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AI Research Scientist

RDAlabs
Bengaluru, Karnataka

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Job details

Qualifications

TensorFlow
Elasticsearch
Image processing
Doctoral degree
Computer Science
Applied Mathematics
Signal processing
MCP
Kubernetes
Computer vision
Big data
Software deployment
Spark
Git
Research
Master's degree
Microservices
Analysis skills
C++
Math
Docker
C
Machine learning
Neo4j
Terraform
Deep learning
Redis
Algorithm design
Natural language processing
Software development
GitHub
APIs
Scalability
Kafka
AI
Communication skills
Graph databases
Python

Full job description

Education :

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

Experience:

3–5 years of hands-on experience developing AI/ML algorithms and solution frameworks
2-3 years of experience in one or more domains: language model, computer vision, signal processing, generative AI, optimization programming, recommendation systems, or autonomous agents
1+ year of experience in agentic AI and/or AI reasoning, Digital Twins, Decision/Prescriptive AI
3-5 years of programming in Python and C++. CUDA is a plus

Skills:

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

Preferred Skills:

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

Apply Now

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