DE&A - AIML - Data Science - Conventional AI - Search

Zensar Technologies

Maharashtra

On-site

INR 4,000,000 - 6,500,000

Full time

8 hours ago
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Job summary

Zensar Technologies in Maharashtra seeks a PhD/MS-level AI researcher to advance theoretical and applied AI across finance, healthcare, and enterprise domains. You will design scalable algorithms, apply ML models, and publish findings while collaborating with researchers, engineers, and business partners.

The role emphasizes responsible AI, model interpretability, and cutting-edge techniques such as transformers, diffusion models, and knowledge graphs.

Qualifications

  • Ph.D. or Master’s in CS/Applied Mathematics/Engineering with AI/Optimization focus.
  • Proven experience in applied AI research with deployment in real-world settings.

Responsibilities

  • Experience in regulated industries (e.g., finance, healthcare, insurance).
  • Excellent communication and stakeholder engagement skills.
  • Strong in GPU-based accelerating computing technologies (CUDA, Rapids, NeMo, NIM).
  • Proficiency in model evaluation, distributed training, and hyperparameter optimization.
  • Proficient in Big Data Theory-based large-scale data streaming and in-memory DB techs (Spark, Kafka, Redis, Elastic Search).
  • Strong in automated workflows (GitHub Actions, Terraform, Helm) and containerization (Docker, Kubernetes).
  • Proficient in API, MCP and Microservices technologies.
  • Track records in large-scale, real-time AI/GenAI/AgenticAI/ML DB and solution techs.
  • Background in responsible AI/ML, model interpretability, and fairness auditing.

Skills

Linear algebra
Optimization
Algorithm design
Machine learning
Deep learning
NLP
Computer vision
Knowledge graph
Graph theory
Transformers
Generative modeling
PyTorch
TensorFlow
CUDA
GPU acceleration
DevOps
GitHub Actions
Docker
Kubernetes

Education

Ph.D. or Master’s in CS/Math/Engineering with AI/Optimization focus

Tools

Neo4j
cuGraph
Docker
Kubernetes
Spark
Kafka
Redis
Elastic Search
GitHub Actions
Terraform

Job description

Job Description
  • Strong foundation in mathematics: linear algebra, probability, stochastics, optimization theory
  • Expertise in mathematical programming, algorithm design, and optimization techniques
  • Skilled in formulating complex problems and designing scalable algorithms (e.g. linear/non-linear programming, convex optimization, combinatorial algorithms, etc.) and experience improving algorithms for efficiency and scalability
  • Deep knowledge of machine learning, deep learning, and statistical modeling
  • Strong in Graph Theory or Knowledge Graph related architecture and database (e.g. Neo4j, cuGraph)
  • Hands-on experience with neural networks, transformers, diffusion models, or generative modeling
  • Familiarity with NLP, computer vision, or domain-specific AI applications
  • Proficient in model evaluation, validation, and performance metrics
  • Experience with AI/ML frameworks and libraries (e.g. TensorFlow, PyTorch)
  • Familiarity with software development practices (version control, testing, GPU accelerated computing)
  • Strong analytical thinking and problem-solving skills
  • Ability to derive insights and prove algorithmic effectiveness through rigorous logic and math
  • Demonstrated creativity in tackling open-ended research and real-world AI challenges
  • Clear communicator, able to translate complex ideas for technical and non-technical audiences
  • Effective collaborator in cross-functional teams with researchers, engineers, and business partners
  • Skilled in writing technical documentation, reports, and academic publications is a plus
  • Passion for AI advancement and continuous learning
  • Active interest in emerging AI research, with contributions to publications, open-source projects or conference preferred
Responsibilities
  • Experience in regulated industries (e.g., finance, healthcare, insurance)
  • Excellent communication and stakeholder engagement skills
  • Strong in GPU based accelerating computing technologies (CUDA, Rapids, NeMo, NIM, etc.)
  • Proficiency in model evaluation, distributed training, and hyperparameter optimization
  • Proficient in Big Data Theory based large scale data streaming and in-memory database technologies (Spark, Kafka, Redis, Elastic Search)
  • Strong in automated workflow technologies (GitHub Actions, Terraform, Helmet) and containerization technologies (Docker, Kubernetes)
  • Proficient in API, MCP and Microservices technologies
  • Track records in large-scale, real-time AI/GenAI/AgenticAI/ML database and solution technologies
  • Background in responsible AI/ML, model interpretability, and fairness auditing
Qualifications
  • Ph.D.'s or Master's in Computer Science, Applied Mathematics, Engineering, or related field with AI/Optimization focus
  • Proven experience in applied AI Research with deployment of AI solutions in real-world settings
About Us

At Zensar, we're "experience-led everything". We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.

Part of the $4.8 billion RPG Group, we're a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.

We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.

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