Procigma - Manager - Artificial Intelligence & Machine Learning
2 days ago
Position : Manager - AI & Machine Learning
Location : Gurgaon/ Bengaluru
Organisation : Permanent opportunity with a US MNC
Timings : Regular day shift
Overview :
We are looking for a Manager AI & Machine Learning Engineering to lead a team of ML engineers in developing and deploying high-impact machine learning solutions across core enterprise functions including Sales, Service, Finance, Order Fulfillment, and Supply Chain. This role requires a strong mix of technical leadership, people management, and strategic alignment to guide ML engineers from ideation through production deployment.
Youll play a key role in shaping the AI/ML delivery roadmap, establishing scalable engineering practices, and driving value through predictive models integrated into critical business workflows.
Responsibilities :
1. Team Leadership and Talent Development :
- Manage, coach, and grow a high-performing team of machine learning engineers, promoting a culture of innovation, collaboration, and continuous learning.
- Provide technical direction, architectural oversight, and career mentorship.
- Define team objectives and success metrics aligned with enterprise priorities.
2. Program Execution and Delivery :
- Drive the successful execution of ML use cases such as customer churn prediction, upsell opportunity scoring, demand forecasting, and operational risk detection.
- Work closely with data science, data engineering, product, and business stakeholders to define and deliver scalable ML solutions.
- Oversee delivery timelines, model development, deployment readiness, and feedback integration.
3. ML Engineering and MLOps Strategy :
- Establish best practices in model development, deployment, and monitoring, using tools like MLflow, SageMaker, Azure ML, Airflow, or Kubeflow.
- Guide the team in implementing CI/CD for ML pipelines, model versioning, feature stores, and performance monitoring.
- Champion a strong foundation in software engineering, code quality, and reusability in ML development.
4. Functional & Cross-Domain Focus :
- Align ML efforts with key business domains such as Sales (lead scoring, renewals), Service (case triage), Finance (forecasting), Order Fulfillment (ETA, risk), and Supply Chain (inventory planning, logistics optimization).
- Collaborate with business owners to prioritize high-impact ML use cases and ensure adoption and value realization.
5. Technology & Architecture Oversight :
- Partner with data platform and infrastructure teams to scale ML solutions using Snowflake, Datarobots, and enterprise cloud platforms (AWS, Azure, GCP).
- Ensure ML models integrate seamlessly with business systems such as Salesforce, Oracle Fusion Cloud, and other operational tools.
Required :
- Total 10+ years of experience in machine learning, data science, or engineering roles, with minimum 3+ years in a technical leadership or management capacity.
- Proven experience building and deploying machine learning solutions in production environments.
- Hands-on background with Python, ML frameworks (scikit-learn, PyTorch, TensorFlow), and orchestration tools.
- Strong understanding of MLOps practices, model lifecycle management, and pipeline automation.
- Experience working with cross-functional stakeholders to deliver ML-powered business solutions.
Preferred :
- Experience supporting business functions such as Sales, Finance, or Supply Chain with applied ML.
- Familiarity with cloud platforms (AWS, Azure, or GCP) and enterprise data tools (Snowflake, dbt, Matillion).
- Exposure to enterprise platforms such as Oracle Fusion Cloud, Salesforce, or ServiceNow.
(ref:hirist.tech)
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