Senior Manager, AI/ML Engineering
DU TECH Chennai, Tamil Nadu, India
IT Services and IT Consulting · 201-500 employees
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About the role
The Senior Manager leads AI/ML engineering delivery, overseeing platforms, model development, MLOps, and responsible AI initiatives. This role involves translating business priorities into actionable roadmaps while managing team performance, quality standards, and stakeholder partnerships.
What they look for
Requirements
Candidates must possess a bachelor's degree and 10 to 12 years of relevant experience in AI/ML engineering or a related field. Strong expertise in Python, machine learning frameworks, cloud AI services, and leadership within complex organizations is required.
Full description
Job Summary - Job Description (Internal) Job Summary - Job Advert (External)
The Senior Manager, AI/ML Engineering leads AI/ML engineering delivery and operational performance across AI/ML platforms, model development, MLOps, responsible AI, and production machine learning solutions. This people-leader role translates business and product priorities into plans, establishes quality and governance expectations, manages risks and dependencies, and develops a high-performing team that delivers measurable outcomes. DU Tech is looking for a Senior Manager, AI/ML Engineering to lead AI/ML engineering capabilities across AI/ML platforms, model development, MLOps, responsible AI, and production machine learning solutions. This role combines people leadership, delivery accountability, stakeholder partnership, and disciplined execution to deliver reliable, scalable, secure, and customer-focused outcomes.
Job Responsibilities
Delivery & Execution
- Lead planning, delivery, and operational performance for AI/ML engineering.
- Guide a team responsible for AI/ML platforms, model development, MLOps, responsible AI, and production machine learning solutions.
- Translate priorities into roadmaps, plans, backlogs, and measurable outcomes.
- Reinforce quality, architecture, security, privacy, compliance, and operational standards.
- Manage capacity, delivery risks, dependencies, budgets, and vendors as applicable.
- Use metrics to improve quality, speed, reliability, cost, and stakeholder value.
Support & Enablement
- Lead, coach, and develop team members; support hiring, performance, and talent processes.
- Build strong partnerships across business, product, architecture, security, data, and technology teams.
- Communicate priorities, progress, risks, and decisions clearly.
- Create an inclusive, accountable, and high-performing team environment.
Requirements
Education & Experience Type of Experience*
- Bachelor's degree in Computer Science, Information Technology, Engineering, Design, Analytics, Business, or a related discipline
- 10 to 12 years of relevant experience in AI/ML engineering or a closely related discipline
- Experience with AI/ML platforms, model development, MLOps, responsible AI, and production machine learning solutions
- Experience leading teams, workstreams, programs, or technology delivery in a complex organization
- Knowledge of Python, machine learning frameworks, cloud AI services, model deployment, monitoring, and MLOps
- Experience collaborating across business and technology teams
- Strong analytical, problem-solving, written, and verbal communication skills
Key Primary Skills
"• Bachelor’s degree in Computer Science, Engineering, or a related field
- 2+ years of experience in quality assurance, software testing, test automation; with increasing scope and complexity.
- Knowledge of Software Development Life Cycle (SDLC) and Software Testing Life Cycle (STLC).
- Strong analytical and problem-solving skills"
Secondary Skills
People leadership, delivery and execution management including performance coaching, reviews, career development and scheduling, prioritization, resource risk management
Preferred Qualifications & Interests (PQIs)
- Master's degree in a related technical or business field is preferred
- Advanced knowledge of Python, machine learning frameworks, cloud AI services, model deployment, monitoring, and MLOps
- Experience with enterprise-scale cloud, data, digital, retail, pharmacy, healthcare, or customer technology environments
- Experience working with global teams, managed service partners, or distributed delivery models
- Relevant industry, cloud, agile, product, architecture, data, security, design, or technology certifications are preferred
