Manager Engineering

Caterpillar; Chennai; Vor Ort; INR 1.800.000 - 2.800.000; Vollzeit

Zusammenfassung

Caterpillar in Chennai, India, seeks an Engineering Manager – Data Science to lead multiple pods of data scientists and ML engineers, partnering with AI product owners and platform teams to ensure scalable, high-quality data science solutions.

You will coach, guide delivery, uphold MLOps standards, and champion responsible AI while aligning with business goals in a fast-paced, hybrid environment.

Qualifikationen

• Lead and develop high-performing technical teams delivering complex data science solutions.
• Guide teams in data science, ML, GenAI, and responsible AI practices.
• Plan, prioritize, and deliver in Agile or hybrid environments.

Aufgaben

• Lead, coach, and develop a team of data scientists and ML engineers.
• Ensure high-quality, timely delivery of data science products and platforms.
• Collaborate with AI Product Owners, AI Architects, and stakeholders.

Kenntnisse

Engineering Management

Data Science

ML Engineering

Delivery & Execution

Communication

GenAI

Ausbildung

Bachelor's degree in engineering/CS/DS

Postgraduate preferred

Tools

Python

ML platforms

Docker

Jobbeschreibung

## Manager EngineeringApply: Chennai, Tamil Nadu: Full time: Posted Today: R0000400683**Career Area:**Engineering**Job Description:****Your Work Shapes the World at Caterpillar Inc.**When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.## Role DefinitionThe Engineering Manager – Data Science is responsible for leading, coaching, and developing multiple pods of data scientists and machine learning engineers while ensuring high-quality, timely delivery of data science products and platforms. This role partners closely with AI product owners, AI architects, platform teams, and business stakeholders to ensure data science solutions are technically sound, scalable, and aligned to strategic outcomes.## ResponsibilitiesPeople Leadership & Talent Development • Lead, coach, and develop a team of data scientists and ML engineers • Set clear performance expectations and support career development • Foster an inclusive, high-performing team cultureTechnical & Engineering Leadership • Provide technical guidance across data science and ML solutions working closely with AI Architects • Ensure adherence to engineering standards and MLOps practices • Review model designs and deployment strategiesDelivery & Execution Management • Own delivery execution and capacity planning • Ensure predictable, high-quality delivery • Manage risks, dependencies, and technical debtStakeholder Collaboration • Partner with AI Product Owners and business stakeholders • Communicate progress, risks, and outcomes clearlyQuality, Governance & Responsible AI • Ensure solutions meet quality, security, and compliance standards • Uphold responsible AI principles## Degree RequirementBachelor’s degree in engineering, computer science, data science, or a related field (or equivalent practical experience). Post Graduate or higher is desired.## Skill Descriptors**Engineering Management**Demonstrated ability to lead and develop high‐performing technical teams delivering complex data science and machine learning solutions. Provides clear direction, sets expectations, and holds teams accountable for outcomes while supporting individual growth and engagement. Balances people leadership, technical oversight, and delivery execution in a fast‐moving environment.**Data Science & Machine Learning**Strong working knowledge of data science, machine learning, GenAI and statistical modeling concepts, including supervised and unsupervised learning, feature engineering, model evaluation, and experimentation. Able to guide and review technical approaches, challenge assumptions, and ensure solutions are fit for purpose without requiring hands‐on model development as a primary responsibility.**Delivery & Execution**Proven ability to plan, prioritize, and execute work in Agile or hybrid delivery environments. Manages team capacity, dependencies, and risks to ensure predictable delivery of high‐quality outcomes. Uses data and metrics to assess progress, identify issues early, and drive continuous improvement.**Communication & Collaboration**Excellent verbal and written communication skills, with the ability to clearly articulate complex technical concepts to non‐technical audiences. Builds strong partnerships with product owners, architects, platform teams, and business stakeholders to align expectations, manage trade‐offs, and deliver value.## Software Development Life CycleDemonstrated knowledge of software and data science development life cycles, including experimentation, prototyping, production deployment, and ongoing operations. Understands the differences between research‐oriented work and production‐grade solutions and guides teams accordingly.* Works within formal delivery and governance methodologies* Understands phases, activities, dependencies, and key decision points across the life cycle* Identifies common risks and quality considerations at each stage* Interprets and guides technical documentation, design artifacts, and delivery plans## Artificial IntelligenceWorking knowledge of artificial intelligence, GenAI and machine learning concepts, risks, and opportunities, with the ability to guide teams toward solutions that deliver business outcomes responsibly.* Understands AI methodologies, capabilities, and limitations* Guides teams in applying responsible AI principles, including fairness, transparency, robustness, and governance* Keeps informed of emerging AI technologies and evaluates their applicability to business needs* Supports the adoption of AI practices that balance innovation with risk management## Programming & Technical LiteracyStrong technical literacy across programming and data science tools sufficient to effectively review code, designs, and technical approaches.* Able to assess code quality, maintainability, and architectural alignment* Collaborates effectively with hands‐on engineers and data scientists* Understands testing, version control, and deployment concepts* Hands‐on coding is not a primary responsibility, but technical depth is sufficient to guide and challenge solutions## Technical TroubleshootingDemonstrated ability to lead teams through complex technical and operational issues across data, models, and production systems.* Guides investigation and resolution of data, model, and system issues* Reviews logs, metrics, and system behavior to support root cause analysis* Partners with platform and operations teams to resolve production incidents* Ensures issues are documented, learnings are captured, and preventative actions are implemented## NoteThis Job Description is intended as a general guide to the job duties for this position and is intended for the purpose of establishing the specific salary grade. It is not designed to contain or be interpreted as an exhaustive summary of all responsibilities, duties, and effort required of employees assigned to this job. At the discretion of management, this description may be changed at any time to address the evolving needs of the organization. It is expressly not intended to be a comprehensive list of “essential job functions” as that term is defined by the Americans with Disabilities Act.**Posting Dates:**October 16, 2026 - October 29, 2026