design of Experiments) (preferred).
Strong working knowledge of GCP and enterprise AI architecture patterns (preferred).
Expertise in open-source technologies such as Python, R, Spark, SQL (preferred).
Experience building enterprise-grade GenAI and agent-based AI solutions (preferred).

Benefits

Comp & perks

Health insurance
401(k) matching
Flexible work hours
Paid time off
Professional development opportunities