Description

You will leverage machine learning and GenAI technologies to extract insights from large datasets and solve complex problems.

Responsibilities

• Develop machine learning and deep learning solutions using supervised and unsupervised techniques including regression, classification, and clustering.
• Implement GenAI and Large Language Models, specifically working with architectures like BERT, RoBERTa, and transformers.
• Manage the full machine learning lifecycle, including feature engineering, training, validation, scaling, deployment, and monitoring.
• Translate business requirements into technical analytics and reporting to support data-driven decision-making.
• Collaborate with data engineers, product managers, and software developers to integrate models into production environments.

Required Skills

• 5–7 years of experience in data science or a related role.
• Advanced knowledge of NLP and deep learning architectures such as CNNs, RNNs, and transformers.
• Proficiency in Python and the Python ecosystem (Pandas, NumPy, Matplotlib, Seaborn).
• Hands-on experience with TensorFlow, PyTorch, SciKit-learn, Keras, and OpenCV.
• Experience with GenAI models including language generators, translators, and summarizers.
• Working knowledge of GCP, Databricks, and Spark.
• Experience with YAML and Terraform.
• Strong understanding of statistical methods, optimization, and pattern recognition.
• Ability to communicate technical model performance and data insights to non-technical stakeholders.

Preferred Skills

• Master’s degree or PhD in Computer Science, Statistics, or Applied Mathematics.
• Experience with SQL, Tableau, or Power BI.

Key Skills

Education

Any Graduate