Applied Scientist

2 days ago

Bengaluru Karnataka, India Stellar IT Solutions LLC Full time

**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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