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Salary
≈ $11k – $26k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff · 7+ years exp

Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Oct 17, 2026.

Overview
Company
Impact
Profile match
Tech Mahindra is a prominent Indian multinational information technology services and consulting enterprise specializing in digital transformation, cloud modernization, business process re-engineering, and network services. Headquartered in Pune, Maharashtra, India (with its registered office in Mumbai), the company is a flagship entity of the diversified Mahindra Group conglomerate. Established in 1986 (initially as Mahindra British Telecom), it operates across dozens of countries with a global delivery footprint serving enterprise clients in telecommunications, banking and financial services, healthcare, automotive, and retail. The organization is particularly recognized for its deep engineering heritage in telecommunications and 5G network integration, offering end-to-end solutions spanning artificial intelligence, enterprise application management, customer experience (CX), and next-generation connectivity infrastructure.
Backed by Seafund

Job Description

  • Skill Set :

    AI and Gen AI Architecture

  • Total Experience :

    7.00 to 10.00 Years

  • No of Openings :

    1

  • Job Post Date :

    07/09/2026

  • Job Expiry Date :

    31/10/2026

  • Domain :

    IT

  • Location :

    BENGALURU [India]

  • Job Reference No :

    4105661

Job Summary

Job Title: AI Developer

Job Title: AI Engineer - Recommender System & Decision Optimization

Location: Bengaluru, Hyderabad, PAN India

Years of Experience: 7-10 Years

Job Summary:

We are seeking a highly skilled AI Engineer with a strong background in implementing recommender systems and decision optimization engines. The ideal candidate will possess expertise in AI algorithms, including optimization, machine learning, and reinforcement learning. This role is critical in enhancing our analytics capabilities and driving data-driven decision-making processes.

Responsibilities:

  • Design, develop, and implement advanced recommender systems tailored to meet business needs.
  • Build and optimize decision-making engines using AI algorithms to improve operational efficiency.
  • Collaborate with cross-functional teams to gather requirements and translate them into technical specifications.
  • Conduct thorough data analysis to identify trends and insights that inform algorithm development.
  • Utilize process optimization techniques to enhance existing workflows and systems.
  • Monitor and evaluate the performance of AI models, making adjustments as necessary to improve accuracy and efficiency.
  • Stay updated with the latest advancements in AI and machine learning technologies.
  • Document processes, algorithms, and methodologies for future reference and knowledge sharing.

Mandatory Skills:

  • Proven experience in process optimization techniques and methodologies.
  • Strong proficiency in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Experience with reinforcement learning and its application in real-world scenarios.
  • Solid understanding of data structures, algorithms, and software engineering principles.
  • Ability to analyze large datasets and extract meaningful insights.
  • Excellent problem-solving skills and attention to detail.

Preferred Skills:

  • Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for deploying AI solutions.
  • Familiarity with big data technologies (e.g., Hadoop, Spark).
  • Knowledge of statistical analysis and data visualization tools.
  • Experience in Agile methodologies and project management.

Qualifications:

  • Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
  • 7-10 years of relevant experience in AI engineering, with a focus on recommender systems and optimization.
  • Strong communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
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