Data Scientist

3 days ago

Jaipur Rajasthan, India Celebal Technologies Full time

**- Generative AI Solutions**: Develop innovative Generative AI solutions using machine learning and AI technologies, including building and fine-tuning models such as GANs, VAEs, and Transformers.

**- Classical ML Models**: Design and develop machine learning models (regression, decision trees, SVMs, random forests, gradient boosting, clustering, dimensionality reduction) to address complex business challenges.

**- Deep Learning Systems**:Train, fine-tune, and deploy deep learning models such as CNNs, RNNs, LSTMs, GANs, and Transformers to solve AI problems and optimize performance.

**- NLP and LLM Optimization**: Participate in Natural Language Processing activities, refining and optimizing prompts to improve outcomes for Large Language Models (LLMs), such as GPT, BERT, and T5.

**- Data Management & Feature Engineering**:Work with large datasets, perform data preprocessing, augmentation, and feature engineering to prepare data for machine learning and deep learning models.

**- Model Evaluation & Monitoring**: Fine-tune models through hyperparameter optimization (grid search, random search, Bayesian optimization) to improve performance metrics (accuracy, precision, recall, F1-score). Monitor model performance to address drift, overfitting, and bias.

**- Code Review & Design Optimization**: Participate in code and design reviews, ensuring quality and scalability in system architecture and development. Work closely with other engineers to review algorithms, validate models, and improve overall system efficiency.

**- Educational Background**:Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Data Science, or any related field.

**- Experience in Machine Learning**: Extensive experience in both classical machine learning techniques (e.g., regression, SVM, decision trees) and deep learning systems (e.g., neural networks, transformers). Experience with frameworks such as TensorFlow, PyTorch, or Keras.

**- Natural Language Processing Expertise**:Proven experience in NLP, especially with Large Language Models (LLMs) like GPT, BERT, or T5. Experience in prompt engineering, fine-tuning, and optimizing model outcomes is a strong plus.

**- Programming Skills**:Proficiency in Python and relevant libraries such as NumPy, Pandas, Scikit-learn, and natural language processing libraries (e.g., Hugging Face Transformers, NLTK, SpaCy).

**- Mathematical & Statistical Knowledge**:Strong understanding of statistical modeling, probability theory, and mathematical optimization techniques used in machine learning.

**- Model Deployment & Automation**:Experience with deploying machine learning models into production environments using platforms such as AWS SageMaker or Azure ML, GCP AI, or similar. Familiarity with MLOps practices is an advantage.

**- Code Review & System Design**: Experience in code review, design optimization, and ensuring quality in large-scale AI/ML systems. Understanding of distributed computing and parallel processing is a plus.

**Soft Skills & Behavioural Qualifications**:

- Must be a good team player and self-motivated to achieve positive results
- Must have excellent communication skills in English.
- Exhibits strong presentation skills with attention to detail.
- It’s essential to have a strong aptitude for learning new techniques.
- Takes ownership for responsibilities
- Demonstrates a high degree of reliability, integrity, and trustworthiness
- Ability to manage time, displays appropriate sense of urgency and meet/exceed all deadlines
- Ability to accurately process high volumes of work within established deadlines.

**Job Types**: Full-time, Permanent

Pay: ₹600,000.00 - ₹1,500,000.00 per year

**Benefits**:

- Health insurance
- Life insurance
- Paid sick time
- Paid time off
- Provident Fund

Schedule:

- Day shift
- Monday to Friday

Supplemental Pay:

- Performance bonus
- Yearly bonus

Application Question(s):

- How soon you can join ?

**Experience**:

- Data science: 3 years (required)

**Location**:

- Jaipur, Rajasthan (preferred)

Work Location: In person

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