EdgeVerve | Senior Artificial Intelligence Engineer | bangalore
1 month ago
Key Responsibilities:
- Machine Learning Model Development: Research, design, and implement advanced machine learning algorithms and models to address business challenges.
- Data Engineering: Extract, transform, and load (ETL) large datasets from various sources into a Postgres database.
- Model Deployment: Deploy machine learning models into production environments, ensuring optimal performance and scalability.
- AI Integration: Integrate AI capabilities into existing systems and applications.
- Team Leadership: Mentor and guide junior team members in machine learning and data science practices.
- Problem Solving: Analyze complex business problems and develop innovative solutions using machine learning techniques.
- Collaboration: Work closely with cross-functional teams to understand business requirements and translate them into technical solutions
Required Skill Set:
Technical Skills:
- AI: Understanding of AI concepts, Strong proficiency Gen AI base application development. Exposure to embedding and semantic search and RAG based application development.
- Machine Learning: Proficiency in machine learning algorithms (regression, classification, clustering, deep learning) and their implementation using Python libraries (TensorFlow, PyTorch, Scikit-learn).
- Programming: Expert-level Python programming skills, including data manipulation, statistical analysis, and model development.
- Database: Proficiency in SQL and experience with PostgreSQL for data storage and retrieval.
- Cloud Platforms: Familiarity with cloud platforms (AWS, GCP, Azure) for deploying and managing machine learning workloads.
- Data Engineering: Experience with data pipelines, ETL processes, and data preprocessing techniques.
- Big Data: Knowledge of big data technologies (Hadoop, Spark) is a plus.
Soft Skills:
- Problem Solving: Ability to analyze complex problems and develop effective solutions.
- Communication: Excellent communication skills to explain technical concepts to both technical and non-technical audiences.
- Collaboration: Strong teamwork and interpersonal skills to work effectively with cross-functional teams.
- Leadership: Ability to mentor and guide junior team members.
- Business Acumen: Understanding of business objectives and how machine learning can drive business value.
- Continuous Learning: Passion for staying updated with the latest advancements in machine learning and AI.
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