About the Role :
We are seeking a skilled and innovative Data Scientist to join our AI and Machine Learning team. In this role, you will focus on researching, developing, and deploying AI models and machine learning solutions. You will work with large datasets, apply statistical and ML techniques, and build scalable AI-driven systems to solve complex business problems.
Key Responsibilities :
- Analyze large and complex datasets to derive actionable insights.
- Design, develop, and deploy end-to-end AI / ML solutions.
- Build and fine-tune predictive models using supervised, unsupervised, and reinforcement learning techniques.
- Collaborate with cross-functional teams to integrate AI models into applications and systems.
- Implement and monitor scalable data pipelines and model deployment processes.
- Apply modern testing strategies and prompt engineering in AI model design.
- Leverage Azure and MLOps tools to manage workflows and ensure reproducibility.
- Stay up to date with advancements in AI / ML, NLP, and deep learning frameworks.
Required Skills : Proficient in :
Languages & Frameworks :
Python, R, FastAPIAzure UI Search API (React)Cloud & DevOps :
Azure Cloud (Basics), Azure DevOpsGitLab & GitLab PipelinesAnsible, REX for deploymentsDatabases & ETL :
Cosmos DB (API for MongoDB)Azure Data Factory, DatabricksMachine Learning & AI :
Data mining, data cleaning, and preprocessingSupervised and unsupervised learning techniquesNLP techniques and deep learning architectures (RNNs, Transformers)AI integration, deployment, and solution deliveryPyTorch and MLOps frameworksMonitoring data pipelines and model performanceData Science & Testing :
Prompt engineeringModern testing frameworks for AI systemsExpert-level Skills (in addition to the above) :
AI & Language Models :
Azure OpenAI ServicesGPT family models (GPT-3, GPT-4, GPT-4o)Embeddings and vector searchDeep Learning & ML Algorithms :
Advanced expertise in TensorFlow and PyTorchReinforcement learningDeep understanding of ML algorithms and architecturesMathematics & Statistics :
Strong foundation in linear algebra, calculus, probability, and statisticsStatistical and probabilistic modelingData Engineering & Big Data :
Azure Storage AccountsSpark, HiveAnalytics & Visualization :
Pandas, NumPy, SQLData visualization tools : Matplotlib, Seaborn, TableauAI-driven analytics and decision-making systemsPreferred Qualifications :
Bachelors / Masters / PhD in Computer Science, Data Science, Applied Mathematics, or related fields.Experience working with large-scale, real-time AI / ML applications.Published work in AI / ML conferences or open-source contributions is a plus.ref : hirist.tech)