Artificial Intelligence/Machine Learning Engineer
2 days ago
Description :
We are looking enthusiastic AI/ML Developer with 3 years of relevant experience in machine learning and artificial intelligence.
    The candidate should be well-versed in designing and developing intelligent systems and have a solid grasp of data handling and model deployment.
Key Responsibilities : 
- Develop and implement machine learning models tailored to business needs.
    - Develop and fine-tune Generative AI models (e.g., LLMs, diffusion models, VAEs) using platforms like Hugging Face, LangChain, or OpenAI.
    - Conduct data collection, cleaning, and pre-processing for model readiness.
    - Train, test, and optimize models to improve accuracy and performance.
    - Work closely with cross-functional teams to deploy AI models in production environments.
    - Perform data exploration, visualization, and feature selection
    - Stay up-to-date with the latest trends in AI/ML and experiment with new approaches.
    - Design and implement Multi-Agent Systems (MAS) for distributed intelligence, autonomous collaboration, or decision-making.
    - Integrate and orchestrate agentic workflows using tools like Agno, CrewAI or LangGraph.
    - Ensure scalability and efficiency of deployed solutions.
    - Monitor model performance and perform necessary updates or retraining.
Requirements :
- Experience working with vector databases (Pinecone, Weaviate, Chroma) for RAG systems.
- Good understanding of machine learning concepts, including classification, regression, clustering, and deep learning.
- Knowledge of knowledge graphs, semantic search, or symbolic reasoning.
- Proficiency in working with tools such as Pandas, NumPy, and data visualization libraries.
- Hands-on experience deploying models using REST APIs with frameworks like Flask or FastAPI.
- Familiarity with cloud platforms (AWS, Google Cloud, or Azure) for ML deployment.
- Knowledge of version control systems like Git.
- Experience with Natural Language Processing (NLP), computer vision, or predictive analytics.
- Exposure to MLOps tools and workflows (e.g., MLflow, Kubeflow, Airflow).
- Basic familiarity with big data frameworks like Apache Spark or Hadoop.
- Understanding of data pipelines and ETL processes.
What We Offer :
- A vibrant and learning-driven work culture.
- 5 days a week & Flexible work timings
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