Senior Manager (Machine Learning)

Sprinklr · Gurgaon

  • Experience7–20 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelexecutive
  • Posted3 Sept 2026
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About Sprinklr

Sprinklr is hiring in Gurgaon in technology software. This role looks for around 7+ years of experience.

Skills

  • Python
  • TensorFlow
  • PyTorch
  • scikit-learn
  • machine learning algorithms
  • deep learning
  • natural language processing
  • data mining
  • AWS
  • Google Cloud Platform
  • Microsoft Azure
  • MLOps
  • data privacy regulations
  • ethical AI

The role

A machine learning manager at a technology software company develops machine learning solutions and leads data science initiatives. The role applies artificial intelligence and data science to product-focused engineering.

Full job description

Responsibilities:

Lead the end-to-end lifecycle of AI/ML projects, from problem definition and data exploration to model development, deployment, and monitoring.

Manage and mentor a cross-functional team of AI/ML professionals.

Define the AI/ML roadmap and strategy aligned with business goals.

Oversee data governance, model accuracy, performance, and ethical AI practices.

Collaborate with engineering and product teams to integrate ML models into production systems.

Stay abreast of the latest AI/ML technologies, frameworks, and research.

Ensure scalability, reliability, and performance of AI/ML systems.

Present findings and insights to senior leadership and stakeholders.

Drive innovation by identifying new AI opportunities within the organization.

Requirements:

Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Mathematics, or a related field (Ph. D. preferred).

8+ years of experience in AI/ML, with at least 3 years in a leadership or managerial role.

Strong proficiency in Python, TensorFlow, PyTorch, Scikit-learn, or similar ML frameworks.

Deep understanding of machine learning algorithms, deep learning, NLP, and data mining techniques.

Experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools.

Proven track record of deploying AI solutions in production environments.

Excellent leadership, project management, and communication skills.

Knowledge of data privacy regulations and ethical AI practices.

Publications or patents in the AI/ML field.