Applied Scientist

17 hours ago

Bengaluru, Karnataka, India Stellar Solutions Full time ₹ 20,00,000 - ₹ 25,00,000 per year

Job Title: Applied Scientist

Location: 100% Remote (India)

Duration: 12-Month Contract

About the Role

We are seeking a highly skilled Applied Scientist with expertise in machine learning, large-scale ML systems, and MLOps practices. In this role, you will design, develop, and deploy production-grade ML solutions while collaborating closely with cross-functional teams in engineering, analytics, and product.

Key Responsibilities
  • Design, develop, and deploy ML models into production environments with a focus on scalability and reliability.
  • Build and optimize recommendation systems, NLP models, time series forecasts, or pattern recognition solutions.
  • Contribute to large-scale software architectures, APIs, and model versioning systems.
  • Implement ML workflows with CI/CD, containerization, and orchestration tools.
  • Work on distributed model training, hyperparameter optimization, and GPU-accelerated deep learning.
  • Collaborate with teams to ensure responsible AI/ML practices, interpretability, and fairness in deployed models.
  • Engage with stakeholders to communicate technical concepts in a clear and actionable manner.
Required Qualifications
  • PhD in Computer Science, Applied Mathematics, Engineering, or a related quantitative field.
  • 4+ years of experience designing and deploying ML models in production.
  • 1+ year of experience in recommendation systems, NLP, time series, or pattern recognition.
  • Strong proficiency in Python (preferred), with additional experience in Java or C/C++.
  • Hands-on experience with ML frameworks: PyTorch, TensorFlow, or scikit-learn.
  • Proficiency with cloud-based ML platforms: AWS SageMaker, Azure ML, or GCP AI.
  • Strong foundation in probability theory, statistics, and machine learning algorithms.
  • Familiarity with MLOps/DevOps: CI/CD pipelines, GitHub Actions, Docker, Kubernetes, Terraform.
  • Strong collaboration and communication skills, with ability to work independently in a remote-first environment.
Preferred Qualifications
  • Experience in regulated industries (finance, healthcare, insurance).
  • Strong understanding of deep learning architectures: CNNs, RNNs, Transformers, GANs.
  • Expertise in GPU-based accelerated computing (CUDA, RAPIDS, NeMo, NIM, etc.).
  • Proficiency in Big Data technologies: Spark, Kafka, Redis, Elastic Search.
  • Strong background in API and microservices architecture.
  • Experience with real-time AI/ML solutions, distributed training, and automated workflows.
  • Background in responsible AI, interpretability, and fairness auditing.

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